| "Illustrator Business Course - fast - for beginners" |
| "This course is for you that wants to start with illustrator and apply it to your business. We are going through a logo, business card, letterhead, and brochure.You will learn in no time and if there is anything you need more help with, then I will make a new video to explain.I want to help you, so you can save money and do the design for yourself.Good luck"
Price: 19.99 |
| "Crypto Explained Simply" |
| "Cryptocurrency and blockchain are explained in everyday terms that absolutely anyone can understand. Youll learn what crypto is, exactly how it works and why it has value. Mark Jeffreys unique, amiable and non-technical style will paint a vivid picture in your mind with metaphors and specific examples. Youll go on a tour of the major name crypto coins and learn whats special about each and the people behind them. Then youll learn exactly how to acquire and safely store your own crypto, with specific websites and wallets and exchanges. This course is at once a wide-ranging overview of crypto's legal, historical and technical background alongside hands-on, practical how-to information. Youll come away completely up to speed on the most important revolution in computing since the Internet itself."
Price: 19.99 |
| "Desarrollando Mobile/Web Apps con PowerBuilder + PowerServer" |
| "Dirigido a programadores PowerBuilder que deseen ampliar sus conocimientos para desarrollar aplicaciones Web y Mviles, sin necesidad de tener experiencia previa en desarrollo en tecnologas como HTML, JS, Angular o en dispositivos iOS o Android.Se mostrar la arquitectura, la instalacin y las herramientas para que el desarrollador pueda conocer cmo manejar el ciclo completo de creacin y despliegue de aplicaciones que sean de 3 capas y ejecuten sobre PowerServer."
Price: 34.99 |
| "Migrar lgica de negocio PowerBuilder a SnapObjects" |
| "Dirigido a programadores PowerBuilder que deseen ampliar sus conocimientos para desarrollar aplicaciones orientadas a Cloud.Se revisarn aspectos como refactoring de aplicaciones PB para consumir Web APIs, as como los pasos a seguir para reutilizar los DataWindows dentro de Web APIs basados en el patrn MVC, en Lenguaje C# y en la tecnologa .NET DataStore."
Price: 29.99 |
| "HTML5 - impariamo a creare siti web da ZERO!" |
| "Trasforma le tue idee in realt!Impara a realizzare fantastici siti web in completa autonomia, senza l'ausilio di fastidiosi tool esterni.Form, table e lists sono solo alcuni degli elementi che affronteremo durante il corso.Con HTML5 potrai approcciare al mondo dello sviluppo web, un mondo in continua crescita ed un mercato in continua espansione.Ti insegner i fondamenti di questo fantastico linguaggi di testo e le sue principali funzionalit."
Price: 19.99 |
| "Construo Virtual com REVIT (BIM 3D)" |
| "Nesse curso voc vai trabalhar com a modelagem de um projeto real de um edifcio de 3 pavimentos.A partir do arquivo dos arquivos de Estrutura e Arquitetura em AutoCAD, que voc receber, ir entender como modelar o edifcio conforme ele foi construdo.Voc vai dominar o processo construtivo e no apenas a simples modelagem.Vou te apresentar como representar corretamente os elementos 3D dos pacotes de trabalho dessa obra real.Mesmo que voc no tenha experincia com obras no tem problema, pois o passo a passo desse curso vai inclusive lhe ajudar a entender as etapas construtivas."
Price: 99.99 |
| "Planejamento BIM 4D com Navisworks - Estruturas de Concreto" |
| "Nesse curso voc vai trabalhar com o planejamento 4D de um projeto estrutural de 15 pavimentos.A partir dos arquivos de Estrutura e do Cronograma da Obra que voc receber, voc ir entender como fazer um planejamento da obra e simular a construo virtual conforme ela ser executada no canteiro de obras.Voc vai dominar o planejamento 4D e a execuo da estrutura de concreto e no apenas um simples cronograma.Vou te apresentar como elaborar de forma correta um planejamento 4D assertivo para uma obra de estruturas de concreto de grande porte .No curso voc aprender a criar um Planejamento BIM 4D de duas formas, a primeira somente com o Navisworks, aps essa etapa voc vai aprender a criar o Planejamento BIM4D importando um cronograma existente do MS-Project.Mesmo que voc no tenha experincia com obras no tem problema, pois o passo a passo desse curso vai inclusive lhe ajudar a entender as etapas construtivas."
Price: 99.99 |
| "Common Core Pre-Algebra: Parts 1-4" |
| "WELCOME TO COMMON CORE PRE-ALGEBRA: PARTS 1-4In this course, you will be able to find yourself understanding mathematics again! Topics include:-Number Sense-Basic Arithmetic-Integers-Fractions-Decimals-Order of Operations-And more!Tell all your friends about this course and have fun while learning! This is the best way to learn, at your own pace. In addition you will have access to google classroom worksheets, practice exams, and much more."
Price: 99.99 |
| "Crie aplicaes escalveis com Vue.js 2 + Firebase + Vuex" |
| "Aprenda a desenvolver sistemas escalveis com uma das melhores stacks (conjunto de frameworks) do mercado!Nesse curso voc aprender as seguintes coisas:Utilizar o vue.js,Servidor firebase,Vuetify,Quasar,Trello,Git,Bitbucket,Estrutura de um projeto,Desafios e maiores dvidas concernentes a um projeto grande,Precificar um projeto,Manusear um E-Commerce com gerao de boletos/carto de crdito,Gerar aplicativos a partir de um cdigo fonte web,Reviso html, css, javascript,Conceitos de trabalho em equipe e as tarefas principais de cada profissional.Conceitos simples de UX."
Price: 579.99 |
| "Create A Retro City Loop in Cinema 4D & After Effects" |
| "Learn how to make a stylish retro city loop animation in Cinema 4D and After Effects. You will also learn various techniques & tools that you can use for motion graphics projects in general such as:How to use the various tools in Cinema 4D to build a large city sceneThe concept of creating a seamless loopA retro lighting and rendering style in Cinema 4DOutput/render settings from Cinema 4D, how to use Multi Passes in Cinema 4DImporting the rendered sequence/s into After EffectsUsing After Effects for post effects and finishing touchesThe best export setting in Premier Pro for Instagram and Youtube.This class is suitable for users of all levels. Beginners who have not used the software before will be able to follow along. Intermediate to advanced users will be able to learn about or expand their knowledge of how to make looping scenes in Cinema 4D."
Price: 49.99 |
| "Gestin de Grupos de Facebook" |
| "Aprende cmo generar comunidad entre tus clientes y prospectos, y convirtete en su lder de un modo simple, probado y fcil de aprender.Sientes que no puedes hacer que los miembros de tu grupo participen e interacten como a ti te gustara? Tranquilo, no eres el nico a quien le pasa.En entrevista con varios emprendedores que intentan llevar adelante una comunidad y con administradores de grupos de Facebook surgieron de manera recurrente algunos de estos problemas:""La gente no responde como quiero a las publicaciones que subo a mi grupo""""Las fotos tienen muchos likes pero pocos comentarios de contenido.""""No tengo ni idea de por dnde empezar""Que te conozcan y recomienden es fundamental para tu negocio. Y los grupos de Facebook son el mejor canal a travs del cual lograr este objetivo. Aprender a manejarlos correctamente es imprescindible para la consolidacin de tu comunidad, y a partir de all de tu marca."
Price: 34.99 |
| "Estrategia segura,simple y efectiva para ganar con BITCOIN" |
| "METODOLOGA :en las clases te dejare tareas mayormente operaciones con pequeas cantidades de bitcoin (aproximado no menor a $11 )Ejemplos :-Trasferir bitcoin o retirar bitcoin-Hacer el cambio de bitcoin a su moneda local-Hacer el cambio de su moneda local a bitcoin -Aplicar mi estrategia de inversin con una fraccin de bitcoin-Ejercicio de almacenar de $10 a $100 de bitcoin en una billetera descentralizada AL TERMINAR EL CURSO PODRS HACER LO SIGUIENTE-Girar dinero entre personas a nivel mundial sin impuestos y con comisiones nulas o casi nulas.-Ahorrar dinero sin impuestos de forma privada sin terceros ni intermediarios.-Cambiar rpidamente de bitcoin a su moneda local (mucha liquides ) -Podr proteger su dinero y el de su familia en caso de inflacin.-Aprender a ganar dinero con la fluctuacin del precio.-Esconder dinero de forma annima -Lectura de grficas de trading-Estrategias probadas HERRAMIENTAS QUE APRENDERS A USAR -Mercado de bitcoin con alta liquides-Billeteras descentralizadas de bitcoin -Indicadores de trading"
Price: 24.99 |
| "Como lleve mi canal en Youtube de 0 a 120.000 suscriptores" |
| "Como lleve mi canal en Youtube de 10.000 a 120.000 suscriptores en un aoComo muchos de ustedes al principio me fue muy difcil hacer que mi mensaje llegara a las personas, pareca imposible conseguir mas seguidores, mi canal tenia varios aos estancado en la marca de los 10.000 seguidores lo cual era frustrante y muchas veces estuve a punto de tirar la toalla, de rendirme.Pero decid darle al canal y a mi mismo una nueva oportunidad, comenc a estudiar este arte desde la visin del mercadeo, buscando entender mejor esta plataforma y a mi espectadores y fue as como logre un cambio muy importante en el trafico de mi canal, me di cuenta que deba revisar no solo mis contenidos si no toda la estrategia en general.Pase de adquirir uno o dos suscriptores por semana a conseguir cientos cada da, aumente de manera importante el numero de visualizaciones y lo mas importante logre sostener y en algunos casos ver como las cifras aumentaban de manera constante y sostenida. Youtube no solo me ha permitido llegar a millones de personas, me ha permitido crear una empresa, Clasesdeguitarra com co la cual hoy tiene mas de 20.000 estudiantes activos, me he convertido en un best seller en Amazon donde he vendido millares de libros y he creado una App la cual tiene mas de 200.000 descargas, todo gracias a mi xito en esta plataforma.Segn mis clculos en unos tres aos debo estar llegando al milln de suscriptores, todo gracias a la estrategia que enseo en este curso y a la cual desde ahora puedes acceder, en ella te enseare:Cuales son los tres pilares indispensables del xito en Youtube.Como mejorar los contenidos buscando una mayor retencin de la audiencia. Como aumentar las visualizaciones.Como aumentar la base de suscriptores.Como explotar las herramientas que te ofrece la plataforma.Ser creador es algo que requiere mucho esfuerzo y disciplina, pero si eres constante La recompensa es grande!"
Price: 24.99 |
| "Teknik Dasar Editing Video menggunakan Adobe Premiere Pro CC" |
| "Buat kamu yang sedang tertarik dan baru memasuki dunia creative media tertutama dalam hal editing video, kamu berada ditempat yang tepat karena dalam kursus ini kamu akan mendapatkan banyak ilmu baru untuk pemula dalam hal editing video, tentunya dengan menggunakan Software editing Adobe Premiere Pro CC. Jadi, buat kamu, Yuk! ikuti kursusnya. Dalam kursus ini akan membahas semua hal dasar dalam editing video. Enjoy!"
Price: 280000.00 |
| "AutoCAD 3d Mimari Modelleme Kursu" |
| "Yaklak 15 yldr mimari projeler retmekte ve bunlarn 3 boyutlu sunumlarn hazrlamaktaym. Mimari sunum ilerinde 3 boyutlu modelleme nemli bir yer kaplamaktadr. Ben modelleme ilerimi AutoCAD de yaparak zaman kazanyorum. nk bana gre mimari model AutoCAD de ok pratik ve hzl hazrlanabilmektedir. Ayrca dier kullanacanz 3ds MAX, Lumion vb. programlar ile tam uyumlu almakta. Bu eitim seti ile sizde AutoCAD kullanarak istediiniz binann ve mimari elmann modellemesini rahatlkla yapabileceksiniz."
Price: 19.99 |
| "Microsoft Power BI Masterclass - A Complete Hands-on Guide" |
| "Data visualization is the standard way to communicate complex information into meaningful visuals that have a long-lasting impact. Gone are the days when data analysis was restricted to a spreadsheet and limited graphing capabilities. The current era of business intelligence has equipped business professionals with state-of-the-art analytical tools such as Power BI allowing them to visually see the state of the business and identify patterns to bolster successful strategies.Microsoft Power BI (business intelligence) is a powerful visualization and analytics tool that helps companies of all sizes analyze their data and share insights. With this technology, enterprises can monitor their business more closely and get instant answers with rich dashboards available for every device.The course Power BI for business professionals is designed for anyone who wants to create impactful visualizations and reports that utilize the underlying data and convey the message that has a long-lasting impact. The course is organized in small bitesize lectures in order to retain the attention of the student. The course begins by covering the core concepts of Power BI and data visualization. It then covers the specific visualization and their purposes. Many sections in the course contain practical activity files to help students test and apply their knowledge in a real scenario.Course Outline (Detailed)IntroductionIn this video instructors are introduced as well as how the course is organized is explained2.1Introduction to Power BIIn this video the instructor will narrate the Lesson 2 outlineLesson 2: Signing Up for Power BI and Loading Data2.2Downloading Power BI DesktopIn this video the instructor will narrate the basic steps and system requirements to download Power BI2.3Login into Power BI onlineIn this video the instructor will outline the procedure to Login into Power BI2.4Loading Data into Power BIIn this video the instructor will give a demo on how to load data in Power BI2.5Recap & ConclusionIn this video the instructor will recap and conclude Lesson 2Lesson 3: Power BI Tables3.1Introduction to Power BI TablesIn this video the guide will narrate the Lesson 3 outline3.2Creating your first table in Power BIIn this video the narrator will exhibit the course of actions taken to create a table in Power BI3.3Formatting and sorting TablesIn this video the instructor will narrate the ways to format and sort tables in Power BI3.4Using Multiple Measures in TablesIn this video the narrator will demonstrate the process to insert multiple measures in a single table3.5Cross Filtering TablesIn this video the guide will instruct on how to cross filter tables in Power BI3.6Practical Activity - TablesPractical Activity testing understanding of tables3.7Methods of AggregationIn this video the instructor will exhibit the techniques to compile information from databases in Power BI3.8Practical Activity - Methods of AggregationPractical Activity testing how information can be aggregated and presented in Power BI3.9Percentage CalculationsIn this video the narrator will illustrate the ways to calculate percentages of data in Power BI3.10Conclusion to Tables SectionIn this video the guide will recap and conclude Lesson 3Lesson 4:Matrix and Cards4.1Introduction to Matrix and CardsIn this video the instructor will narrate the Lesson 4 outline4.2Creating the Matrix VisualizationIn this video students will learn how matrix tables can be visualized on Power BI canvas4.3Methods of Aggregation for MatrixStudents will learn how information could be added to give an sum view of the data presented on a matrix table4.4Percentage of Calculations for the MatrixStudents will learn how numbers presented on a matrix table can be converted to percentages4.5Multi Row VisualizationKPI cards are good way to present numbers. In this video student will learn how to use KPIs to create multi row visualizations4.6Card VisualizationCard visualization covered in this video will demonstrate how to present and label a single KPI on the Power BI canvas4.7Practical Activity - Cards, Multi Row and MatrixPractical activity testing knowledge of Cards, Multi Row and Matrix4.8Conclusion to Matrix and Card VisualizationsTopic is summarized in this videoLesson 5: Filters and Slicers5.1Introduction to Filters and SlicersThe video introduces the important concept of filters and slices which when applied can create visualizations which are more specific to user needs5.2Text SlicersThis video demonstrates how slicers could be applied to text to filter information5.3Numeric SlicersThis video demonstrates how slicers could be applied to numbers to filter information5.4Date SlicersThis video covers how a date can be filtered by using date slicers5.5Visual Level Text FiltersThis video demonstrates how visuals could show customized information by applying visual level text filters5.6Visual Level Numeric FilterThe video is an extension to visual level filters demonstrating how numeric filters can be applied to a visual5.7Visual Level Date FiltersThe video is an extension to visual level filters demonstrating how datefilters can be applied to a visual5.8Page and Report Level FiltersThe video is an extension to visual level filters demonstrating how datefilters can be applied to a visual5.9Practical Activity - FiltersPractical activity testing knowledge of filters5.10Conclusion to Filters and SlicersChapter round up of lesson 5Lesson 6:Column Visualizations6.1Introduction to Column VisualizationsColumn visualization are introduced and expectations of videos coming in lesson is set6.2Column VisualizationsHow to make a basic column visualization is covered6.3Stacked Column VisualizationsStacked column visualization is covered. Students learn what is the difference between the 2 types of column visualization and when to use them6.4Cross Filtering and SlicersHow to set cross filters to slicers to add more interactivity to visualizations6.5Practical Activity - Column and Bar VisualizationsPractical Activity testing knowledge of Column and Bar Visualizations6.6Graph OptionsDifferent types of graph visualizations available in Power BI6.7Analytics PaneHow the analytics pane can add dynamic reference lines to visuals, and provide focus for important trends or insights6.8Practical Activity - Graph OptionsPractical Activity testing understanding of Graph Options in Power BI6.9Conclusion to the Column Visualizations SectionLesson round-up video summarizing what is taughtLesson 7:Trend Analysis7.1Introduction to Trend AnalysisHow trend analysis can enrich the current visualization in power bi7.2Line GraphsLearn how to add line graphs in power BI7.3Area GraphsHow lines can be converted to area charts7.4Ribbon GraphsHow to make ribbon graphs in power bi7.5Practical Activity - Trend AnalysisPractical Activity testing understanding of Trend analysis in Power BI7.6Conclusion to Trend Analysis SectionLesson round up video summarizing what is taughtLesson 8 :Other Graph Types8.1Introduction to Other Graph TypesIntroduction to other types of charts used in Power BI8.2Waterfall and KPI VisualizationsHow waterfall and KPI charts could help us create a visualization8.3Combination GraphsIn this video combination charts are explained in Power BI. How they can be helpful in conveying greater detail in the same visualization8.4Pie GraphsHow pie charts are made in power bi are explained in this video8.5Tree map GraphsHow tree map visualization is created in power bi is explained in this video8.6Geographical GraphsHow information such as name of cities and countries can help present companies information on a map8.7Scatterplots and Bubble plotsOther charts such as Scatterplots and Bubble plots are explained in this video8.8Practical Activity - ScatterplotsPractical Activity Scatterplots test students understanding from previous videos8.9Practical Activity Scatterplots TutorialThis video contains answers to the practical activity conducted8.10Conclusion to Other GraphsChapter Roundup summarizing the concepts learned in previous videosLesson 9: Interactive Dashboards9.1Introduction to Interactive Reports/DashboardsIn this lesson we cover the objectives of how the previously acquired knowledge could be used to create interactive reports in power bi9.2DIY Worldwide LLCA scenario of a fictitious company Worldwide LLC where information could be used to create a report9.3Drill Through FiltersIn this video concept of how a visual can provide a more focused information using drill though filters9.4Advanced ToolTipsAdvance tool tips help to create a custom information to be shown as a tool tip of a visualization9.5BookmarksHow information or a visual could be bookmarked to create a story line effect in Power BI9.6Publishing reportsHow reports in desktop could be published to power BI online9.7Conclusion to Interactive DashboardsChapter roundup summarizing the core concepts learnedLesson 10 : Power BI Service10.1Introduction to Power BI ServicePower BI online service is introduced in this lesson10.2Setting Up DashboardsHow different visuals from multiple reports could be combined in the form a dashboard in power bi10.3Dashboards V ReportsMajor differences between dashboard and report is identified10.4Set up Alerts and SubscriptionsHow can we setup alerts for a visuals or subscriptions for updates on data models is created in Power BI10.5Getting Insight from your DataHow the analytics engine of power BI can generate insights in Power BI online10.6Setting up the Mobile ViewThe video aims to discuss how reports and dashboards are best optimized for mobile views10.7Natural Language QueriesThe NLP is a brand-new feature of Power BI which helps us ask questions from the data source by typing English sentences.10.8Practical Activity - Natural LanguagePractical Activity - Natural Language testing understanding of10.9Conclusion to the Power BI ServiceConclusion video summarizing what is covered in previous videos of the lessonLesson 11:Power BI Security, Workspaces and Refresh11.1Introduction to Power BI Security, Workspaces and RefreshIn this video the security features and data refresh options of power bi are introduced11.2Data GatewaysIn this video the instructor explained how data gateway can help sync data that is lying on local machine to power BI online11.3Row Level SecurityHow information could be kept secure by restricting access applied on certain rows of data in Power BI11.4Creating workspaces in Power BIHow workspaces are created in Power BI online to share and collaborate with others11.5Publishing AppsHow publishing apps can help broadcast our reports and dashboard and share with entire organization.11.6Conclusion to Power BI Security, Workspaces and RefreshConclusion video summarizing what is covered in previous videos of the lessonLesson 12:Power BI and Excel12.1Introduction to Power BI and ExcelLesson introductory video highlighting how power BI reports could be further analyzed in excel12.2Power BI and Excel Pivot TablesHow Power BI reports could be exported and analyzed in excel pivot tables12.3Pinning Excel RangesHow reports analyzed in excel could be pinned to Power BI12.4Excel Online WorkbooksHow source file could be analyzed in online excel12.5Conclusion to Power BI and ExcelConclusion video summarizing what is covered in previous videos of the lessonLesson 13:Custom Visualizations13.1Introduction to Custom VisualizationsHow visuals can be made more customized are introduces in this video13.2Custom VisualizationsDifferent types of customization option available in Power BI are discussed in this video13.3ThemesHow different themes could be added to a report in Power BI13.4Conclusion to Custom VisualizationsConclusion video summarizing what is covered in previous videos of the lessonLesson 14:Publish and Embed Dashboards14.1Introduction to Publish and EmbedHow reports could be published or embedded to other platforms such as power point14.2Publish and Embed DashboardsHow dashboards could be published or embedded to other platforms such as power point14.3Power BI Usage ReportsHow activity of work done in Power BI could be monitored such as how many times a report is viewed.14.4Conclusion to Publish and Embed DashboardsConclusion video summarizing what is covered in previous videos of the lessonLesson 15: Course Conclusion15.1Course ConclusionIn this video a brief summary of each Lesson is given to give a small recap to students."
Price: 19.99 |
| "Oracle Weblogic 12c for Administrators: A Complete Guide" |
| "Oracle WebLogic Server is a scalable, enterprise-ready Java Platform, Enterprise Edition (Java EE) application server.The WebLogic Server infrastructure supports the deployment of many types of distributed applications and is an ideal foundation for building applications based on Service-Oriented Architectures (SOA).SOA is a design methodology aimed at maximizing the reuse of application servicesThe WebLogic Server complete implementation of the Java EE 5.0 specification provides a standard set of APIs for creating distributed Java applications that can access a wide variety of services, such as databases, messaging services, and connections to external enterprise systems.End-user clients access these applications using Web browser clients or Java clients. It also supports the Spring Framework, a programming model for Java applications which provides an alternative to aspects of the Java EE modelWebLogic Server clusters provide scalability and reliability for your applications by distributing the workload among multiple instances of WebLogic Server. Incoming requests can be routed to a WebLogic Server instance in the cluster based on the volume of work being processed. In case of hardware or other failures, the session state is available to other cluster nodes that can resume the work of the failed node.Work Managers prioritize work based on rules you define and by monitoring actual run time performance statistics. This information is then used to optimize the performance of your application.WebLogic Server persistent store is a built-in, high-performance storage solution for WebLogic Server subsystems and services that require persistence. For example, it can store persistent JMS messages or temporarily store messages sent using the Store-and-Forward feature. The persistent store supports persistence to a file-based store or to a JDBC-enabled database.Enterprise-ready deployment tools facilitate deployment and migration of applications from the development phase to a production environment.Production redeployment enables enterprises to deploy a new version of their application without interrupting work in progress on the older version."
Price: 19.99 |
| "AWS Certified Developer Associate (2019)- A Complete Guide" |
| "Amazon Web Services - (AWS) Certification is a growing and essential certification for any IT professional or developer working with AWS. This course is designed to help you pass the AWS Certified Developer Associate 2019 Exam. Even if you have no prior knowledge of the AWS platform before, by the end of this AWS course you will be able to take the exam. No specific programming knowledge is needed although knowing at least one programming language would be advantageous and no prior AWS experience required. With AWS certification, you will have an advantage over other developers in the industry and will have the upper hand in any cloud or development related job.Please note, this is not a course to teach you how to code, this course is specifically designed on helping you to pass the AWS Certified Developer exam.AWS are constantly evolving their platform, This course will help you find the study material also and will guide you to keep up to date with the exam and AWS services as well.All lectures are 5 - 15 minutes long. The Hands-on Labs are designed in such a way to guide you through each step and help you understand all the possibilities and overcome all the hurdles in deploying applications and migrating your local services to AWS platform"
Price: 19.99 |
| "Data Science and Machine Learning Bootcamp with Python & R" |
| "This course teaches big ideas in machine learning like how to build and evaluate predictive models. This course provides an intro to clustering in R from a machine learning perspective.This online machine learning course is perfect for those who have a solid basis in R and statistics but are complete beginners with machine learning. Youll get your first intro to machine learning.After learning the true fundamentals of machine learning, you'll experiment with the techniques that are explained in more detail. By the end, you'll be able to learn and build a decision tree and to classify unseen observations with k-Nearest Neighbors.Also, you'll be acquainted with simple linear regression, multi-linear regression, and k-Nearest Neighbors regression.This course teaches the big ideas in machine learning: how to build and evaluate predictive models, how to tune them for optimal performance, how to preprocess data for better results, and much more.At the end of this course, our machine learning and data science video tutorials, youll have a great understanding of all the main principles.Details of the course:Module 01: Basics of R toolIn this video, we are going to install r programming with rstudio in Windows Platform.Lab 01 R Installation and ConceptsIn this lab, we are going to learn about how we can install R Programing in Windows and learn about its several key concepts which are necessary for Programming in R.Video 2_R Progrming ConceptsIn this video, we are going to learn the necessary concepts of RProgramming.Video 3_R Progrming ComputationsIn this tutorial, we will be learning about several mathematical algorithms and computations.Lab 02 R Programing ComputationsIn this lab, we are going to understand RData Structures that includes - vectors, matrices, arrays, data frames (similar to tables in a relational database) and lists in R Programing Computations.Video 4_R Data StructuresIn this video, we will discuss R data structures that resemble a table, in which each column contains values of one variable and each row contains one set of values from each column.Module 02: Basic Data VisualizationIn this video, we will be understanding circular statistical graphics, which is divided into slices to illustrate numerical proportions in a pie chart.Lab 03 Plotting Pie Chart using R ToolIn this practical demonstration, you will learn how we can plot a pie chart. Also, well learn the representation of values as slices of a circle with different colors in the pie chart using the R tool.Video_6 Bar ChartsIn this video, we will learn the categorical data with rectangular bars with heights or lengths proportional to the values that they represent in the bar chart.Lab 04 Plotting Bar Chart using R ToolIn this lab, we are going to learn how we can plot a bar chart that represents data in rectangular bars with a length of the bar that is proportional to the value of the variable using the R tool.Video_7 Box PlotIn this video, we learn about how we can display the distribution of data in a standardized way in Boxplot.Lab 05 Making Box Plot using R ToolIn this lab, we will discuss how we can make a box plot which is a measure of how well the data is distributed in a data set and it divides the data set into three quartiles using the R tool.Video_8 HistogramsIn this video, we are going to learn about the histograms which are the graphs of a distribution of data that is designed to show centering, dispersion (spread), and shape (relative frequency) of the data by using its different functions.Lab 06 Working on Histograms using R ToolIn this lab, well be working on histograms that represent the frequencies of values of a variable bucketed into ranges where each bar in histogram represents the height of the number of values present in that ranger creates a histogram using hist() function.Video_9 Line ChartsIn this video, we are going to learn about the line charts which are also known as Line graph that is used to visualize the value of something over time.Lab 07 Plotting Line Chart using R ToolIn this lab, we will learn how we can plot a line chart which is a graph that connects a series of points by drawing line segments between them and then these points are ordered in one of their coordinates (usually the x-coordinate) value.Video_10 Scatter PlotIn this video, we are going to learn about a set of points plotted on a horizontal and vertical axis which is important in statistics because they can show the extent of correlation, if any, between the values of observed quantities or phenomena (called variables) in Scatter plot.Lab 08 Working on Scatterplot using R ToolIn this lab, we will be working on Scatterplot which shows many points plotted in the Cartesian plane at where each point represents the values of two variables. In this one variable is chosen in the horizontal axis and another in the vertical axis. The simple scatterplot can be created using the plot() function.Video_11 Case Study Basic Data VisualizationIn this video, we will explore some interesting case studies on basic data visualizations which is useful for getting a basic understanding of what characteristics is happened in different cases of data visualization with its constituent approaches.Module 03: Advanced Data VisualizationVideo_12 Basic Illustration of ggplot2 PackageIn this video, we will learn about the ggplot2 package which is a system for declaratively creating graphics, based on The Grammar of Graphics at where we provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.Lab 09 Basic Illustration of ggplot2 PackageIn this lab, we are going to perform a basic illustration on the ggplot2 package which includes a popular collection of packages called the tidyverse at where each geom accepts a particular set of mappings using the R tool.Video_13 FacetingIn this video, we are going to learn about faceting. How we can facet our data with facets by which you can gain an additional way to map the variables.Lab 10 Facetting using R ToolIn this lab, well be learning about how we can perform faceting by facet the data which creates a matrix of panels defined by row and column faceting variables. facet_wrap() , which wraps a 1d sequence of panels into 2d.Video_14 Jitterred PlotsIn this video, we are going to learn about Jittering which means adding random noise to a vector of numeric values, which is done in jitter-function by drawing samples from the uniform distribution in jittered plots.Lab 11 Working on Jiterred Plots using R ToolIn this lab, well be working on jittered plots where we jitter the data and makes the data easy to understand which uses points to graph the values of different variables.Video_15 Frequency PolygonsIn this video, we will learn how we can represent our data in a graphical form in Frequency Polygon which is used to depict the shape of the data and to depict trends and usually drawn with the help of a histogram but can also be drawn without it as well.Lab 12 Making Frequency Ploygons with Histograms using R ToolIn this lab, we will be discussing how we can make frequency Polygons with histograms that represent the frequencies of values of a variable bucketed into ranges.Video_16 Time SeriesIn this video we are going to learn about time series of data points indexed (or listed or graphed) in time order.Lab 13 Working on TimeSeries using R ToolIn this lab, we will be working on time series where the statistical algorithms will work and a record will maintain time by time for a particular period of time.Lab 14 Creating Surface Plots using R ToolIn this lab we will discuss on how we can create multi-dimensional surface plot, which is a three-dimensional surface that has solid edge colors and solid face colors the function plots the values in matrix Z as heights above a grid in the x-y plane defined by X and Y and the color of the surface varies according to the heights specified by Z.Lab 15 Working on Revealing Uncertainty using R ToolIn this lab, we will work on revealing uncertainty in data that occurs in domains ranging from natural science to medicine to computer science at their participants described what uncertainty looks like in their data and how they deal with it.Lab 16 Understanding Weighted DataIn this lab, we will be understanding the weighted data which is used to adjust the results of a study to bring them more in line with what is known about a population.Lab 17 Drawing Maps and highlighting Vector BoundariesIn this lab, we will learn how we can draw maps and highlights the vector boundaries which besides the actual map with various elements step by step and draw a nice realistic vector map drawing.Lab 18 Working on Diamonds Data SetIn this lab, we will be working on diamonds data set at where we learn how we can import dataset libraries and understand the linear relationship between two variables which contains different attributes.Lab 19 Dealing with OverlappingIn this lab we are going to learn about how we can deal with overlapping if we have two pieces of something, and one is covering a part of another, then they're overlap in it.Lab 20 Working on Statistical SummariesIn this lab we will be working on statistical summaries which summarize and provide information about our sample data which tells us something about the values in our data set that includes the average lies and whether our data is skewed.Module 04: Leaflet MapsVideo 17_Implementing Leaflet with RIn this video, we will learn about how we can implement leaflet in R by using its open-source JavaScript libraries for interactive maps.Lab 21 Implementing Leaflet with R toolIn this lab, we will understand how we can implement Leaflet which is a popular open-source JavaScript library for the interactive maps using the R tool.Video 18_Using Basemaps and Adding Markers in MapIn this video we are going to learn about the basemaps in R and understand how we can add markers in a map.Lab 22 Adding Markers in a MapThis lab will learn how we can add markers in a map where the map includes a marker, also called a pin, to indicate a specific location.Video 19_Popus and LabelsIn this video, we are going to learn how we can attach textual or HTML content that displayed on mouse hover using popups and labels where popups don't need to click a marker/polygon for the label to be shown.Lab 23 Working with Popups and LabelsIn this lab we will be working on Popups and labels which are small boxes containing arbitrary HTML, that point to a specific point on the map we use the addPopups() function to add standalone popup and addLabel() function to add a little label to the map.Video 20_Shiny Framework using Leaflet and RIn this video we are going to understand about a web shiny framework and Leaflet at where we assign a render leaflet call to the output inside the render leaflet expression where you return a leaflet map object.Lab 24 Shiny Framework using Leaflet and RIn this lab, we will make a shiny framework using leaflet and R as where in the UI you call leafletOutput, and on the server side you assign a renderLeaflet call to the output. Inside the renderLeaflet expression, you return a Leaflet map object and the web framework is completed.Module 05: StatisticsVideo 21_Linear RegressionIn this video you will learn about the linear approach to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables) in Linear Regression.Lab 25 Working with Linear RegressionIn this lab we will work on Linear regression where we will find a line that best fits the data points available on the plot, so that we can use it to predict output values for inputs that are not present in the data set we have, with the belief that those outputs would fall on the line.Video 22_Multiple RegressionIn this video, we are going to understand an extension of simple linear regression, which is used when we want to predict the value of a variable based on the value of two or more other variables in multiple regression.Lab 26 Working with Multiple RegressionIn this lab we will perform multiple regression which is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.Video 23_Logistic RegressionIn this video we are going to learn about Logistic regression which is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome.Lab 27 Performing Logistic RegressionIn this lab, we will be performing Logistic Regression which is used to describe data and to explain the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables.Video 24_Normal DistributionIn this video, we will learn about an arrangement of a data set in which most values cluster in the middle of the range and the rest taper off symmetrically toward either extreme in Normal Distribution.Lab 28 Working with Normal DistributionIn this lab well be working on normal distribution which is a probability function that describes how the values of a variable are distributed it is asymmetric distribution where most of the observations cluster around the central peak and the probabilities for values further away from the mean taper off equally in both directions.Video 25_Binomial DistributionIn this video, well be discussing about the binomial distribution which is a specific probability distribution that is used to model the probability of obtaining one of two outcomes, a certain number of times (k), out of fixed number of trials (N) of a discrete random event.Lab 29 Performing Binomial DistributionIn this lab, well be performing binomial distribution which consists of the probabilities of each of the possible numbers of successes on N trials for independent events that each have a probability of of occurring.Video 26_Poission RegressionIn this video we are going to learn about Poisson regression which is used to model response variables (Y-values) that are counts and tells you which explanatory variables have a statistically significant effect on the response variable.Lab 30 Working with Poisson RegressionIn this lab we will be working on Poisson regression which is used to model response variables (Y-values) that are counts and also tells you which explanatory variables have a statistically significant effect on the response variable.Video 27_Analysis of CovarianceIn this video we will learn about Analysis of covariance (ANCOVA) which allows to compare one variable in two or more groups taking into account (or to correct for) variability of other variables that are also called covariates.Lab 31 Analysis of CovarianceIn this lab we will understand the analysis of covariance which is used to test the main and interaction effects of categorical variables on a continuous dependent variable, controlling for the effects of selected other continuous variables, which co-vary with the dependent.Video 28_Time Series AnalysisIn this video we are going to learn about the sequence of well-defined data points measured at consistent time intervals over a period of time in time series analysis.Lab 32 Time Series AnalysisIn this lab we will be performing time series analysis which is a sequence of well-defined data points measured at consistent time intervals over a period of time and also use of statistical methods to analyze time-series data and extract meaningful statistics and characteristics about the data.Video 29_Decision treeIn this video we are going to learn about the graph that uses a branching method to illustrate every possible outcome of a decision in Decision tree.Lab 33 Working with Decision TreeIn this lab we are going to work on the decision tree which is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility.Lab 34 Implementation of Decision Tree in DatasetIn this lab, we will learn how we can implement a decision tree by splitting the training set of the dataset into subsets while making the subset we have to take care that each subset of training dataset should have the same value for an attribute.Lab 35 Working with Nonlinear Least SquareIn this lab we will be working on non-linear least-square which is the form of least squares analysis used to fit a set of m observations with a model that is non-linear in n unknown parameters (m n) and refine the parameters by successive iterations.Video 30_Survival AnalysisIn this video we are going to understand about the set of methods for analyzing data where the outcome variable is the time until the occurrence of an event of interest while performing Survival Analysis.Lab 36 Working with Survival AnalysisIn this lab we will be working on survival analysis is generally defined as a set of methods for analyzing data where the outcome variable is the time until the occurrence of an event of interest.Module 06: Data ManipulationVideo 31_Data Mungigng and VisualizationIn this video we will learn about data munging and visualization at where we transform and map data from one ""raw"" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics.Video 32_Hearchical ClusteringIn this video we will understand an algorithm that groups similar objects into groups called clusters while learning Hierarchical Clustering.Lab 37 Working with Hierarchical ClusteringIn this lab we are working on hierarchical clustering which typically works by sequentially merging similar clusters, it can also be done by initially grouping all the observations into one cluster, and then successively splitting these clusters.Video 33_K-means ClusteringIn this video we are going to learn the clustering which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster in k-means clustering.Lab 38 K means ClusteringIn this lab well be performing K means clustering which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster.Module 07: H2O PackageVideo 34_Supervised and Unsupervised LearningIn this video, we are going to understand how we can train the machine using data which is well labeled and where you do not need to supervise the model while learning Supervised and unsupervised learning.Lab 39 Working with Supervised and Unsupervised LearningIn this lab we are working on Supervised and unsupervised learning which is a machine learning technique, where you do not need to supervise the model it allows you to collect data or produce a data output from the previous experience.Video 35_Regression with H2OIn this video we will learn the scalable open-source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models, Gradient Boosting Machines etc. in regression with H2O.Lab 40 Installation of H2O PackageIn this lab, we will learn about how we can install H2O package in R which has several distributions containing almost all the data science packages.Module 08: TensorFlow PackageLab 41 Performing Regression with TensorFlowIn this lab, we are going to perform regression with TensorFlow which aims to predict the output of a continuous value and provide the model with a description.Module 09: First Machine LearningVideo 36_Machine Learning with Dataset and Iris Dataset ImplementationIn this video, we are going to learn the use of Multiple Measurements in Taxonomic Problems with 50 samples each as well as some properties about each flower in Machine learning with dataset and iris dataset implementation.Lab 42 Machine Learning with DatasetIn this lab, we will learn machine learning with a dataset that contains a handful number of great datasets that can be used to build computer vision (CV) models.Video 37_Evaluation of Algorithms with Model and Selecting Best ModelIn this video, we are going to learn about the algorithm over a training dataset with different hyperparameter settings that will result in different models at where we selecting the best-performing model from the set in evaluating of algorithms with model and selecting the best model.Lab 43 Evaluation of Algorithms with ModelsIn this lab, we are going to perform evaluation of algorithms with models which is an integral part of the model development process and it also helps to find the best model algorithms that need a validation set.Module 10: Artificial Neural NetworksVideo 38_Demonstration of sample Neural NetworkIn this video, we will learn that how we can demonstrate a neural network by taking a sample in this at where discuss its different features.Video 39_Prediction Analysis of Neural Network and Cross-Validation Box PlotIn this video, we will understand how we can perform prediction analysis of neural networks and learn how we can cross-validate our data while using boxplot by discussing both.Module 11: Cluster GenerationVideo 40_ClusteringIn this video well be discussing about clustering which is a task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters).Video 41_Cluster Generation Output AnalysisIn this video, we are going to learn all about cluster generation at where we understand that how we can perform a specific task and gets a specific output in cluster generation output analysis.Module 12: Decision TreesLab 44 Plotting a Decision TreeIn this lab we are going to plot a decision tree which is basically a binary tree flowchart where each node splits a group of observations according to some feature variable.Module 13: Text MiningVideo 42_ Text MiningIn this video we are going to understand the process of exploring and analyzing large amounts of unstructured text data aided by software that can identify concepts, patterns, topics, keywords and other attributes in the data in text mining.Lab 45 Text Mining with RIn this lab, we will be performing text mining with R which contains each document or set of text, along with some meta attributes that help describe that document.Module 14: Beginning the Data Science JourneyVideo 43_Data ScienceIn this video, we will be discussing the data science which is the study of where information comes from, what it represents and how it can be turned into a valuable resource in the creation of business and IT strategies.Video 44_Why is Data Science so important?In this video we will learn the different methods in data science and understand how the data would be represented in better form and why it is so important.Video 45_Python Data Science EcosystemIn this video, we are going to learn the whole ecosystem of python at where we understand how we can load the libraries in order to perform data science tasks in Python.Module 15: Introducing JupyterVideo 46_Basics of JupyterIn this video, we are going to understand the main components like the kernels and the dashboard where it has the kernel for python code in Jupyter basics.Lab 46 Installing AnacondaIn this lab, we are going to learn about how we can install Anaconda in windows as per your system requirements.Lab 47 Starting with jupyterIn this lab, we are going to learn about how we can use Jupyter which allows you to start more than just Notebooks at where you can also create a text file, a folder, or a Terminal in your browser.Lab 48 Basics of jupyterIn this lab, we are going to learn the basics of Jupyter which are necessary to understand while you are giving several commands in Jupyter.Video 47_Markdown SyntaxIn this video we are going to learn about the format for writing for the web in Jupyter while using the Markdown syntax function.Lab 49 Working with Markdown SyntaxIn this lab, we will be working on markdown syntax which is to be used as a format for writing for the web.Module 16: Understanding Numerical Operations with NumPyVideo 48_1D Arrays with NumPyIn this video, we will be discussing the NumPy at where we learn about the 1-dimension array and understand its different features and know about different libraries and tools like Pandas in 1D arrays with NumPy.Lab 50 1D arrays with numpyIn this lab, we will learn how we can create a 1-dimensional array with NumPy at where you can get the particular array object which discovers vectors, matrices, tensors, matrix types, matrix factorization, etc.Video 49_2D Arrays with NumPyIn this video, we are going to learn about how the 2-dimensional arrays work by importing different libraries and tools in 2D Arrays with NumPy.Lab 51 2D Arrays with NumPyIn this lab, we will learn how we can create a 2-dimensional array with NumPy at where you can get an array object which discovers several dimensions that have a container of items of the same type and size.Video 50_Functions in NumPyIn this video, we will understand different functions of NumPy which contains a large number of various mathematical operations and provides standard trigonometric functions, functions for arithmetic operations, handling complex numbers, etc.Lab 52 Functions in NumPyIn this lab we are going to perform different functions of NumPy which contains a large number of various mathematical operations and also provides a standard trigonometric function, functions for arithmetic operations, handling complex numbers, etc.Video 51_Random Numbers and Distributions in NumPyIn this video, we will learn the different random numbers like its dftype , np . int etc in NumPy and understand how we can demonstrate it using several distributions in NumPy.Lab 53 Random Numbers and Distributions in NumPyIn this lab, we will learn about the random numbers which return an array of specified shape and fills it with random integers and the several distributions with NumPy while using Jupyter.Module 17: Data Preparation and Manipulation with PandasVideo 52_Pandas PackageIn this video we are going to understand the pandaspackage which is an open-source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.Video 53_Read in Data Files &Subsetting DataFramesIn this video we will understand how we can read a CSV file into a pandas' DataFrame and how we can subset data frame using subset function which let us subset the data frame by observations.Lab 54 Subsetting DataFramesIn this lab, we will learn how we can subset our data for the selection of data frame elements that look something like the df[ ] df. loc[ ].Video 54_Boolean Indexing in DataFramesIn this video we are going to learn all about Boolean Indexing in DataFrames at where we have to give each row of the DataFrame (or value of a Series) will have a True or False value associated with it depending on whether or not it meets the criterion.Lab 55 Boolean Indexing in DataFramesIn this lab we will learn how we can perform Boolean indexing in each row of the DataFrame (or value of a Series) that have a True or False value associated with it, depending on whether or not it meets the criterion.Video 55_Summarizing and Grouping DataIn this video, we will discuss aggregating functions that sometimes the user needs to view the summary of the data and learn how we can group data by columns or rows you select, which helps you better to understand your data.Lab 56 Summarizing and Grouping DataIn this lab, we are going to learn how we can summarize and group our data which contains aggregated values useful for analyzing the data and provides aggregate functions to generate the summarized and grouped data.Module 18: Visualizing Data with Matplotlib and SeabornLab 57 Graphs with MatplotlibIn this lab, we will understand the graphs with matplotlib which is a collection of command style functions that make matplotlib that will introduce you to graphing in python with Matplotlib.Module 19: Introduction to Machine Learning and Scikit-learnVideo 56_Types of Machine LearningIn this video we will learn the semi-automated extraction of knowledge from data and understand the different sub-categorized types of machine learning methods.Video 57_Introduction to Scikit learnIn this video we will learn about the different methods of cleaning, uniforming, and streamlined API, as well as by very useful and complete online documentation in introduction to Scikit learn.Module 20: Building Machine Learning Models with Scikit-learnVideo 58_Linear, Logistic, K-Nearest, Decision Trees, Random ForestIn this video, we will discuss different regression and its classification like Linear, Logistic, k-Nearest, Decision Trees, Random Forest etc.Lab 58 Working with Linear RegressionIn this lab, we will be performing linear regression which is a basic and commonly used type of predictive analysis, which is used to examine things and shows a straight line through data points.Lab 59 Working with K-means ClusteringIn this lab we are working with K-means clustering which is used when you have unlabeled data and works iteratively to assign each data point to one of K groups based on the features that are provided.Module 21: Model Evaluation and SelectionVideo 59_Performance MetricsIn this video we are going to learn about the figures and data representation of an organizations actions, abilities, and overall quality and different forms of performance metrics, including sales, profit, return on investment, customer happiness, customer reviews, personal reviews, overall quality, and reputation in a marketplace in performance metrics.Lab 60 Working on Performance MetricsIn this lab we are going to understand about the use of metrics to understand and evaluate employee performance that can be essential for identifying objects.Video 60_Cross-ValidationIn this video, we will understand a technique used to protect against overfitting in a predictive model, particularly in a case where the amount of data may be limited and learn how we can cross-validate data in cross-validation.Lab 61 Hands-on with Cross-ValidationIn this lab, we will understand cross-validation which is a method of evaluating a machine learning model's performance across random samples of the dataset.Video 61_Grid SearchIn this video, we will be discussing grid search which is the process of scanning the data to configure optimal parameters for a given model and build a model on each parameter combination possible which iterates through every parameter combination and stores a model for each combination.Module 22: Getting Started with Python and Machine LearningVideo 62_Introduction to Machine LearningIn this video we are going to learn about the artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed in machine learning.Lab 62 Installing Software and Setting UpIn this lab well learn about the step by step installation of a software by understanding its different setting. In this video, we will be setting-up the software.Module 23: Exploring the 20 Newsgroups Dataset with Text Analysis AlgorithmsVideo 63_Exploring the 20 Newsgroups Dataset with Text Analysis AlgorithmsIn this video we will learn how we can explore the 20 newsgroups dataset with the text analysis algorithms by discovering serval algorithms and different techniques in it.Lab 63 Touring Powerful NLP Libraries in PythonIn this lab well be touring the powerful libraries of NPL in python where these packages handle a wide range of tasks such as part-of-speech (POS) tagging, sentiment analysis, document classification, topic modeling, etc.Lab 64 Getting the Newsgroups DataIn this lab, well be learning how we can get newsgroups data which is a collection of approximately 20,000 newsgroups so every unique word will have a unique value in our dictionary which is the most commonly used algorithm for text classification, Naive Bayes, etc.Lab 65 Thinking about FeaturesIn this lab, we will learn about the different features that are needed to fulfill the work and helps us to gather great ideas that can be done while using the tool.Lab 66 Working with VisualizationIn this lab we will understand that how we represent information and data in a graphical form by using visual elements like charts, graphs, data visualization tools that provide an accessible way to see and understand trends, outliers, and patterns in data.Video 64_Data Preprocessing and Topic ModelingIn this video, we will understand statistical modeling for discovering the abstract topics that occur in a collection of documents and learn how we can preprocess our data in Data preprocessing and Topic Modeling.Module 24: Spam Email Detection with Nave BayesVideo 65_Exploring Nave BayesIn this video, well be discussing exploring Nave Bayes at where we can explore nave Bayes that can make an assumption that the predictor variables are independent of each other.Lab 67 Model Tuning and Cross-validationIn this lab, well perform Model tuning and cross-validation which is the process of training learners using one set of data and testing it using a different set and selecting the values for a model's parameters that maximize the accuracy of the model and validate it.Module 25: News Topic Classification with Support Vector MachineVideo 66_The Mechanics of SVMIn this video, we will discuss the mechanics of the support vector machine which is a linear model for classification and regression problems that can solve linear and non-linear problems and work well for many practical problems.Lab 68 The Implementations of SVMIn this lab, we will perform the implementation of the support vector machine (SVM) that provides analysis of data for classification and regression analysis while they can be used for regression, and is mostly used for classification.Video 67_The Kernels of SVMIn this video, well learn about the function of kernel that is to take data as input and transform it into the required form in the kernels of support vector machines (SVM).Lab 69 The Kernels of SVMIn this lab we will work on function of kernel that can take data as input and transform it into the required form in the kernels of the support vector machine (SVM).Module 26: Click-Through Prediction with Tree-Based AlgorithmsVideo 68_Decision Tree ClassifierIn this video we are going to learn how we can build classification or regression models in the form of a tree structure which breaks down a dataset into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed.Lab 70 Decision Tree ClassifierIn this lab, we will learn about the decision tree classifier which builds classification or regression models in the form of a tree structure and breaks down a dataset into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed.Video 69_The Implementation of Decision TreeIn this video, we will understand how we can implement a decision tree by making several predictions with criterion information for achieving the dataset in Decision tree.Lab 71 Random Forest banging a Decision TreeIn this lab, we will be learning about the random forest banging a Decision tree which is an ensemble bagging algorithm to achieve low prediction error and also reduces the variance of the individual decision trees by randomly selecting trees and then either average them or picking the class that gets the most vote.Module 27: Click-Through Prediction with Logistic RegressionVideo 70_Logistic Regression ClassifierIn this video, well be discussing logistic regression which is basically a supervised classification algorithm. In this classification problem, the target variable(or output), y, can take only discrete values for a given set of features(or inputs), X.Lab 72 Working on Logistic Regression ClassifierIn this lab we will learn about the logistic regression classifier which classifies the target variable(or output), y, can take only discrete values for a given set of features(or inputs), X for the contrary to popular belief, logistic regression (IS) a regression model.Video 71_Click Through Prediction with Logistic Regression by Gradient DescentIn this video, we will discuss click-through prediction which predicts clicks and works with logistic regression by using gradient Descent at where it preprocesses data and the feature selection techniques would be done.Lab 73 Working on Feature Selection via Random ForestIn this lab, we will work on feature selection via random forest which is a process of identifying only the most relevant features which are used by random forests naturally ranks by how well they improve the purity of the node.Module 28: Stock Price Prediction with Regression AlgorithmsVideo 72_Stock Price Prediction with Regression AlgorithmsIn this video we will learn how we can predict the future stock price with the technique, which provide relevant links by using several regressions and different algorithms in it.Lab 74 Predicting Stock Price with Regression AlgorithmsIn this lab, we will work on predicting stock price with regression algorithms where the model overfits to the date and month column instead of taking into account the previous values from the point of prediction. The model will consider the value from the same date a month ago, or the same date/month a year ago while getting it.Video 73_Data Acquisition and Feature GenerationIn this video we are going to learn about the Data acquisition by which we can gather signals from measurement sources and digitizing the signals for storage, analysis, and presentation on a PC and understand different feature generation.Video 74_Regression Performance EvaluationIn this video, we will understand the regression performance against the ground truth at where we can evaluate it and compelled it to provide a necessary explanation regression performance evaluation.Module 29: Best PracticesVideo 75_Best PracticesIn this video, we will work on different methods that we've learned like different regression, distributions, generations and several methods.Lab 75 Best Practices in the Training Sets Generation StageIn this lab we will learn Best practices in the training sets generation stage with well-prepared data that is safe to move on with the generation stage with their redefined training sets.Lab 76 Best Practices in the Deployment and Monitoring StageIn this lab, we will work on the Best Practices in the Deployment and Monitoring Stage at where you deploy code. And, also it will ensure that you're sufficiently monitoring production for the metrics that matter to your engineers and your business."
Price: 19.99 |
| "Apache kafka - A Complete Hands-on Kafka Developer's Guide" |
| "Apache Kafka has become the leading distributed data streaming enterprise big data technology. Kafka is used in production by over 33% of the Fortune 500 companies such as Netflix, Airbnb, Uber, Walmart, and LinkedIn.To learn Kafka easily, step-by-step, you have come to the right place! No prior Kafka knowledge is required.If you look at the documentation, you can see that Apache Kafka is not easy to learn...Thanks to my several years of experience in Kafka and Big Data, I wanted to make learning Kafka accessible to everyone.We'll take a step-by-step approach to learn all the fundamentals of Apache Kafka.At the end of this course, you'll be productive and you'll know the following:The Apache Kafka Ecosystem ArchitectureThe Kafka Core Concepts: Topics, Partitions, Brokers, Replicas, Producers, Consumers, and more!Launch your own Kafka cluster in no time using native Kafka binaries Windows / MacOS X / LinuxLearn and Practice using the Kafka Command Line Interface (CLI)Code Producer and Consumers using the Java APIReal-world project using Twitter as a source of data for a producer and ElasticSearch as a sink for our consumerNote: The hands-on section is based on Java, which is the native Kafka programming language. But, good news! Your learning in Java will be completely applicable to other programming languages, such as Python, C#, Node.js or Scala, and Big Data frameworks such as Spark, NiFi or Akka."
Price: 19.99 |
| "Object Oriented Programming in Java - Beginner to Beyond" |
| "ES6 released in 2015 gave a big change and gave a lot of new features to JavaScript and modern web development. ES6 targets the declarative programming approach which helps the developer perform a quick development with complete ease.ES6 with new keywords allowed hoisting and scoping of the variables whether they are local, block-level or global. The new way of creating functions being vastly used because of its simple syntax and impact on the JavaScript this keywordTill ES5 the old approaches for iterations, performing asynchronous operations were used. Such as callback hell had become a mess but ES6 with the promises gave a proper design for asynchronous functionsNot only JavaScript is capable of functional programming but also with the release of ES6, Object Oriented Programming has been introduced in JavaScriptA bunch of methods ES6 has provided to quickly solve problems increasing the efficiency of code. Instead of writing the whole logic behind a solution, various functions are provided to help solve the problemMany modern libraries like React are using most of the syntax and implementation of ES6. Thus providing ease to the development. Although new features after ES6 are also being released they dont have the complete detail and a big change which ES6 broughtIntroduction to JS ES6 (Detailed)This lecture provides an overview of the course, the course objectives and requirements for the courseWhats New In ES6This lecture gives a brief overview of ES6, its approach, an additional featuresModule 1: i. ScopesThe paradigm of scopes in ES6, having access to local and global scopes and introducing let and constii. HoistingDiscriminates between the hoisting with var and hoisting in ES6 with let and constiii. Template LiteralsThis lecture introduces a new feature of ES6 which replaced using the string for variables to many extents and used for multi-line statementsiv. Default ParametersThis lecture covers how ES6 solved the problem of assigning default values of the function arguments by using Default Parametersv. Rest OperatorES6 introduces rest operators to gather all or remaining arguments of the function in an arrayvi. Spread OperatorThis lecture shows how the spread operator is used to separating each value of arrays or objectsvii. Arrow FunctionsThis lecture introduces ES6 most popular feature i.e. is arrow functions, how it is used and its syntaxviii. Arrow Functions with map, filter, reduceDescribes using the arrow functions with javascripts high order function such as map, filter and reduceModule 2:i. for .. of iteratorThe new method of iteration introduced in ES6. It can be applied to various objects to extract their keys or values or both and arrays also.ii. Destructuring Part 1This lecture contains the first part of Destructuring why is it so important. It is used in breaking down the elements of the array.iii. Destructuring Part 2How destructuring is applied to the objects to extract its various propertiesiv. Enhanced Object Properties And MethodsThe new enhanced methods and properties if objects to make it work in an easy wayv. SymbolA new and unique data type introduced in ES6vi. Set And MapNew types of data structures introduced in ES6 and their methods of adding, deleting, and getting the valuesvii. Weakmaps and Weak SetsAn introduction of weak maps and weak sets and how are they different from the maps and sets respectivelyviii. New Array MethodsThis lecture includes new array methods that are introduced in ES6Ix. New Built-in MethodsES6 contains a bunch of new built-in methods. This lecture aims to include those methodsModule 3:i. ClassesThis lecture includes the explanation of the Classes introduced in ES6 and how they are accessed.ii. Classes InheritanceThis lecture explains how OOP is applied in ES6 classes and how the instance of objects is creatediii. Setters and GettersClasses consist of the set and get methods to directly change the values. This lecture aims at explaining itiv. ModulesES6 contains various declarative approaches. Modules are one of them introduced in ES6 to access features from different filesv. Generators Part 1This lecture aims to explain what are generator functions, how they are controlledvi. Generators Part 2 This lecture concludes the generators that how values are handled and using generators inside another generatorsvii. Promise Part 1This lecture elaborates what is a promise, why are they used, its basic structure and its implementation in ES6viii. Promises Part 2This lecture includes advanced examples of Promises, how to chain multiple promises and promise . all () method"
Price: 19.99 |
| LINEBOT |
| "LINE Developers2019/12/28LINE Messaging API + Google Apps Script LineBotMessaging API LineGoogle Apps Script GoogleLineGoogleLineLineGoogleLineLineLineBotGoogle Apps Script JavaScriptLineBotLineBotMessaging API LineBot"
Price: 8400.00 |
| "GmailLINEMessaging APIGASLinebot" |
| "LINE Developers2019/12/28LINE Messaging API + Google Apps Script LINEGmailLinebotMessaging API LineGoogle Apps Script GmailLineLineGmailLineLineLineGooglebot LineLineLineBotGoogle Apps Script JavaScriptLineBotLineBotMessaging API LineBot"
Price: 8400.00 |
| "LINE Bot Designer & Node-REDLINE" |
| "LINE Bot DesignerLINE Bot DesignerLINEBOTLINE Bot DesignerLINE Bot DesignerLINELINE Bot DesignerLINE Bot DesignerLINEBOTLINEBOTLINE Bot DesignerNode-REDNode-REDLINE Bot DesignerNode-REDLINEBOTBOTBOTBOTBOTBOTBOTBOTline official account managerRichMenuAPINode-REDLINE Bot DesignerLINE Bot DesignerNode-REDLINEBOTNode-REDLINE RichMenuAPI"
Price: 9600.00 |
| AILINEBOT |
| "GoogleCloudVisionAPIAILINEBOTAILINEBOTJavaScriptLINEBOTLINBOTLINE Japanese New YearURLURLURLURLOCRLINBOTSNSAIGoogleCloudVisionAPIGoogleCloudVisionAPILINEMessaging APIGASGoogleAppsScriptMessaging APIGoogleAppsScriptJavaScript"
Price: 9600.00 |
| "les fondamentaux du basketball" |
| "Informations gnrales sur les fondamentaux offensifs et dfensifs de la discipline sportive du Basketball:le dribblele tir la passe la dfense le rebond le jeu sans ballonTous les fondamentaux offensifs avec la balle(dribble, tir,passe) sont excuts en jeu partir de la position de triple menace, afin de permettre aux joueurs dtre productifs,performants, excellents et efficaces, lors du droulement d'un match, et face diffrentes situations de jeu."
Price: 19.99 |
| "System Center Configuration Manager CB (SCCM) - Automated" |
| "If you are the type of individual who like to work smart and automate things, this course is for you.In this course we will be covering everything that is needed to automate the installation System Center Configuration Manager with the help of PowerShell scripts.It might sound a bit over the top at the moment, but after completing the course you will have a better understanding of what is required, to automate the installation of Microsoft System Center Configuration Manager and all the pre-requisites.In this course we will be covering the scripted install of:Windows Server Roles and FeaturesWindows ADK 10Windows ADK WINPEMicrosoft SQL Server 2017Microsoft SQL Server 2017 Latest Cumulative UpdateMicrosoft SQL Server Management StudioConfigure some settings in Microsoft SQL Server 2017Microsoft System Center Configuration Manager"
Price: 49.99 |
| "Dive into Calculus : Vectors and Matrices" |
| "This course covers matrices and vector calculus for functions of more than one variable. These mathematical tools and methods are used extensively in the physical sciences, engineering, economics and computer graphics.Topics include vectors and matrices, parametric curves, partial derivatives, double and triple integrals, and vector calculus in 2- and 3-space.As its name suggests, multivariable calculus is the extension of calculus to more than one variable. That is, in single variable calculus you study functions of a single independent variable.In multivariable calculus we study functions of two or more independent variables.These functions are interesting in their own right, but they are also essential for describing the physical world.Many things depend on more than one independent variable. Here are just a few:In thermodynamics pressure depends on volume and temperature.In electricity and magnetism, the magnetic and electric fields are functions of the three space variables (x,y,z) and one time variable t.In economics, functions can depend on a large number of independent variables, e.g., a manufacturer's cost might depend on the prices of 27 different commodities.In modeling fluid or heat flow the velocity field depends on position and time.Single variable calculus is a highly geometric subject and multivariable calculus is the same, maybe even more so. In your calculus class you studied the graphs of functions y=f(x) and learned to relate derivatives and integrals to these graphs. In this course we will also study graphs and relate them to derivatives and integrals. One key difference is that more variables means more geometric dimensions. This makes visualization of graphs both harder and more rewarding and useful.By the end of the course you will know how to differentiate and integrate functions of several variables. In single variable calculus the Fundamental Theorem of Calculus relates derivatives to integrals. We will see something similar in multivariable calculus."
Price: 19.99 |
| TOEICAdri |
| ": Adri : PDF TOEICAdri124PDFPDFAdriRLVBSea()She()TOEIC6Errhum ( )AdriMBA102 RL 12865I. II. 5 1. DAY 1: WOOD vs UDON 2. DAY 2: RIGHT vs LIGHT 3. DAY 3: SEA vs SHE 4. DAY 4: VERY vs BERRY 5. DAY 5: STAFF vs STUFF (+ WALK vs WORK)III. (DAY 6)IV. BONUS 1: 5 (DAY 7)V. BONUS 2: 4 (DAY 8)118 :TK SNS2020"
Price: 24000.00 |
| "Start Selling Online with Woocommerce Shopping Cart" |
| "The motive of this course is for the user to start directly selling online with minimal effort. The tutorial explains woocommerce plugin for wordpress website and how it lessens the efforts to start selling online. The course first explains how to create wordpress bitnami website using aws cloud . Then it begins configuring the created website step by step. Then it explains how to install the woocommerce plugin and configure all its settings. The course highlights some settings that are skipped during setup and cause trouble later.Then it explains how to change the Appearance of this website by installing a new theme.It explains how to configure payment gateways for this new website and how to start accepting payments from customers who buy books through our web store.For example illustration of Tony's Book Store is provided which make this tutorial more realistic. The site explained during this course is now a live site.The tutorial explains how to change menu items , how to change footer information and makes effort to quickly make this new website up and running.Course also explains some of the finer points such as Applying Coupon Code in order to carry out brisk sales of the products.All in all , this is one tutorial for people who want to get their online store ready as quickly as possible with no feature compromised."
Price: 1600.00 |
