| "Data Science with Python - A Complete Guide!: 3-in-1" |
| "In todays world, everyone wants to gain insights from the deluge of data coming their way. Data Science provides a way of finding these insights, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis. Thanks to its flexibility and vast popularity that data analysis, visualization, and Machine Learning can be easily carried out with Python.Starting out at the basic level, this Learning Path will take you through all the stages of data science in a step-by-step manner.This comprehensive 3-in-1 course is a comprehensive course packed with step-by-step instructions, working examples, and helpful advice on Data Science Techniques in Python. Youll start off by creating effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience. Youll learn how to develop statistical plots using Matplotlib and Seaborn to help you get insights into real size patterns hidden in data. Also explore useful libraries for visualization, Matplotlib and Seaborn, to get insights into data.By the end of this course, youll become an efficient data science practitioner by understanding Python's key concepts! Contents and OverviewThis training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Learning Python for Data Science, covers data analytics and machine learning using Python programming. In this course youll learn all the necessary libraries that make data analytics with Python. Learn the Numpy library used for numerical and scientific computation. Employ useful libraries for visualization, Matplotlib and Seaborn, to provide insights into data. Explore coding on real-life datasets, and implement your knowledge on projects.By the end of this course, you'll have embarked on a journey from data cleaning and preparation to creating summary tables, from visualization to machine learning and prediction. The second course, Python Data Science Essentials, covers fundamentals of data science with Python. This course takes you through all you need to know to succeed in data science using Python. Get insights into the core of Python data, including the latest versions of Jupyter Notebook, NumPy, Pandas and scikit-learn. Delve into building your essential Python 3.6 data science toolbox, using a single-source approach that will allow to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and prepare for machine learning and visualization techniques.The third course, Practical Python Data Science Techniques, covers practical Techniques on Working with Data using Python. This video will begin from exploring your data using the different methods like data acquisition, data cleaning, data mining, machine learning, and data visualization, applied to a variety of different data types like structured data or free-form text. Deal with data with a time dimension and how to build a recommendation system as well as about supervised learning problems (regression and classification) and unsupervised learning problems (clustering). Perform text preprocessing steps that are necessary for every text analysis applications. Specifically, youll cover tokenization, stopword removal, stemming and other preprocessing techniques.By the end of the video course, you will become an expert in Data Science Techniques using Python.By the end of the course, youll learn the fundamentals of data science and gain an in-depth understanding of data analysis with various Python packages. About the AuthorsIlyas Ustun is a data scientist. He is passionate about creating data-driven analytical solutions that are of outstanding merit. Visualization is his favorite. After all, a picture is worth a thousand words. He has over 5 years of data analytics experience in various fields like transportation, vehicle re-identification, smartphone sensors, motion detection, and digital agriculture. His Ph.D. dissertation focused on developing robust machine learning models in detecting vehicle motion from smartphone accelerometer data (without using GPS). In his spare time, he loves to swim and enjoy the nature. He loves gardening and his dream is to have a house with a small garden so he can fill it in with all kind of flowers.Luca Massaron is a data scientist and a marketing research director specialized in multivariate statistical analysis, machine learning and customer insight with over a decade of experience in solving real world problems and in generating value for stakeholders by applying reasoning, statistics, data mining and algorithms. From being a pioneer of Web audience analysis in Italy to achieving the rank of top ten Kaggler, he has always been passionate about everything regarding data and analysis and about demonstrating the potentiality of data-driven knowledge discovery to both experts and non-experts. Favouring simplicity over unnecessary sophistication, he believes that a lot can be achieved in data science just by doing the essential.Marco Bonzanini is a data scientist based in London, United Kingdom. He holds a Ph.D. in information retrieval from the Queen Mary University of London. He specializes in text analytics and search applications, and over the years, he has enjoyed working on a variety of information management and data science problems. He maintains a personal blog, where he discusses different technical topics, mainly around Python, text analytics, and data science. When not working on Python projects, he likes to engage with the community at PyData conferences and meetups, and he also enjoys brewing homemade beer."
Price: 199.99 |
| "Neural Networks with TensorFlow - A Complete Guide!: 3-in-1" |
| "Tensorflow is Googles popular offering for machine learning and deep learning. It has become a popular choice of tool for performing fast, efficient, and accurate Deep Learning. TensorFlow is one of the newest and most comprehensive libraries for implementing Deep Learning and building CNNs. Neural Networks are at the forefront of almost all recent major technology breakthroughs. The intersection of big data, parallel programming, and AI generated a new wave of Neural Network research.Are you looking forward to getting hands-on and use Deep Learning to build CNNs and train efficient Neural Networks? If yes, then this is the course perfect for you! This comprehensive 3-in-1 course takes a solution-based approach where every topic is explicated with the help of a real-world example. Use Tensorflow to implement different kinds of Neural Networks from simple feedforward Neural Networks to multi layered perceptrons, CNNs, RNNs and more! Moreover, Implement multi layered perceptrons, CNN, and more using Tensorflow!By the end of the course, youll not just be able to build powerful Deep Learning models, but also accelerate the training of your models and scale them as required.Contents and OverviewThis training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Learning Neural Networks with Tensorflow, covers Neural Networks by solving real real-world datasets using Tensorflow. In this course, youll start by building a simple flower recognition program, making you feel comfortable with Tensorflow, and it will teach you several important concepts in Neural Networks. Next, youll start working with high-dimensional uses to predict one output: 1275 molecular features you can use to predict the atomization energy of an atom. The next program well create is a handwritten number recognition system trained on the famous MNIST dataset. In the final program, estimate what a celebrity looks like, checking for new pictures to see whether a celebrity is attractive, wears a hat, has lipstick on, and many more properties that are difficult to estimate with ""traditional"" computer vision techniques. After the course, youll not only be able to build a Neural Network for your own dataset, youll also be able to reason which techniques will improve your Neural Network.The second course, Advanced Neural Networks with Tensorflow, covers getting hands-on to understand Advanced Neural Networks with TensorFlow. You'll explore Deep Reinforcement Learning algorithms such as Generative Networks and Deep Q Learning. You will learn to implement some more complex types of neural networks such as Deep Q Learning with OpenAI Gym, autoencoders, and Siamese neural networks. During the course of the video, you will be working on real-world datasets to get a hands-on understanding of neural network programming. You will also get to train generative models and will learn Autoencoder applications. By the end of this course, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle.The third course, TensorFlow for Neural Network Solutions, covers exploring high-level concepts such as neural networks, CNN and RNN using TensorFlow. This course covers important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last section will show you how to take it to production. Once you are familiar and comfortable with the TensorFlow ecosystem, the last section will show you how to take it to production.By the end of the course, youll not just be able to build powerful Deep Learning models, but also accelerate the training of your models and scale them as required.About the Authors Roland Meertens is currently developing computer vision algorithms for self-driving cars. Previously he has worked as a research engineer at a translation department. Examples of things he has made are a Neural Machine Translation implementation, a post-editor, and a tool that estimates the quality of a translated sentence. Last year, he worked at the Micro Aerial Vehicle Laboratory at the university of Delft, on indoor localization (SLAM) and obstacle avoidance behaviors for a drone that delivers food inside a restaurant. Another thing he worked on was detecting and following people using onboard computer vision algorithms on a stereo camera. For his Master's thesis, he did an internship at a company called SpirOps, where he worked on the development of a dialogue manager for project Romeo. In his Artificial Intelligence study, he specialized in cognitive artificial intelligence and brain-computer interfacing. His research interests lie in machine learning techniques, human-robot interaction, brain-computer interfaces, and human-computer interaction. Nick McClure is currently a senior data scientist at PayScale, Inc. in Seattle, WA. Prior to this, he has worked at Zillow Group and Caesars Entertainment Corporation. He got his degrees in Applied Mathematics from The University of Montana and the College of Saint Benedict and Saint John's University. He has a passion for learning and advocating for analytics, machine learning, and artificial intelligence."
Price: 199.99 |
| "R: Machine Learning with R - Beginner to Expert!: 4-in-1" |
| "Machine learning is a subfield of computer science that gives computers the ability to learn without being explicitly programmed. It explores the study and construction of algorithms that can learn from and make predictions on data. R language is widely used among statisticians and data miners to develop statistical software and perform data analysis. It provides a cutting-edge power you need to work with Machine Learning techniques. This comprehensive 4-in-1 is a step-by-step real world guide on machine learning and deep learning that takes you through the core aspects for building powerful data science applications with the help of the R programming language. Apply R to simple predictive modeling with short and simple code. Dive into the advanced algorithms such as hyper-parameter tuning and DeepLearning, and putting your models into production!By the end of this course, you'll explore the advanced topics in machine learning with R in a step by step manner with examples to build powerful predictive models in R!Contents and OverviewThis training program includes 4 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Getting Started with Machine Learning in R, covers learning Machine learning techniques in the popular statistical language R. The course will take you through some different types of ML. Youll work with a classic dataset using Machine Learning. You will learn Linear and Logistic Regression algorithms and analyze the dataset. Youll explore algorithms like Random Forest and Naive Bayes for working on your data in R. Analysis of the data set is demonstrated from end to end, with example R code you can use. Then youll have a chance to do it yourself on another data set.By the end of the course you will learn how to gain insights from complex data and how to choose the correct algorithm for your specific needs.The second course, Advanced Machine Learning with R, covers advanced techniques like hyper parameter tuning, deep learning in a step by step manner with examples. In this course, youll get to know the advanced techniques for Machine Learning with R, such as hyper-parameter turning, deep learning, and putting your models into production through solid, real-world examples. In the first example, youll learn all about neural networks through an example of DNA classification data. Youll explore networks, implement them, and classify them. After that, youll see how to tune hyper-parameters using a data set of sonar data and youll get to know their properties. Next, youll understand unsupervised learning with an example of clustering politicians, where youll explore new patterns, understand unsupervised learning, and visualize and cluster the data.The third course, R Machine Learning solutions, covers building powerful predictive models in R. This video course will take you from very basics of R to creating insightful machine learning models with R. You will start with setting up the environment and then perform data ETL in R. Data exploration examples are provided that demonstrate how powerful data visualization and machine learning is in discovering hidden relationship. Youll then dive into important machine learning topics, including data classification, regression, clustering, association rule mining, and dimensionality reduction.The fourth course, Applied Machine Learning and Deep Learning with R covers building powerful machine learning and deep learning applications with help of the R programming language and its various packages. In this course, youll examine in detail the R software, which is the most popular statistical programming language of recent years. Explore different learning methods, clustering, classification, model evaluation methods and performance metrics. From there, youll dive into the general structure of the clustering algorithms and develop applications in the R environment by using clustering and classification algorithms for real-life problems Next, youll learn to use general definitions about artificial neural networks, and the concept of deep learning will be introduced. Finally, you will dive into developing machine learning applications with SparkR, and learn to make distributed jobs on SparkR.By the end of this course, you'll explore the advanced topics in machine learning with R in a step by step manner with examples to build powerful predictive models in R.About the AuthorsPhil Rennertis a Principal Research Engineer in Information Science, in the overall business of extracting wisdom from information overload. He has a long track record of solving challenging technical problems, innovating new techniques where existing ones don't apply. He is extensively skilled in machine learning, natural language processing, and data mining.Tim Hoolihancurrently works at DialogTech, a marketing analytics company focused on conversations. He is the Senior Director of Data Science there. Prior to that, he was CTO at Level Seven, a regional consulting company in the US Midwest. He is the organizer of the Cleveland R User Group. In his job, he uses deep neural networks to help automate of a lot of conversation classification problems. In addition, he works on some side-projects researching other areas of Artificial Intelligence and Machine Learning. Personally, he enjoys working on practice problems on Kaggle .com as well. Outside Data Science, he is interested in mathematical computation in general; he is a lifelong math learner and really enjoys applying it wherever he can. Recently, he has been spending time in financial analysis, and game development. He also knows a variety of languages: R, Python, Ruby, PHP, C/C++, and so on. Previously, he worked in web application and mobile development.Yu-Wei, Chiu (David Chiu) is the founder of LargitData Company. He has previously worked for Trend Micro as a software engineer, with the responsibility of building up big data platforms for business intelligence and customer relationship management systems. In addition to being a startup entrepreneur and data scientist, he specializes in using Spark and Hadoop to process big data and apply data mining techniques to data analysis. Yu-Wei is also a professional lecturer, and has delivered talks on Python, R, Hadoop, and tech talks at a variety of conferences. In 2013, Yu-Wei reviewed Bioinformatics with R Cookbook, a book compiled for Packt Publishing.Olgun is PhD candidate at Department of Statistics, Mimar Sinan University. He has been working on Deep Learning for his PhD thesis. Also working as Data Scientist.He is so familiar with Big Data technologies like Hadoop, Spark and able to use Hive, Impala. He is a big fan of R. Also he really loves to work with Shiny, SparkR. He has many academic papers and proceedings about applications of statistics on different disciplines. Mr. Olgun really loves statistic and loves to investigate new methods, share his experience with people."
Price: 199.99 |
| "Master Parallel & Concurrent Programming Using Python:2 in 1" |
| "Are you looking forward to get well versed with Parallel & Concurrent Programming Using Python? Then this is the perfect course for you!The terms concurrency and parallelism are often used in relation to multithreaded programs. Parallel programming is not a walk in the park and sometimes confuses even some of the most experienced developers.This comprehensive 2-in-1 course will take you smoothly through this difficult journey of current programming in Python, including common thread programming techniques and approaches to parallel processing. Similarly with parallel programming techniques you explore the ways in which you can write code that allows more than one process to happen at once.After taking this course you will have gained an in-depth knowledge of using threads and processes with the help of real-world examples along with hands-on in GPU programming with Python using the PyCUDA module and will evaluate performance limitations.Contents and OverviewThis training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Python Parallel Programming Solutions will teach you parallel programming techniques using examples in Python and help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, we move on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool. Next you will be taught about process-based parallelism, where you will synchronize processes using message passing and will learn about the performance of MPI Python Modules. Moving on, youll get to grips with the asynchronous parallel programming model using the Python asyncio module, and will see how to handle exceptions. You will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker.The second course, Concurrent Programming in Python will skill-up with techniques related to various aspects of concurrent programming in Python, including common thread programming techniques and approaches to parallel processing.Filled with examples, this course will show you all you need to know to start using concurrency in Python. You will learn about the principal approaches to concurrency that Python has to offer, including libraries and tools needed to exploit the performance of your processor. Learn the basic theory and history of parallelism and choose the best approach when it comes to parallel processing. About the Authors:Giancarlo Zaccone, a physicist, has been involved in scientific computing projects among firms and research institutions. He currently works in an IT company that designs software systems with high technological content.BignumWorks Software LLP is an India-based software consultancy that provides consultancy services in the area of software development and technical training. Our domain expertise includes web, mobile, cloud app development, data science projects, in-house software training services, and up-skilling services"
Price: 199.99 |
| "Julia: From Julia's Zero to Hero: 2 in 1" |
| "Are you looking forward to get well versed with Julia? Then this is the perfect course for you!Julia is a young language with limited documentation and although rapidly growing, a small user community. Most developers today will know the object oriented paradigm used in mainstream languages such as Python, Java and C++. This presents a challenge switching to Julia which is more functionally oriented.With this comprehensive 2-in-1 course takes a practical and incremental approach. It teaches the fundamentals of Julia to developers with basic knowledge of programming. It is taught in a hands on approach, with simple programming examples the student can try themselves. Building on that, it will invite the user to a tour of the ecosystem of Julia through practical code examples.By end of this course you will more productive and acquire all the skills to work with data more efficiently. Also help you quickly refresh your knowledge of functions, modules, and arrays & shows you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation & also get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform.Contents and OverviewThis training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Getting Started With Julia covers complete INSTALLATION AND SETUP along with basic of Julia. This course will not only introduce the language, but also explain how to think differently about problems with the Julia approach. This course also focuses various aspects such as Functional Programming in Julia, Metaprogramming, Debugging and Testing & much more.The second course, Julia Solutions covers consist complete guide to programming with Julia for performing numerical computation will make you more productive and able to work with data more efficiently. The course starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. Well also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation. Later on, youll see how to optimize data science programs with parallel computing and memory allocation. Youll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform. This course also includes videos on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the course, you will acquire the skills to work more effectively with your data.About the Authors:Erik Engheim is a professional mobile developer with experience in many different programming languages, often in combination. Erik Engheim has worked with C/C#, Java, C++, Objective-C, and Swift before moving into Julia. His experience with Julia involves automation, and high performance processing of code strings.Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in machine learning, data science, data analysis, computational statistics, and natural language processing (NLP). Rohit currently works as a senior data scientist at Zomato, also having worked as the first data scientist at Kayako.He is part of the Julia project, where he develops data science models and contributes to the codebase. Additionally, Raj is also a Mozilla contributor and volunteer, and he has interned at Scimergent Analytics."
Price: 199.99 |
| "Automation Testing with Selenium WebDriver 3.x: 4-in-1" |
| "There is often a need to test your web applications against a vast number of browsers and platforms due to their increasing complexity. For this, you need to build reliable and maintainable test automation cases. Here's where Selenium comes in. This comprehensive 4-in-1 course is a step-by-step guide with a practical approach to help you learn how to create extremely reliable and stable automation tests with Selenium WebDriver. You will learn to design advanced and easy to maintain test automation frameworks with browser factory, Page Object Models, and Selenium Grid from scratch. You will utilize the Advanced User Interactions API to quickly spin up a Selenium Grid or run tests on the cloud.This training program includes 4 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Dive into Core of Selenium Automation, starts off with explaining you how to solve difficult problems that you will undoubtedly come across as you start using Selenium in an enterprise environment. You will then learn to produce the right feedback when failing and what the common exceptions are, explain them properly (including the root cause), and fix them. You will also see the differences between the three available implicit waits and explicit waits, and learn to work with effective page objects. Next, you will learn how to utilize the advanced user interactions API and how you can run any JavaScript you need through Selenium. Finally, you will learn hard assertions and soft assertions and how to use them.The second course, Advanced Selenium Automation, covers delving into the world of advanced Selenium automation. In this video, youll focus on more advanced usage of the Selenium API to enable cross-browser testing, as well as simulating advanced user interactions with complex applications. Debugging rare test failures through advanced techniques and utilizing the specialized parts of each client library are covered as well.The third course, Optimizing Selenium Test Performance, covers benefits and advantages of Selenium 3.0. Focus on the most common performance bottlenecks and how to work round them through optimization and parallelization. You'll finish the course with the use of Selenium Grid and Sauce Labs for limitless parallelization and other goodies.The fourth course, Mastering Selenium WebDriver 3.X Test Automation, starts off with explaining you how to create extremely reliable and stable automation tests with Selenium WebDriver. You will then learn how to design advanced and easy to maintain test automation frameworks with browser factory, Page Object Models, and selenium grid from scratch. You will also utilize the Advanced User Interactions API to quickly spin up a selenium grid or run tests on the cloud.By the end of this Learning Path, you will have developed a practical knowledge of using Selenium WebDriver to create comprehensive test cases skillfully.Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:Dmitry Shyshkin is a lead QA automation engineer at FareCompare .com with 6 years of test automation experience using Selenium. He has worked in Waterfall and Agile environment, on desktop, web-based and mobile projects. He started his QA career without any QA/Testing knowledge. He took online Software QA classes where he learned about different types of testing. On his second job, he learned about test automation for the first time, and liked it more than manual testing and thereby decided to move into test automation."
Price: 199.99 |
| "The Complete PowerShell 6.x Masterclass: 3-in-1" |
| "PowerShell has become the most efficient tool for managing Windows systems. It combines command-line speed, the flexibility of scripting, and the power of a GUI-based admin tool. Its ability to solve problems efficiently and then to turn that solution into a new tool or automated task allows the system administrators to eliminate future manual labor hours. So, if youre a sysadmin who wants to perform complex administration in a timely manner with less effort, then go for this Learning Path. This comprehensive 3-in-1 course is a comprehensive tutorial with a set of scenarios, real-world examples, and scripts to easily get you started with Windows PowerShell 6.0 and its capabilities. You will be able to perform complex administration and automation tasks using PowerShell 6.x with ease and will master the new features and changes that it brings to create, manage, and operate virtual machines and their underlying storage and network components in your Azure cloud environment.This training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.In the first course, Automating Your Systems with PowerShell 6.x, you will discover the core features of PowerShell and build consistent patterns to work with software and infrastructure through scripts and command-line administration.The second course, Mastering System Administration with PowerShell 6.x, starts off with windows system administration and explores different features, services, shares, and permissions. You will then learn Windows Management Instrumentation (WMI), which is an essential aspect of PowerShell 6. You will also work on managing remote systems, creating and connecting reusable remote sessions to multiple systems, invoking commands on remote machines, and closing connections and deleting remote sessions. Next, you will discover what managing your infrastructure through code means using the popular Desired State Configuration feature of PowerShell. Finally, you will see how PowerShell has expanded its influence across the datacenter, as you use PowerShell to manage Active Directory, Azure, IIS, and more.In the third course, Azure PowerShell on the Cloud, you will start by learning the core concepts of working with Azure, including getting signed in, saving credentials, and working with resource groups. You will then learn how to use Azure PowerShell to manage three of the most useful infrastructure resources Azure customers use in their environments: storage, network, and virtual machines. You will also learn how to deploy Azure resources through Azure RM templates.Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:Michael Simmons is an IT Professional with over 20 years of experience managing and administering technology and helping the people who use it. He started using PowerShell and became involved in the community in 2007 and started iLovePowerShell .com in 2010 as a blog and resource for the community where he discusses PowerShell and how to use it to improve your career. As a PowerShell expert and evangelist, he continues to spread knowledge from an admin/tech support perspective. He's driven to teach IT professionals to write great code, empowering them to take control of their job and acquire an inspiring career. His technical and industry coverage has been featured on Petri .com and TomsItPro .com."
Price: 199.99 |
| "Docker Fundamentals" |
| "Docker is a leading software container platform. Using containers, Docker guarantees that a particular application will always run the same, regardless of where it's deployed.The course begins with a basic introduction to Docker, and explore our first Hello world! example. You then move on to Docker installation and more Hello world! examples on various platforms, and explore the Docker architecture and its major components such as the Docker Registry, Docker containers, and so on. Moving ahead, you will delve deeply into understanding Docker containers one of the most important features in Docker. We also look at container and data management, customizing Docker images using Dockerfile, uploading images to the registry, and Dockerfile best practices. Along with learning Docker, you will also learn how Docker simplifies DevOps automation.By the end of this course, you will successfully deploy applications in a Docker container.About the AuthorSreeprakash (or Sree) Neelakantan is a Cloud and DevOps enthusiast based in India. He has worked as the Information Technology Manager at KLM Royal Dutch Airlines and is also the Winner of the Top Quality Performance Award from KLM for cost reduction and Process Enhancement.He is the founder and the Chief Cloud Architect at Schogini Systems Pvt. Ltd. Sree holds multiple Amazon AWS certifications including DevOps Engineer Professional. Apart from his Electrical Engineering Degree (with honors) from the prestigious College of Engineering, Trivandrum, he also has studied Advanced Programming Techniques from TIFR (Tata Institute of Fundamental Research), Mumbai. He spends time conducting technology training workshops both online and onsite for organizations. He has traveled to 30+ countries to train and implement technology solutions."
Price: 199.99 |
| "Java: Object-Oriented Programming Concepts" |
| "Java is a mature, elegant and sophisticated object oriented language that runs in a JVM (Java Virtual Machine).Once compiled into bytecode, Java can run in a JVM regardless of the underlying environment, Java is Write once and run anywhere. Over the years Java has built for itself the reputation of a language that is capable of delivering high performance robust applications that are elegant,structured and sophisticated. Java is about the Object Oriented way.There are several aspects of the Java language that must be mastered for a developer to use Java at its full potential: The distinction between Classes and Objects, the interaction of Objects and Classes in the forging of an application, the concepts of OO programming (Inheritance and Polymorphism, Abstract Classes and Interfaces, Abstraction and Encapsulation), the memory model, Object identity, the Java Collections framework.You will learn about all these fundamental aspects in this course.About the AuthorRichard Naoufal started coding in Java around 2003. After working as a developer, an architect, a technical project manager he is now a trainer and a consultant. His focus today concerning Java is to make the best of it."
Price: 199.99 |
| "Java SE 8 Programmer 1" |
| "Java is the leading programming language of choice for over 9 million developers and is deployed on billions of devices and servers worldwide. It drives websites, desktop applications, mobile phones, IOT devices, and much more. It has been adopted by everyone from large multinational corporations to small local business.This course is designed for the beginner who wants to learn Java and for any Java developer who wants to become an Oracle Certified Associate Java Programmer by taking the Java SE 8 Programmer I exam. This course is ideal for those coming from another language and who want to get up-to-speed quickly.You will be taken on a journey through the fundamental concepts of the Java language and given the knowledge necessary to write your own Java application. You will learn about flow control by using loops, decision logic, and exception handling; you will learn how to manipulate data and store it in a data structure. Once you are comfortable using these constructs, youll learn how to structure classes and design applications using object-oriented concepts.Once you have completed this course you will be able to write and launch a Java application and ready to take the Associate exam.About the AuthorAlex Theedom is a senior Java developer with over 10 years' experience developing Spring and Enterprise Java applications in a variety of sectors including finance, gambling, and e-learning. He is a regular speaker at conferences such as JavaOne, Devoxx, jDay, VoxxedDay, and JEEConf.He shares his passion for Java through courses recorded for some of the best-known training providers and has published many articles for Java blogs."
Price: 199.99 |
| "Learning Functional Programming with F#" |
| "In todays world fully functional web applications are a key requirement and a necessity.We can have a run through developing web applications that includes server-side as well as the client-side programming using Fable, F# to JavaScript compiler.We will focus on the .NET Core platform so that your application will work in a cross-platform manner.About the AuthorOnur Gumus is a Lead Software Engineer based in Dubai. He has diverse interests in software development, architecture, Wing Chun, and Chess. He spends most of his time building .NET applications. His previous experience is as Software Architect at P.I. Works, where he developed several F# projects and gave internal tutorials to the developers. He is extremely passionate about F# and functional programming, and hopes to spend more and more time helping developers in the community to become proficient at functional programming."
Price: 199.99 |
| "Continuous Integration and Automation with Jenkins: 2-in-1" |
| "In agile development practices, developers need to integrate their work frequently to fix bugs or to create a new feature or functionality. Jenkins is used specifically for continuous integration, helping to enforce the principles of agile development. Jenkins is one of the most popular and leading Continuous Integration servers on the market today. This popularity is because, it is an open source project and a very flexible tool, which you can easily use it to automate all of the steps of your software delivery process on any platform. It is designed to maintain, secure, communicate, test, build, and improve the software development process. Setting up Jenkins and running build jobs is not enough for a production infrastructure. This comprehensive 2-in-1 course a modular and highly interactive approach, providing a general introduction and explanatory, hands-on content. Youll start off with configuring Jenkins effectively to work with Git in building and testing your software. Youll discover the process of using Jenkins to build, test, and package Java applications. Youll also learn about the extensible features of Jenkins with automated deployment on a cloud platform.By the end of the course, youll be able to set up the stage for a DevOps culture by learning Continuous Integration, automating your Jenkins projects and getting continuous feedback for your upstream & downstream projects!Contents and OverviewThis training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Effective Jenkins: Getting Started with Continuous Integration, covers Continuous Integration, automate your Jenkins projects and get continuous feedback for your upstream & downstream projects. In this first volume, you will understand the key concepts of CI and CD, as well Continuous Deployment. Get started with Jenkins by installing and configuring a Master and Node server. Once this is done, understand the main parts of Jenkins and create different types of Jenkins projects to automate everything that you want. Youll finish the section by looking to a Java web project and create the necessary steps for build and test it, therefore you can implement it to your real project.The second course, Hands-On Continuous Integration and Automation with Jenkins, covers building, testing, and packaging applications with Jenkins in this hands-on video course supported by practical real-world examples. This video course delves into the installation of the required software dependencies and libraries and demonstrates the workflow you'll need to follow to perform continuous integration for a sample application. From there, you will learn how to integrate code repositories and build tools in order to build code pipelines to implement both continuous integration and continuous delivery. Finally, you will also learn to automate deployment to a cloud platform such as AWS.By the end of the course, youll be able to set up the stage for a DevOps culture by learning Continuous Integration, automating your Jenkins projects and getting continuous feedback for your upstream & downstream projects! About the AuthorsRodrigo Russo is a Certified Jenkins Engineer and has 14+ years' experience in software development with different programming languages and technologies in different countries (Brazil, US, Portugal, Germany and Austria) and projects in companies ranging from a financial institution to game and e-commerce ventures including Walmart .com, Good game Studios and HERE. He is an enthusiastic practitioner of agile methodologies, Continuous Delivery and DevOps, with large-scale adoption experience. He is always seeking to optimize the software development life cycle through automation, process improvements, developing new tools and techniques. Rodrigo holds a B.S. in Computer Science and a post-graduate in Software Engineering.Sandro Cirulli is a certified Jenkins engineer, co-maintainer of XSpec, an open source unit testing framework for XML technologies, and co-organizer of DevOps Oxford Meetup. Sandro currently works as Lead Language Technologist in the Dictionaries department of Oxford University Press (OUP) where he's in charge of system administration, cloud, and DevOps. Sandro holds an MS degree in Computer Science from Oxford Brookes University and blogs at sandrocirulli .net."
Price: 199.99 |
| "Deep Learning with TensorFlow and Google Cloud AI: 2-in-1" |
| "Deep learning is the intersection of statistics, artificial intelligence, and data to build accurate models. With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. Tensorflow is Googles popular offering for machine learning and deep learning. It has become a popular choice of tool for performing fast, efficient, and accurate deep learning. TensorFlow is one of the most comprehensive libraries for implementing deep learning.This comprehensive 2-in-1 course is your step-by-step guide to exploring the possibilities in the field of deep learning, making use of Google's TensorFlow. You will learn about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data with the help of insightful examples that you can relate to and show how these can be exploited in the real world with complex raw data. You will also learn how to scale and deploy your deep learning models on the cloud using tools and frameworks such as asTensorFlow, Keras, and Google Cloud MLE. This learning path presents the implementation of practical, real-world projects, teaching you how to leverage TensorFlows capabilities to perform efficient deep learning.This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Hands-on Deep Learning with TensorFlow, is designed to help you overcome various data science problems by using efficient deep learning models built in TensorFlow. You will begin with a quick introduction to TensorFlow essentials. You will then learn deep neural networks for different problems and explore the applications of convolutional neural networks on two real datasets. You will also learn how autoencoders can be used for efficient data representation. Finally, you will understand some of the important techniques to implement generative adversarial networks.The second course, Applied Deep Learning with TensorFlow and Google Cloud AI, will help you get the most out of TensorFlow and Keras to accelerate the training of your deep learning models and deploy your model at scale on the Cloud. Tools and frameworks such as TensorFlow, Keras, and Google Cloud MLE are used to showcase the strengths of various approaches, trade-offs, and building blocks for creating, training and evaluating your distributed deep learning models with GPU(s) and deploying your model to the Cloud. You will learn how to design and train your deep learning models and scale them out for larger datasets and complex neural network architectures on multiple GPUs using Google Cloud ML Engine. You will also learn distributed techniques such as how parallelism and distribution work using low-level TensorFlow and high-level TensorFlow APIs and Keras.By the end of this Learning Path, you will be able to develop, train, and deploy your models using TensorFlow, Keras, and Google Cloud Machine Learning Engine.Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:Salil Vishnu Kapur is a Data Science Researcher at the Institute for Big Data Analytics, Dalhousie University. He is extremely passionate about machine learning, deep learning, data mining, and Big Data analytics. Currently working as a Researcher at Deep Vision and prior to that worked as a Senior Analyst at Capgemini for around 3 years with these technologies. Prior to that Salil was an intern at IIT Bombay through the FOSSEE Python TextBook Companion Project and presently with the Department of Fisheries and Transport Canada through Dalhousie University.Christian Fanli Ramsey is an applied data scientist at IDEO. He is currently working at Greenfield Labs a research center between IDEO and Ford that focuses on the future of mobility. His primary focus on understanding complex emotions, stress levels and responses by using deep learning and machine learning to measure and classify psychophysiological signals.Haohan Wang is a deep learning researcher. Her focus is using machine learning to process psychophysiological data to understand peoples emotions and mood states to provide support for peoples well-being. She has a background in statistics and finance and has continued her studies in deep learning and neurobiology.Christian and Haohan together they make dyad machina and their focus area is at the interaction of deep learning and psychophysiology, which means they mainly focus on 2 areas: - They want to help further intelligent systems to understand emotions and mood states of their users so they can react accordingly - They also want to help people understand their emotions, stress responses, mood states and how they vary over time in order to help people become more emotionally aware and resilient"
Price: 199.99 |
| "Python Foundations: The Road to Succinct Python 3: 3-in-1" |
| "Python is an easy to learn, powerful programming language. Its elegant syntax and dynamic typing, together with its interpreted nature, makes it an ideal language for scripting and rapid application development in many areas and on most platforms. If you're a developer who wish to build a strong programming foundation with this simple yet powerful programming language Python, then this learning path is for you. This comprehensive 3-in-1 course is packed with step-by-step instructions, working examples, and helpful advice to teach you the programming aspects of Python and use them to build powerful applications. You will learn concepts such as variables, functions, loops, data types, lists, decorators, and working with strings. You will also be able to write Python code in a smarter way by learning various object-oriented programming concepts and techniques. You will explore data structures and algorithms in Python by implementation of different types of data structure, spanning from linear data structures to tree graph algorithms.This training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Getting Started with Modern Python, starts off with setting up your development environment, including downloading Python and setting up your IDE (PyCharm). You will then be introduced to Python lists and list comprehensions. You will also understand what a generator is and why you need to use it. Next, you will learn how to use functions and decorators. You will learn how to create a very simple, single-file Python program, and how to execute it both from the command line and from within the IDE. Finally, you will learn to debug Python programs.The second course, Getting Started with Object-Oriented Programming in Python 3, begins with building objects and classes, followed by developing constructors and destructors to call and kill the objects. You will then get a detailed understanding of Inheritance and its dependence on objects. Based on their data types, you will learn to process objects differently through polymorphism, while abstraction techniques will enable you to hide data from a user. To ensure efficient coding, you will be introduced to exceptions and error handling. Furthermore, encapsulation with methods and variables will help you to keep data safe from external, unwanted interference. Finally, you will be taken through recursion mechanisms.The third course, Python Data Structures and Algorithms, starts off with covering the basics of data structures, linked lists, and arrays in Python. You will then learn how to code tuples in Python followed by an example that shows how to program dicts and sets in Python. You will also understand and implement stack, queue, and hash tables. Next, you will learn how to use tree/graph data structures including binary trees, heaps and priority queues in Python. Finally, you will be shown how to apply different algorithms such as Graph traversal, Shortest Path, Minimum Spanning Tree, Maximum Flow tree, and DAG topological sorting.By the end of this Learning Path, you will be well-versed with the programming concepts in Python 3 to write Python programs in a better and efficient manner.Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:Joran Beasley has over 7 years of experience as a professional software developer (primarily in Python) and is an active contributor to the Python community. He has previously worked with Packt Publishing as a tech reviewer.Besides being a Computer Science Instructor, Indrasen Pilankar has more than 8 years of experience in the computational field. He geeks out on networking, working on various open source projects based on this, as well as IoT, Cloud Computing, Linux, Android, and more. Opening up devices rather than using them has been a hobby of his ever since he was a kid because he's more interested in understanding the device. A hardcore hardware guy, he builds devices such as tablets and storage devices and also solves day-to-day tech problems. Apart from the tech world, he loves cats and plays basketball.Harish Garg, founder of BignumWorks Software LLP is a data scientist and a lead software developer with 17 years of software Industry experience. BignumWorks Software LLP is an India based Software Consultancy that provides consultancy services in the area of software development and technical training. Harish has worked for McAfeeIntel for 11+ years. He is an expert in creating data visualizations using R, Python, and web-based visualization libraries.Mithun Lakshmanaswamy, part of BignumWorks Software LLP, has been developing applications in Python for more than nine years. He has written enterprise level distributed applications that are deployed on scores of servers and have the ability to support thousands of users simultaneously. Some of the applications he has developed are related to parsing millions of virus definitions, analyzing network packets from an enterprise setup, etc. He is also quite proficient in the teaching technical concepts and is quite involved with his current orgs training programmes. He has worked on multiple projects working with Python, AWS etc implementing the concepts of concurrent and distributed computing."
Price: 199.99 |
| "Microservices with Spring Cloud" |
| "In this course, you will learn how to split an existing application into smaller services and what you need to build, deploy, and run it. You will learn how you can use Docker to support your local development and how you can utilize it to run your application in the cloud. To work with multiple services, you will need (for example) service discovery and reverse proxies. To be able to maintain the development pace, you also need to break up your user interface, so every service can serve its own UI, and you need to learn how to communicate with these services synchronously using REST and asynchronously using events. To run your application, you need to know what is going on in your distributed application, so monitoring and tracing calls is an important topic as well, and one that you'll learn about. So overall, this course will give you valuable insights and recipes with which to create your own distributed application, for deployment to the cloud.You will also see what needs to be done to upgrade a Spring Boot 1.x service to Spring Boot 2 with the recent Spring Cloud release.About the AuthorPatrick Cornelissen is a software developer at heart and the founder and CEO of the Orchit GmbH and kulinariWeb GmbH. He has written a number of applications in various languages and platforms and specializes in microservice-based applications and the transition of monolithic applications into microservices. He has been using the Spring Framework since 2009 and has been a big fan ever since. After his family, software craftsmanship is a passion of his that he pursues whenever he has any spare time. For this, he has organized, for example, code retreats and open space conferences in the past. He enjoys both learning and teaching new things in the field of (agile) software development."
Price: 199.99 |
| "Deep Learning with Python - A Complete Guide!: 2-in-1" |
| "Deep learning is the next step to machine learning with a more advanced implementation. Deep learning is currently one of the best providers of solutions regarding problems in image recognition, speech recognition, object recognition, and natural language with its increasing number of libraries that are available in Python.With deep learning being used by many data scientists, deeper neural networks are evaluated for accurate results. Deep Learning is revolutionizing a wide range of industries. For many applications, Deep Learning has been proven to outperform humans by making faster and more accurate predictions.This comprehensive 2-in-1 course takes a solution-based approach where every topic is explicated with the help of a real-world example. It is is a unique blend of independent solutions arranged in the most logical manner. Use Python frameworks such as TensorFlow, Caffe, Keras, and Theano for Natural Language Processing, Computer Vision, and more!By the end of the course, youll not only dive into the future of Data Science but also implement intelligent systems using Deep Learning with Python!Contents and OverviewThis training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Deep Learning with Python, covers implementing intelligent systems using deep learning with Python. This course takes you from basic calculus knowledge to understanding backpropagation and its application for training in neural networks for deep learning and understand automatic differentiation. Through the course, we will cover thorough training in convolutional, recurrent neural networks and build up the theory that focuses on supervised learning and integrate into your product offerings such as search, image recognition, and object processing. Also, we will examine the performance of the sentimental analysis model and will conclude with the introduction of Tensorflow. By the end of this course, you can start working with deep learning right away. This course will make you confident about its implementation in your current work as well as further research.The second course, Python Deep Learning Solutions, covers over 20 practical videos on neural network modeling, reinforcement learning, and transfer learning using Python. This course provides a top-down and bottom-up approach to demonstrating Deep Learning solutions to real-world problems in different areas. These applications include Computer Vision, Generative Adversarial Networks, and time series. This course presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, it provides a discussion on the corresponding pros and cons of implementing the proposed solution using a popular framework such as TensorFlow, PyTorch, and Keras. The course includes solutions that are related to the basic concepts of neural networks; all techniques, as well as classical network topologies, are covered. The main purpose of this video course is to provide Python programmers with a detailed list of solutions so they can apply Deep Learning to common and not-so-common scenarios.By the end of the course, youll dive into the future of Data Science and implement intelligent systems using Deep Learning with Python.About the AuthorsEder Santana is a PhD candidate on Electrical and Computer Engineering. His thesis topic is on Deep and Recurrent neural networks. After working for 3 years with Kernel Machines (SVMs, Information Theoretic Learning, and so on), Eder moved to the field of deep learning 2.5 years ago, when he started learning Theano, Caffe, and other machine learning frameworks. Now, Eder contributes to Keras: Deep Learning Library for Python. Besides deep learning, he also likes data visualization and teaching machine learning, either on online forums or as a teacher assistant.Indra den Bakker is an experienced Deep Learning engineer and mentor. He is the founder of 23insights (part of NVIDIA's Inception program), a machine learning start-up building solutions that transform the world's most important industries. For Udacity, he mentors students pursuing a Nanodegree in Deep Learning and related fields, and he is also responsible for reviewing student projects. Indra has a background in computational intelligence and worked for several years as a data scientist for IPG Mediabrands and Screen6 before founding 23insights."
Price: 199.99 |
| "Practical scikit-learn for Machine Learning: 4-in-1" |
| "Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. scikit-learn is arguably the most popular Python library for Machine Learning today. Due to its popularity and coverage of a wide variety of ML models and built-in utilities, jobs for scikit-learn are in high demand, both in industry and academia.scikit-learn is one of the most powerful Python Libraries with has a clean API, and is robust, fast and easy to use. It solves real-world problems in the areas of health, population analysis, and figuring out buying behavior, and more!This comprehensive 4-in-1 course is an easy-to-follow, step-by-step guide that will help you get to grips with real-world applications of algorithms for Machine Learning. Youll firstly learn how to build and evaluate the performance of efficient models using scikit-learn. Observe data from multiple angles and use machine learning algorithms to solve real-world problem to make your projects successful. Use Regression Trees, Support Vector Machines, K-Means Clustering, and customer segmentation algorithms in real world situations. Finally, apply your knowledge to practical real-world projects using ML models to get insightful solutions!By the end of this course, you'll build a strong foundation for entering the world of Machine Learning and data science with Pythons own scikit-learn the help of this comprehensive guide!Contents and OverviewThis training program includes 4 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Machine Learning with scikit-learn, covers learning to implement and evaluate machine learning solutions with scikit-learn. This course examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It also discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. Youll learn to use scikit-learns API to extract features from categorical variables, text and images; evaluate model performance; and develop an intuition for how to improve your models performance.By the end of this course, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.The second course, Fundamentals of Machine Learning with scikit-learn, covers building strong foundation for entering the world of Machine Learning and data science. In this course you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are: Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, and Feature engineering. In this course, you will also learn how these algorithms work and their practical implementation to resolve your problems.The third course, Hands-on scikit-learn for Machine Learning, covers Machine Learning projects with Pythons own scikit-learn on real-world datasets. If youre an aspiring machine learning engineer ready to take real-world projects head-on, Hands-on scikit-learn for Machine Learning will walk you through the most commonly used models, libraries, and utilities offered by scikit-learn. By the end of the course, you will have a set of ML problem-solving tools in the form of code modules and utility functions based on scikit-learn in one place, instead of spread over several books and courses, which you can easily use on real-world projects and data sets.The fourth course, Real-World Machine Learning Projects with scikit-learn, covers prediction of heart disease, customer-buying behaviors, and much more in this course filled with real-world projects. In this course you will build powerful projects using scikit-learn. Using algorithms, you will learn to read trends in the market to address market demand. You'll delve more deeply to decode buying behavior using Classification algorithms; cluster the population of a place to gain insights into using K-Means Clustering; and create a model using Support Vector Machine classifiers to predict heart disease. By the end of the course you will be adept at working on professional projects using scikit-learn and Machine Learning algorithms.By the end of this course, you'll build a strong foundation for entering the world of Machine Learning and data science with Pythons own scikit-learn the help of this comprehensive guide!About the AuthorsGiuseppe Bonaccorso is an experienced team leader/manager in AI, machine/deep learning solution design, management, and delivery. He got his MSc Eng in electronics in 2005 from the University of Catania, Italy, and continued his studies at the University of Rome Tor Vergata and the University of Essex, UK. His main interests include machine/deep learning, reinforcement learning, big data, bio-inspired adaptive systems, cryptocurrencies, and NLP.Farhan Nazar Zaidi has 25 years' experience in software architecture, big data engineering, and hands-on software development in a variety of languages and technologies. He is skilled in architecting and designing networked, distributed software systems and data analytics applications, and in designing enterprise-grade software systems. Farhan holds an MS in Computer Science from University of Southern California, Los Angeles, USA and a BS in Electrical Engineering from University of Engineering, Lahore, Pakistan. He has worked for several Silicon-Valley companies in the past in the US as a Senior Software Engineer, and also held key positions in the software industry in Pakistan. Farhan works as consultant, solutions developer, and in-person trainer on big data engineering, microservices, advanced analytics, and Machine Learning.Nikola Zivkovic is a software developer with over 7 years' experience in the industry. He earned his Masters degree in Computer Engineering from the University of Novi Sad in 2011, but by then he was already working for several companies. At the moment he works for Vega IT Sourcing from Novi Sad. During this period, he worked on large enterprise systems as well as on small web projects. Also, he frequently talks at meetups and conferences and he is a guest lecturer at the University of Novi Sad."
Price: 199.99 |
| "Moodle: A Complete Guide: 3 in 1" |
| "Are you looking forward to get well versed with performing various activities in moodle? Then this is the perfect course for you.Moodle is one of the most popular open source platforms to create, manage, and organize content for courses. This comprehensive 3-in-1 course guides you to work with repositories and e-portfolios and organize the content to gamify the course. Similarly, you'll gain interest in learning various other elements that can be added to a Moodle course in order to make it more attractive to students.By the end of the course, you will be able to make the most of Moodle for teaching purposes along with having your own portable repositories for collaborative work.Contents and OverviewThis training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Moodle for Beginners hows you how to create both activities and resources, creating them in a Moodle course and also using external tools. Well enhance our Moodle course by creating external websites, blogs, videos, and channels in order to create a dynamic course. Furthermore, youll learn to work with repositories and e-portfolios and organize the content to gamify the course. Youll learn how to deal with and organize information, edit, and share it.The second course, Moodle Recipes is one of the most popular open source platforms to create, manage, and organize content for courses. It starts giving recipes on how to enhance the Moodle course using different types of external elements and embed them in it. Later it goes on adding social condiments as well as the creation of groups within Moodle. Afterwards, the course shows how to interact online and live among students, teachers, and parents.The Third course, Mastering Moodle shows how to create graded activities and exams, personalize grade-books, provide feedback, and award students with the use of badges in several ways using different tools. These may be within the Moodle course or external tools specific to such purposes. The course also covers applying gamification to Moodle. There are plenty of items that can be used in order to gamify a Moodle course. There are simple steps to bear in mind when designing and then applying for a Moodle course. Students can get badges for specific goals within the course. There are plenty of other elements that can be added to a Moodle course in order to make it more attractive to students. Blocks are also explored and added according to the needs of the course. Gamified courses need gamification blocks as well as certain plugins.About the Authors:Silvina P. Hillar is Italian and has been teaching English since 1993. She has always had a great interest in teaching and has done a lot of research on teaching methodologies and management techniques, and embedding them into e-learning and teaching. She has also explored different types of e-learning combining them with Moodle.She also researches multimedia assets that enhance teaching and learning through VLE platforms. She tries to embed the learning of students through new resources that are appealing and innovative for them. In this way, she ensures that multimedia stimulates different thinking skills as well as multiple types of intelligence.She is an English teacher, a Certified Legal Translator (English/Spanish), and has a postgraduate degree in Education (graduated with honors).She has worked at several schools and institutions with native English speaking students and students of English as a foreign language, and as an independent consultant for many international companies in the capacity of an Interpreter, Translator, and Virtual Learning Environment (VLE) Course Designer.She has always had a passion for technological devices concerning education. Formerly, videos and cassettes were a must in her teaching lessons; the computer was, and still does, play a big role. Her brother, Gastn C. Hillar, designed some programs and games for her teaching. Lately, she has been teaching using Moodle and the Web. She believes that one of the most amazing challenges in education is bridging the gap between classic education and modern technologies.She has authored: Moodle 1.9: The English Teacher's Cookbook, Moodle 2.0 Multimedia Cookbook, Moodle 2.5 Multimedia Cookbook second edition, Mind Mapping with FreeMind, and Moodle 2.3 Multimedia Video Course.When not tinkering with computers, she enjoys traveling with her son, Nico and her love, Jorge, with whom she spends wonderful time."
Price: 199.99 |
| "Hands-on Scikit-learn for Machine Learning" |
| "Scikit-learn is arguably the most popular Python library for Machine Learning today. Thousands of Data Scientists and Machine Learning practitioners use it for day to day tasks throughout a Machine Learning projects life cycle. Due to its popularity and coverage of a wide variety of ML models and built-in utilities, jobs for Scikit-learn are in high demand, both in industry and academia.If youre an aspiring machine learning engineer ready to take real-world projects head-on, Hands-on Scikit-Learn for Machine Learning will walk you through the most commonly used models, libraries, and utilities offered by Scikit-learn.By the end of the course, you will have a set of ML problem-solving tools in the form of code modules and utility functions based on Scikit-learn in one place, instead of spread over several books and courses, which you can easily use on real-world projects and data sets.All the code and supporting files for this course are available on GithubAbout the AuthorFarhan Nazar Zaidi has 25 years' experience in software architecture, big data engineering, and hands-on software development in a variety of languages and technologies. He is skilled in architecting and designing networked, distributed software systems and data analytics applications, and in designing enterprise-grade software systems.Farhan holds an MS in Computer Science from University of Southern California, Los Angeles, USA and a BS in Electrical Engineering from University of Engineering, Lahore, Pakistan. He has worked for several Silicon-Valley companies in the past in the US as a Senior Software Engineer, and also held key positions in the software industry in Pakistan. Farhan works as consultant, solutions developer, and in-person trainer on big data engineering, microservices, advanced analytics, and Machine Learning."
Price: 124.99 |
| "Building Web Applications with TypeScript, Angular & React" |
| "TypeScript offers a sliding scale of how much or how little effort you want to put into your declarations: the more effort you put in, the more type safety and code intelligence you get. You will begin this course by learning the fundamentals of TypeScript and eventually move toward advanced concepts. You'll learn how TypeScript relates to JavaScript that you might have written before. You'll understand the benefits of TypeScript and how helps you to avoid software defects. We will learn to use type guards, check null and undefined, create tagged union types, and compare the performance of algorithms. You'll use TypeScript to build a weather forecast widget with Angular, and then build a note-taking client/server application using Angular, Node.js, and MongoDB. Finally, you will create a real-time chat application with React.About the AuthorsIvo Gabe de Wolff has been a freelance developer under the name of ivogabe since 2012 and is also studying mathematics and computing sciences at Utrecht University. When he was eleven, he started programming in GameMaker. Currently, he uses TypeScript on a daily basis. Recently, he has used TypeScript in lots of different environments, including mobile apps, servers, and command-line tools. Now, he mainly specializes in Node.js programming. Furthermore, he is the author of various open source projects, including gulp-typescript. If you want to read more about TypeScript, JavaScript, gulp, or functional programming.Gabriel Isenberg has over 15 years of experience in building web applications at scale. Currently, he is a principal development lead at GoDaddy, where he is delivering the next generation of user experiences utilizing React, React Native, and Node.js. Previously, he worked as a consultant, helping Fortune 500 companies convert large JavaScript codebases over to TypeScript. Additionally, he participates in the development of the JavaScript language standard via Ecma International Technical Committee 39. Sahil Malik, the founder and principal of Winsmarts .com, has been a Microsoft MVP and INETA Speaker for the past 8 years, author and reviewer of many books and numerous articles in both the .NET and SharePoint space, consultant and trainer who delivers training and talks at conferences internationally. Sahil has trained for the best names in the Microsoft technology space, and has architected and delivered SharePoint based solutions for extremely high profile clients."
Price: 199.99 |
| "Troubleshooting Linux Administration" |
| "Troubleshooting is an important skill used in many Information Technology (IT) roles including help desks, system administration, networking, and security. This course will help you learn practical and proven techniques to deal with many tasks you'll encounter when administering a Linux server.In this troubleshooting course, you will master the full power of the superuser; you'll use sudo to fix user management files and passwords, and schedule tasks with cron before troubleshooting.You will also troubleshoot and resolve wireless issues, identify machine issues with different troubleshooting processes, configure an SSH server for remote connections, and set up a Network File System to connect to your client.About the AuthorPaul Olushile graduated with a diploma degree in computer science and is currently working as a cybersecurity expert. He loves teaching and hence he has been freelancing for over 4 years to share his expertise as a Unix/Linux administrator with students. He has a diverse set of certifications, interests, and experiences, including server administration."
Price: 124.99 |
| "Java EE 8 Application Development" |
| "This course is the perfect guide to create a Java EE 8 application. You'll build a real-world chat application and will learn the best patterns and techniques in Java EE.You'll build a business model for a chat application with CDI and JSON. First, you'll create the skeleton of the business model. Moving on, youll learn to add features to the model such as user, message, and chat. Once youve set the model, you'll develop a connection between chat client and server using Websockets. Then, you'll create a REST API for other front-end JSclient applications. Finally, you'll develop a UI for the chat application by using the latest version of Java Server Faces JSF 2.3.By the end of the course, you'll be able to create a full-fledged web application using the new features of Java EE 8.About the AuthorTomasz Lelek is a Software Engineer who programs mostly in Java and Scala. He is a fan of microservice architectures and functional programming. He dedicates considerable time and effort to be better every day. Recently, he's been delving into big data technologies such as Apache Spark and Hadoop. He is passionate about nearly everything associated with software development.Tomasz thinks that we should always try to consider different solutions and approaches before solving a problem. Recently, he was a speaker at several conferences in Poland - Confitura and JDD (Java Developer's Day) and also at Krakow Scala User Group.He also conducted a live coding session at Geecon Conference. He is currently working on this website. Conducted workshops about Apache Kafka on the Geecon conference."
Price: 124.99 |
| "Serverless Architecture with AWS Lambda - A Complete Guide!" |
| "Serverless architecture is a way to build and run applications and services without having to manage infrastructure. Lambda eliminates the problem of dealing with cloud-based servers at all levels of technology stack, and offers a pay-per-request billing model where you don't have to pay for idle computing time. Thus it becomes extremely important to understand the serverless architecture, which will help you build, manage, and secure serverless applications with AWS Lambda.This comprehensive 3-in-1 course is all-inclusive guide will help you build Serverless applications and run Serverless workloads using the AWS Lambda service. Firstly, youll dive into the Serverless world of AWS Lambda and master its core components and how it works. Youll learn to build, deploy, manage, and secure serverless applications. Finally, youll master the serverless ecosystem with a variety of toolsets and AWS services.By the end of the course, youll dive into the exciting world of serverless architecture with AWS Lambda to build and manage secure serverless applications on AWS.Contents and OverviewThis training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Deep Dive into AWS Lambda, covers exploring and discovering the Serverless ecosystem with AWS services including DynamoDB. This video course starts with an introduction to the world of Serverless computing and its advantages and use cases, followed by a deep dive into AWS Lambda. Youll be introduced to the concepts of Serverless computing and will get to know about the benefits. Then well cover how to build and deploy an AWS Lambda function, and youll learn to integrate AWS Lambda with Simple Storage Service. Along the way, youll also discover how to design and deploy considerations for AWS Lambda.The second course, Design Serverless Architecture with AWS and AWS Lambda, covers diving into the exciting world of serverless architecture with AWS Lambda. This course starts with introduction to serverless architectures and then you'll delve into design considerations, followed by building a serverless application and deploying it on your serverless architecture. This video covers practical example of deploying and orchestrating a serverless application using DynamoDB, AWS Lambda, and API Gateway. Towards the end of the video, we will learn about some security considerations in protecting your serverless application. By the end of this course, you will have mastered working with serverless architectures on AWS Cloud.The third course, Hands-on Serverless Architecture with AWS Lambda, covers building cost-effective and highly scalable serverless applications using AWS Lambda. In this course, you'll learn to build code and deploy it without ever needing to configure or manage underlying servers. You'll build, secure, and manage serverless architectures that can power the most demanding web and mobile apps. You won't have to provision infrastructures or worry about scale. By the end of this course, you will know how to design and implement production-ready AWS serverless solutions. You'll be able to architect and build your own serverless applications on AWS.By the end of the course, youll dive into the exciting world of serverless architecture with AWS Lambda to build and manage secure serverless applications on AWS.About the AuthorsAlan Rodrigues has been working on software components such as Docker containers and Kubernetes for the last 2 years. He has extensive experience working on the AWS Platform, currently being certified as an AWS Solution Architect Associate, a SysOps Administrator, and a Developer Associate. He has seen that organizations are moving towards using containers as part of their Microservices architecture. And there is a strong need to have a container orchestration tool in place. Kubernetes is by far the most popular container orchestration on the market.Michael Haberman (MCT, MCPD, AWS solution architect, and GDG organizer) is a senior consultant and lecturer. He is a full-stack expert, specializing in web technologies such as JavaScript, HTML and CSS; he loves Node .js and AWS."
Price: 199.99 |
| "Hands-on Serverless Architecture with AWS Lambda" |
| "Serverless architecture is a way to build and run applications and services without having to manage infrastructure. Lambda eliminates the problem of dealing with cloud-based servers at all levels of technology stack, and offers a pay-per-request billing model where you don't have to pay for idle computing time. Thus it becomes extremely important to understand the serverless architecture, which will help you build, manage, and secure serverless applications with AWS Lambda.In this course, you'll learn to build code and deploy it without ever needing to configure or manage underlying servers. You'll build, secure, and manage serverless architectures that can power the most demanding web and mobile apps. You won't have to provision infrastructures or worry about scale.By the end of this course, you will know how to design and implement production-ready AWS serverless solutions. You'll be able to architect and build your own serverless applications on AWS.About the AuthorAlan Rodrigues has been working on software components such as Docker containers and Kubernetes for the last 2 years. He has extensive experience working on the AWS Platform, currently being certified as an AWS Solution Architect Associate, a SysOps Administrator, and a Developer Associate.He has seen that organizations are moving towards using containers as part of their Microservices architecture. And there is a strong need to have a container orchestration tool in place. Kubernetes is by far the most popular container orchestration on the market."
Price: 124.99 |
| "Hands-On Web Penetration Testing with Kali Linux" |
| "Kali Linux contains a large number of penetration testing tools from various different niches in the security and forensics fields. Kali Linux offers a multitude of options to scan a single IP, port, or host (or a range of IPs, ports, and hosts) and discover vulnerabilities and security holes. The output and the information this provides can serve as a precursor to penetration testing efforts.Have you ever wondered how to test web applications security? This course will teach you about web application vulnerabilities and how to use Kali Linux tools to perform web penetration testing to professional standards. You will start with application security and learn about the process of web penetration testing. Then you'll create a test lab with Oracle VirtualBox and Kali Linux. Next, you'll learn about common vulnerabilities in web applications with practical examples, which will help you understand the process of penetration testing and the importance of security. Now you'll be introduced to different tools to assess and analyze web application vulnerabilities. In the end, you'll learn to secure web applications.By the end of the course, you'll be able to perform web penetration testing using Kali Linux.About the AuthorRassoul Ghaznavi Zadeh is an information security architect. He has worked with business to define frameworks, perform risk and gap analysis, and identify security controls and roadmaps. He also works with stakeholders to plan, organize, and manage the successful delivery of security strategies and projects as well as the stable operation of the organization's IT infrastructure security, integration, and optimization.His key skills are:Enterprise security architecture design and business alignmentRisk assessment, management, compliance, and auditingEvaluating and analyzing IT security technologies and solutionsIT security control effectiveness monitoring and measurementVulnerability assessment and penetration testing"
Price: 124.99 |
| "Binary Exploits with Python" |
| "A penetration tester who only knows how to use tools written by others is limited to old techniques. Learning to develop your own exploits will make you much more powerful. Python is the favorite choice for penetration testers because it combines simplicity and ease of use with advanced features.This video course starts with high-level code injection, the simplest sort of exploit. It then explains binary exploits that allow you to skip past unwanted code, such as the password or product key tests, and add Trojan code. You will perform the exploit development process: finding a vulnerability, analyzing a crash in a debugger, creating a crafted attack, and achieving remote code execution on Windows and Linux. You will use the gdb debugger to analyze Linux executables and Python code to exploit them. On Windows, you'll use the Immunity debugger and Python.About the AuthorSam Bowne has been teaching computer networking and security classes at City College San Francisco since 2000. He has given talks and hands-on trainings at DEFCON, HOPE, B-Sides SF, B-Sides LV, BayThreat, LayerOne, Toorcon, and many other schools and conferences. Credentials: PhD, CISSP, DEF CON Black-Badge Co-Winner"
Price: 124.99 |
| "Building Trading Algorithms with Python" |
| "This course is a great opportunity to get started with trading, reap the rewards, and take the markets by storm. Programmers who have a basic knowledge of trading in traditional assets and wish to develop their own trading bots will find that this course addresses their core concerns and shows how to go about designing and developing a trading bot.The course will enable you to get started with creating a traditional asset trading bot. It will arm you with all the necessary programming tools and techniques to develop a full-fledged trading bot that numerous investors/traders can utilize. It covers general features such as using a financial calculator to do conversions, simply by interacting with a bot. Your customers, using your trading, bot can look up recent trends to make informed predictions and see what others have been trading, and how much.About the AuthorHarish Garg, founder of BignumWorks Software LLP, is a data scientist and a lead software developer with 17 years' software industry experience. BignumWorks is an India-based software consultancy that provides consultancy services in software development and technical training. Harish has worked for McAfeeIntel for 11+ years. He is an expert in creating data visualizations using R, Python, and web-based visualization libraries.Mithun Lakshmanaswamy of BignumWorks Software LLP has been developing applications in Python for 9+ years. He has written enterprise-level distributed applications that are deployed on scores of servers and have the ability to support thousands of users simultaneously. Some of the applications he has developed are related to parsing millions of virus definitions, analyzing network packets from an enterprise setup, and so on. He is also quite proficient in teaching technical concepts and is quite involved with his current organizations training programmes. He has worked on multiple projects working with Python, AWS and so on, implementing the concepts of concurrent and distributed computing."
Price: 124.99 |
| "Hands-On Linux System Administration" |
| "Have you only come into brief contact with Linux before, but now you need to set up or maintain a Linux server? Then this course is for you.With this course you'll learn how to master any Linux machine. Control and master the administration of a Linux machine, whether a workstation or a server. You'll learn how to set up services, monitor the system, perform backups, and schedule common tasks.By the end of the course you will be ready to start your career as a Linux system administrator.About the AuthorJack-Benny Persson discovered Linux and the internet way back in 1997, and has since been obsessed by it. Linux and networking have been both his hobby, his field of study, and also his career. He runs a small business in Sweden where he does everything from consulting work to writing books, as long as it has to do with Linux, programming, networking, or electronics. He also has a keen interest in communication and is a HAM radio operator. He is truly a jack-of-all-trades when it comes to technology. One of his (many) dream professions is to become a teacher, though he really likes teaching technology."
Price: 124.99 |
| "Beginning Data Science with Python and Jupyter" |
| "Getting started with data science doesnt have to be an uphill battle. This step-by-step video course is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. Youll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world.We'll start with understanding the basics of Jupyter and its standard features. You'll be analyzing an example of a data analytics report. After analyzing a data analytics report, next step is to implement multiple classification algorithms. Well then show you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context. Finish up by learning to visualize these data interactively.About The AuthorsAlex Galea has been doing data analysis professionally since graduating with a master's in physics from the University of Guelph in Canada. He developed a keen interest in Python while researching quantum gases as part of his graduate studies. More recently, Alex has been doing web data analytics, where Python continues to play a large part in his work. He frequently blogs about work and personal projects, which are generally data-centric and usually involve Python and Jupyter Notebooks.Chris DallaVilla is the founder and CEO of VALID., an independent marketing consulting practice specializing in providing data-driven solutions that help chief marketing officers and their teams strengthen their planning and execution, and drive results. Chris has expertise in digital and social media marketing, as well as certifications in Agile, Google AdWords, and Google Analytics. He studied computer science at Harvard University, design technology at Massachusetts College of Art and Design, and advertising and marketing communications at the Questrom School of Business at Boston University."
Price: 199.99 |
| "Professional Azure SQL Database Administration" |
| "Azure SQL Database is the cloud version of SQL Server. It differs in terms of management, maintenance and administration. Its important to know how to administer SQL Database so that you can get the most out of the features that it provides. You will learn different management aspects of an Azure SQL Database, such as migration, backup and restoration, pricing, security, scalability, monitoring and performance optimization, high availability and disaster recovery. Youll start by understanding the architecture of the Azure SQL Database and its service tiers. Through a narrative of a DBA, who is migrating from a traditional on-premises system to Azure SQL Database, this course will explain the concepts by using different scenarios you might come across while working with Azure SQL Database. If you are interested in developing new or migrating existing applications with Azure SQL Database, then this course is for you. About the AuthorsGethyn Ellis has over eighteen years of experience wit SQL Server and for past ten years he has been working on Azure. He is Microsoft certified trainer. He also trains and is a consultant for SQL Server. Prior to this he has worked with Packt and written books on ""Getting Started SQL Server 2014 Administration"" and, ""Microsoft Azure laaS Essentials"".Ahmad Osama is an independent consultant for Microsoft data platform stack. He has provided consulting, training, content development and SQL support services to more than 120 SQL Server customers globally. An expert in SQL Server and related technologies, he frequently speaks at user group events and conferences. Over the last 9 years, he has worked on countless SQL Server projects, consulted, trained, and mentored more than 1000 IT professionals on SQL Server, delivered more than 50 workshops. Ahmad has been a Microsoft Most Valuable Professional (MVP) awardee for SQL Server from 2014 - 2016.Currently, he works for Pitney Bowes Pvt. Ltd. as a database engineer and is a Microsoft Data Platform rMVP. In his day to day job at Pitney Bowes, he works on developing and maintaining high performance on-premise and cloud SQL Server OLTP environments, building CI/CD environments for databases and automation.Other than his day to day work, Ahmad has written over 100 blogs, including SQL Server Administration/Development, Azure SQL Database, and Azure Data Factory. He regularly speaks at user group events and webinars conducted by the Dataplatformlabs community."
Price: 199.99 |
