ExcitingAds :: Exciting Ads

"In thisPHP and MYSQLcourse we aim to help you understand PHP and MYSQL by breaking down the core fundamentals and helping you learn to write code. We are interested in helping you master and understand PHP and MYSQL. This course starts you out by showing you important aspects of PHP and MYSQL and then moves on to more advancedPHP .We cover the core fundamentals needed for development.Those who want to learn PHP and MYSQL this is how we do itWe useLecturesHands On AssignmentsQuizzesWe use these methods to give you a university type setting and feel it is the best way for us to teach you these skills. With Lectures we go over the details of PHP and MYSQL and explain how things work and should be done. In Hands On Assignments we give you homework which helps push it into your mind and stay there. And in Quizzes we makes sure the knowledge has absorbed. We try to give you a University setting with out the high cost of a University."
Price: 199.99

"C# Programming from Zero to Hero : The Fundamentals"

"In this C# course we aim to help you understand C# by breaking down the core fundamentals and helping you learn to write code. We are interested in helping you master and understand the C# language. This course starts you out by showing you important aspects of C# and then moves on to more advanced C# .We cover the core fundamentals needed for development. Those who want to learn C# this is how we do itWe useLecturesHands On AssignmentsQuizzesWe use these methods to give you a university type setting and feel it is the best way for us to teach you these skills. With Lectures we go over the details of C# and explain how things work and should be done. In Hands On Assignments we give you homework which helps push it into your mind and stay there. And in Quizzes we makes sure the knowledge has absorbed. We try to give you a University setting with out the high cost of a University.What are the requirements? Nothing is pre required, We go over everything with you and cover everything you need to know in this series. What am I going to get from this course? Over 30 lectures and Tons of content!You will be able to efficiently write and understand C#You will be on your way to becoming a great developer"
Price: 199.99

"Jquery The Complete Course"

"In this Jquery course we aim to help you understand Jquery by breaking down the core fundamentals and helping you learn to write code. We are interested in helping you master and understand the Jquery language. This course starts you out by showing you important aspects of Jquery and then moves on to more advanced Jquery .We cover the core fundamentals needed for development.To those who want to learn Jquery this is how we do itWe useLecturesHands On AssignmentsQuizzesWe use these methods to give you a university type setting and feel it is the best way for us to teach you these skills. With Lectures we go over the details of Jquery and explain how things work and should be done. In Hands On Assignments we give you homework which helps push it into your mind and stay there. And in Quizzes we make sure the knowledge has absorbed. We try to give you a University setting with out the high cost of a University."
Price: 199.99

"Python Programming"

"In this python course we aim to help you understand python by breaking down the core fundamentals and helping you learn to write code. We are interested in helping you master and understand the python language. This course starts you out by showing you important aspects of python and then moves on to more advanced python and introduces you to the POSTGRESQL Database .We cover the core fundamentals needed for development.Those who want to learn python this is how we do itWe useLecturesHands On AssignmentsQuizzesWe use these methods to give you a university type setting and feel it is the best way for us to teach you these skills. With Lectures we go over the details of python and explain how things work and should be done. In Hands On Assignments we give you homework which helps push it into your mind and stay there. And in Quizzes we makes sure the knowledge has absorbed. We try to give you a University setting with out the high cost of a University.What are the requirements?Nothing is pre required, We go over everything with you and cover everything you need to know in this series.What am I going to get from this course?Over 30 lectures and Tons of content!You will be able to efficiently write and understand pythonYou will be on your way to becoming a great python developer"
Price: 199.99

"Introduction to Computer Science"

"COURSE IS STILL BEING BUILT!!!!!!!!!!!!!!!!!!In this Computer Science course we aim to help you understand Computer Science by explaining to you what goes into it and covering some areas of Computer Science So you can get a feel for it. . This course starts you out by showing you important aspects of Computer Science .Those who want to learn Computer Science this is how we do itWe useLecturesQuizzesWe use these methods to give you a university type setting and feel it is the best way for us to teach you these skills. With Lectures we go over the details of Computer Science and explain how things work and should be done. And in Quizzes we makes sure the knowledge has absorbed. We try to give you a University setting with out the high cost of a University.What are the requirements? Nothing is pre required, We go over everything with you and cover everything you need to know in this series. What am I going to get from this course? Over 30 lectures and Tons of content!You will be able to make a decision about Computer Science"
Price: 199.99

"Swift : from Apps to Game Development"

"In this Swift course we aim to help you understand Swift by breaking down the core fundamentals and we use ios swift 2 xcode 7 to take you from beginner to ready for a job. We do not just teach theory using ios swift we are helping you learn to write code. We are interested in helping you master and understand the Swift 2 language. This course starts you out by showing you important aspects of IOSSwift 2 and then moves on to more advanced Swift 2 .We cover the core fundamentals needed for development.Those who want to learn Swift 2 this is how we do itWe useLecturesHands On AssignmentsQuizzesWe use these methods to give you a university type setting and feel it is the best way for us to teach you these skills. With Lectures we go over the details of IOS Swift 2 and explain how things work and should be done. In Hands On Assignments we give you homework which helps push it into your mind and stay there. And in Quizzes we makes sure the knowledge has absorbed. We try to give you a University setting with out the high cost of a University."
Price: 199.99

"Instagram Success: Learn from the best brands on Instagram"

"This course gives you an overview of what the big brands are doing on Instagram and how you can quickly and easily make your account just as attractive as they are.Users should have some basic knowledge of Instagram and preferably have a functioning account so they can take advantage of the best practices taught hereBroken into different sections, the course is meant to be a tutorial that is quick and easy to digest where you see some of the strategies of the larger accounts on Instagram and begin to understand why the larger accounts are successful.We look at accounts like Red Bull and Go Pro and show you what they are doing differently than other brands.If you are a small to medium sized business who is just getting going using Instagram as a platform to share your brand, this course is for you. This course is also for people who aspire to have their Instagram look professional like the big brands."
Price: 19.99

"100 Single Page Mini Websites 100x Profit - Amazon Affiliate"

"Welcome to this journey. The technique in this course work for new google update. Your website will not make any money if you cannot get it rank on page 1 no matter how beautiful or how much content you have.If you want to make money. I am showing you a way to make money by being a amazon affiliate.Watch the Promo video.To make money 1) You can setup a complex and beautiful website, invest lot of money and resources into it and take years to build your brand and profile or 2) Make use of google free platform and setup a 1 page blogger website. Does it look unprofessional? No if you are promoting a amazon product and not promoting your own brand, it is just a simple blogger website. The advantage is google own blogger and google give priority to blogger when it come to ranking.Setup a 1 page (nothing more than 1 page as you see in the demo)Create 4 backlink of web 2.0Sit back and wait for 1 weekCheck for ranking and watch your amazon income go upZero maintanence require, as long as the product you are promoting still got searches and still have stock you will generate commission.Want to make more.Setup 100 blogger website. 1 website with all web 2.0 backlink take 1 week to setup (that is if you are working 1 hour a day) (when you get familar with it you will need only 30 mins a day or infact about 5 hours to setup the complete blog)do this everyweek and by the end of 1 year you will have 52 blog earning you 52 amazon commission. Do it for 2 years and 3 years. I personal guranteeed you will never have to look for another job ever againEnrol Now I will see you on the other side"
Price: 149.99

"Photo Restoration: Bring Old Photos Back to Life"

"In this photo restoration course you will learn the art and techniques of restoring photographs using Adobe Photoshop.Do you have some old photos you want to digitize, restore and bring back to life? Or you just want to learn the techniques for restoring old photos? Then this course is for you!In this course you'll learn the techniques of converting old photographs to a digital format and restoring these photos to its former glory. You learn how to fix torn or otherwise damaged areas of a photo to improving the level of detail to adding or fixing the color.We first start out teaching the best methods for scanning and importing your old photos. Next, we will move into the tools and techniques for restoring an old photo. We will go over a variety of topics such as, color correction, fixing the defects and a variety of other image restoration methods. This is a project based course that will help any Photoshop user. Get started and learn how to repair and restore old or damaged photographs using Adobe Photoshop in this easy to follow course. This course is also great for anyone who has a stack of old photos and just wants to simply convert it into a digital photo. Typically, there is some minor adjustments and we will show you how to do just that."
Price: 19.99

"Ultimate Guide to Running - for beginners to experts"

"""Running never gets easier, but if you don't change your mindset, it never gets more difficult either"" Running is both beautiful and dreadful, the highs are high, the lows are low. For some, the most difficult act is that of putting on your shoes, for some its the act of resting, but for everyone who's tried it, running is incredibly unique and personal.We understand that running is not a means-to-an-end but rather an integral part of a healthy and happy life.As people who love to run every day, we want to share the joy of running with you, as your friends, as well as help you to become the best runner you can be, as your coaches.Whatever your running goals may be, this course will help you achieve them and take your running to the next level. There is something here for everyone from the beginner to the seasoned runner.We've noticed a gap between those of you looking to start running for the very first time and those of you looking to break your best time on your next ultra-marathon and we've built the bridge to join us all into one big running community. We've answered your questions, some of which you may not have known to ask yet, and we've covered all facets of a runners' lifestyle from training, racing, cross-training and injuries to nutrition, psychology and even gadgets.This course covers everything from the foundations of good running techniques to the tricks only learned through years of running experience! We are your online running coaches, nutritionists, mentors and comrades. The course offers:Hours of video lectures and presentationsReal-life training footageDownloadable training plansPages of recipes and downloadable meal plansThis course is easy to navigate and find the relevant lectures for your own unique goals. It is a necessary accessory to your training and should constantly be referred back to. This is not designed to be watched from start to finish but rather be incorporated into your runs and practical everyday life. That being said, the course could be completed in a little over 6 hours.This course is for anyone looking to improve their running fitness, set new goals and reach them, improve their overall health and look after their bodies and well-being through the sport of running."
Price: 54.99

"""isiXhosa for Beginners"" South African Language"

"This course is run over 4 weeks, but is self paced. We estimate it should take 8 hours and should you choose to do it in 1 day or the full 8 weeks it is completely up to you, you will have lifetime access to this course you may download the ebooks to take with you forever. The aim of this course is to introduce you to the Xhosa language and make you proficient in basic conversation.The aim of this course is to not only give you an introduction to the language of isiXhosa, but to also be a strong foundation for anyone wanting to take the first step in their journey to mastering the language.This course will focus on conversational isiXhosa, including mastering the poetic clicking sounds, learning general phrases and language skills. A large part of the course also focus on meeting someone new, getting around and asking the important question words we so often need.The format of this course is primarily based on short videos followed by simple quizzes to re-enforce your knowledge. There are many interactive resources and ""Real-life"" communication is encouraged as much as possible.There are a total of 4 units in this course. Should you have any general questions, do not hesitate to post them in the forums"
Price: 29.99

"Maths grade 8 (1 of 5) Numbers, Operations & Relationships"

"Welcome to this Mathematics Grade 8 course, module 1 of 5 on Numbers, Operations & Relationships.The aim of this course is for it to be taught in a 21st century mindset. The course is actually fun, it uses technology, the internet and general knowledge to better equip a student for real life applications.This course is intended for absolutely age 12-14 years old whom already has a foundation phase understanding in Mathematics. This course is also suitable for any end of middle-school to start of High School (US) or Grade 7-9 (UK) teachers who want to improve upon classroom teaching methods. This course is packed with 7+ hours of video content encouraging students to answer questions throughout the videos. There are 5 modules in total, this is module 1.1. Numbers, Operations & Relationships.2. Patterns, Functions & Algebra. 3. Space and Shape.4. Measurement.5. Data Handling.The course has been broken into 5 modules to i) allow students to only enroll in what sections they are struggling with, ii) save the parent or student cost as each module is the price of a tutoring lesson and lastly, iii) to encourage students to break goals into bite-sized chunks. There is 16+ hours of video in all five modules.This course is intended to be a resource to help students throughout the year, it can be completed slowly and referred to throughout your year of study. The course has been broken down into the following sub-sections, each containing their own set of videos:Whole NumbersExponentsIntegersCommon FractionsDecimal FractionsRate & ProportionFinancial MathsEnjoy!"
Price: 39.99

"Mathematics Grade 8 (2 of 5) - Patterns, Functions & Algebra"

"Welcome to this Mathematics Grade 8 course, module 2 of 5 on Patterns, Functions & Algebra.The aim of this course is for it to be taught in a 21st century mindset. The course is actually fun, it uses technology, the internet and general knowledge to better equip a student for real life applications.This course is intended for absolutely age 12-14 years old whom already has a foundation phase understanding in Mathematics. This course is also suitable for any end of middle-school to start of High School (US) or Grade 7-9 (UK) teachers who want to improve upon classroom teaching methods. This course is packed with 2+ hours of video content encouraging students to answer questions throughout the videos. There are 5 modules in total, this is module 2.1. Numbers, Operations & Relationships.2. Patterns, Functions & Algebra. 3. Space and Shape.4. Measurement.5. Data Handling.The course has been broken into 5 modules to i) allow students to only enroll in what sections they are struggling with, ii) save the parent or student cost as each module is the price of a tutoring lesson and lastly, iii) to encourage students to break goals into bite-sized chunks. There is 16+ hours of video in all five modules. This course is intended to be a resource to help students throughout the year, it can be completed slowly and referred to throughout your year of study. The course has been broken down into the following sub-sections, each containing their own set of videos:Numeric and Geometric Patterns.Functions and Relationships.Algebraic Expressions.Algebraic Equations.Enjoy!"
Price: 39.99

"Mathematics Grade 8 (3 of 5) - Space & Shape"

"Welcome to this Mathematics Grade 8 course, module 3 of 5 on Space & Shape.The aim of this course is for it to be taught in a 21st century mindset. The course is actually fun, it uses technology, the internet and general knowledge to better equip a student for real life applications.This course is intended for absolutely age 12-14 years old whom already has a foundation phase understanding in Mathematics. This course is also suitable for any end of middle-school to start of High School (US) or Grade 7-9 (UK) teachers who want to improve upon classroom teaching methods. This course is packed with 2+ hours of video content encouraging students to answer questions throughout the videos. There are 5 modules in total, this is module 3.1. Numbers, Operations & Relationships.2. Patterns, Functions & Algebra. 3. Space and Shape.4. Measurement.5. Data Handling.The course has been broken into 5 modules to i) allow students to only enroll in what sections they are struggling with, ii) save the parent or student cost as each module is the price of a tutoring lesson and lastly, iii) to encourage students to break goals into bite-sized chunks. There is 16+ hours of video in all five modules.This course is intended to be a resource to help students throughout the year, it can be completed slowly and referred to throughout your year of study. The course has been broken down into the following sub-sections, each containing their own set of videos:Geometry of 2D shapesGeometry of 3D objectsGeometry of straight linesTransformation GeometryConstruction Geometry Construction of Geometric FiguresEnjoy!"
Price: 39.99

"Mathematics Grade 8 (5 of 5) - Data Handling"

"Welcome to this Mathematics Grade 8 course, module 5 of 5 on Data Handling.The aim of this course is for it to be taught in a 21st century mindset. The course is actually fun, it uses technology, the internet and general knowledge to better equip a student for real life applications.This course is intended for absolutely age 12-14 years old whom already has a foundation phase understanding in Mathematics. This course is also suitable for any end of middle-school to start of High School (US) or Grade 7-9 (UK) teachers who want to improve upon classroom teaching methods. This course is packed with 1.5+ hours of video content encouraging students to answer questions throughout the videos. There are 5 modules in total, this is module 5.1. Numbers, Operations & Relationships.2. Patterns, Functions & Algebra. 3. Space and Shape.4. Measurement.5. Data Handling.The course has been broken into 5 modules to i) allow students to only enroll in what sections they are struggling with, ii) save the parent or student cost as each module is the price of a tutoring lesson and lastly, iii) to encourage students to break goals into bite-sized chunks. There is 16+ hours of video in all five modules.This course is intended to be a resource to help students throughout the year, it can be completed slowly and referred to throughout your year of study. The course has been broken down into the following sub-sections, each containing their own set of videos:Collecting, Organising and Summarising DataRepresent DataProbabilityEnjoy!"
Price: 39.99

"Mathematics Grade 8 (4 of 5) - Measurement"

"Welcome to this Mathematics Grade 8 course, module 4 of 5 on Measurement.The aim of this course is for it to be taught in a 21st century mindset. The course is actually fun, it uses technology, the internet and general knowledge to better equip a student for real life applications.This course is intended for absolutely age 12-14 years old whom already has a foundation phase understanding in Mathematics. This course is also suitable for any end of middle-school to start of High School (US) or Grade 7-9 (UK) teachers who want to improve upon classroom teaching methods. This course is packed with 2+ hours of video content encouraging students to answer questions throughout the videos. There are 5 modules in total, this is module 4.1. Numbers, Operations & Relationships.2. Patterns, Functions & Algebra. 3. Space and Shape.4. Measurement.5. Data Handling.The course has been broken into 5 modules to i) allow students to only enroll in what sections they are struggling with, ii) save the parent or student cost as each module is the price of a tutoring lesson and lastly, iii) to encourage students to break goals into bite-sized chunks. There is 16+ hours of video in all five modules.This course is intended to be a resource to help students throughout the year, it can be completed slowly and referred to throughout your year of study. The course has been broken down into the following sub-sections, each containing their own set of videos:Area and Perimeter of 2D ShapesVolume and Surface Area of 3D ShapesTheorem of PythagorasEnjoy!"
Price: 39.99

"Stock Fundamental Analysis with Excel"

"Full Course Content Last Update 01/2019Learn stock fundamental analysis through a practical course with Microsoft Excel using Apple Inc. data for historical analysis. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your research as experienced investor. All of this while exploring the wisdom of Nobel Prize winners and best practitioners in the field.Become a Stock Fundamental Analysis Expert in this Practical Course with ExcelUnderstand main financial statements such as balance sheet, income statement and cash flow statement.Interpret financial ratios to analyze operating activities, investing activities, liquidity, solvency and profitability.Comprehend investment valuation ratios to assess relative magnitudes of stock price or enterprise value to key financial statements numerical values and corresponding yields.Estimate cost of equity through capital asset pricing model (CAPM), Fama-French three factors model or arbitrage pricing theory model (APT) and cost of capital through weighted average cost of capital model (WACC).Assess economic profit through economic value added model (EVA) and observed market value added model (MVA).Approximate theoretical stock price through discounted cash flow models (DCF) such as discounted dividends model (DDM), discounted free cash flow to equity model (DFCFE) and discounted free cash flow to firm model (DFCFF).Estimate stock option prices through Black and Scholes model, one-step binomial tree model, two-steps binomial tree model and Monte Carlo Simulation method (MCS).Become a Stock Fundamental Analysis Expert and Put Your Knowledge in PracticeLearning stock fundamental analysis is essential for finance careers in areas such as equity research, investment banking, private equity or venture capital. It is also indispensable for academic careers in finance or business research. And it is necessary for experienced investors research of stock fundamentals.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using Apple Inc. data for historical analysis and to achieve greater effectiveness. Content and OverviewThis practical course contains 49 lectures and 9 hours of content. Its designed for all stock fundamental analysis knowledge levels and a basic understanding of Microsoft Excel is useful but not required.At first, youll learn how to perform stock fundamental analysis operations using built-in functions and array calculations. Next, youll learn how to do random number generation for option pricing calculation using Microsoft Excel Add-in.Then, youll define financial statements. For financial statements, youll define balance sheet, income statement and cash flow statement. After that, youll define financial ratios and compare them with historical average and competitor. For financial ratios, youll define operating activities, investing activities, liquidity, solvency and profitability areas. For models based on financial ratios, youll define DuPont analysis, Altman Z-Score and Piotroski F-Score.Later, youll define investment valuation ratios and compare them with historical average, competitor, market benchmark and risk-free rate of return. For investment valuation ratios, youll define price ratios, enterprise value ratios and yield ratios.Next, youll define cost of equity. For cost of equity, youll define capital asset pricing model (CAPM), Fama-French three factors model and arbitrage pricing theory model (APT). Then, youll define cost of capital. For cost of capital, youll define weighted average cost of capital model (WACC).After that, youll define economic profit. For economic profit, youll define economic value added model (EVA) and observed market value added model (MVA). Later, youll estimate theoretical stock price through discounted cash flow models (DCF). For discounted cash flow models (DCF), youll define discounted dividends model (DDM), discounted free cash flow to equity model (DFCFE) and discounted free cash flow to firm model (DFCFF).Finally, youll define financial options. For financial options pricing, youll define Black and Scholes model, one-step binomial tree model, two-steps binomial tree model and Monte Carlo simulation method (MCS)."
Price: 24.99

"Excel for Data Analysis: Basic to Expert Level"

"Full Course Content Last Update 12/2019Learn data analysis through a practical course with Microsoft Excel using S&P 500 Index ETF prices historical data. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your business data analysis research. All of this while exploring the wisdom of best academics and practitioners in the field.Become a Data Analysis Expert in this Practical Course with ExcelUse main Excel file or workbook types and protect them before sharing. Store data in workbooks consisting of one of more worksheets.Navigate worksheets through their cells which can be grouped in ranges.Move quickly through worksheet using keyboard shortcuts. Perform data calculations using basic arithmetic formulas, main categories built-in functions and arrays.Correct formula errors and perform user input data validation. Organize data interactively using tables and customizable pivot tables while sorting, filtering and performing calculations on their contents.Visualize data using conditional formatting, main chart types and single cell sparklines.Implement data scenarios summary forecast using what-if analysis and find value for achieving certain calculation result using goal seek changing cell iteration.Analyze data and estimate optimal parameter using data analysis tools package and solver Microsoft Excel Add-ins.Identify data trends using moving average and exponential smoothing tools.Summarize data descriptive statistics and print its frequency histogram. Estimate correlation between variables and analyze regression summary output between explained and explanatory variables.Generate random numbers based on specific probability distribution.Estimate optimal parameter using constrained minimization.Become a Data Analysis Expert and Put Your Knowledge in PracticeLearning data analysis is indispensable for business data analysis applications in areas such as consumer analytics, finance, banking, health care, e-commerce or social media. It is also essential for academic careers in data analysis, applied statistics, economics, econometrics and quantitative finance. And its necessary for business data analysis research.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500 Index ETF prices historical data for data analysis to achieve greater effectiveness.Content and OverviewThis practical course contains 42 lectures and 6.5 hours of content. Its designed for all data analysis knowledge levels and a basic understanding of Microsoft Excel is useful but not required.At first, youll define data analysis operations using Microsoft Excel. Next, youll define data analysis tools package and solver Microsoft Excel Add-ins.Then, youll define Excel file, file options, workbook and main workbook types. Next, youll define ribbon. For ribbon, youll define file tab, home tab, insert tab, page layout tab, formulas tab, data tab, review tab and view tab. After that, youll define worksheet. Later, youll define cells and cells references. For cells references, youll define relative reference, absolute reference, mixed reference and 3D reference. Then, youll define ranges and ranges operators. For ranges operators, youll define union range operator, intersect range operator and mathematical union. Next, youll define keyboard shortcuts.Next, youll define formulas, status bar and functions. For functions, youll define date & time functions category, financial functions category, logical functions category, lookup & reference functions category, mathematic & trigonometric functions category, statistics functions category and text functions category. Then, youll define array formulas. After that, youll define formula errors and formula auditing options. Later, youll define range of cells defined name and user input data validation.After that, youll define data analysis. Then, youll define sorting and filtering table data. Next, youll define conditional formatting. For conditional formatting, youll define highlight cell rules, top/bottom rules, data bars rules, color scales rules and icon set rules. Later, youll define column chart, line chart, pie chart, scatter chart, line sparkline, column sparkline and win/loss sparkline. After that, youll define tables and customizable pivot tables. For customizable pivot tables, youll define field selection feature, sorting and filtering feature, value field settings feature and chart feature. Then, youll define what-if data scenario summary and goal seek changing cell iteration. Next, youll define data analysis tools package Microsoft Excel Add-in. For data analysis tools package, youll define moving average analysis tool, exponential smoothing analysis tool, descriptive statistics analysis tool, histogram analysis tool, correlation analysis tool, regression analysis tool and random number generation analysis tool. Finally, youll define solver Microsoft Excel Add-in. For solver, youll define optimal parameter estimation through constrained minimization."
Price: 24.99

"Investment Portfolio Analysis with Excel"

"Full Course Content Last Update 12/2018Learn investment portfolio analysis through a practical course with Microsoft Excel using index replicating ETFs and Mutual Funds historical data for back-testing. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your research as experienced investor. All of this while exploring the wisdom of Nobel Prize winners and best practitioners in the field.Become an Investment Portfolio Analysis Expert in this Practical Course with ExcelCompare main asset classes benchmark indexes replicating funds returns and risks tradeoffs for cash, bonds, stocks, commodities, real estate and currencies.Estimate portfolio expected returns, historical and market participants implied volatility. Approximate portfolio expected excess returns using capital asset pricing model (CAPM), Fama-French-Carhart factors model and arbitrage pricing theory model (APT).Hedge portfolio systematic risk through options trading strategies benchmark indexes replicating funds.Evaluate hedge fund index performance and assess portfolio returns and risks amplification through leverage.Calculate portfolio performance metrics such as Sharpe, Treynor, Sortino, and Kelly ratios.Estimate benchmark global portfolios returns from periodically rebalanced equal weighted asset allocations and those from well-known investment managers.Optimize global portfolios asset allocation weights for mean maximization, standard deviation minimization, mean maximization and standard deviation minimization, mean maximization and value at risk minimization objectives within training range based on Markowitz portfolio theory.Approximate global portfolios returns from periodically rebalanced optimized asset allocations within testing range and compare them with equal weighted and well-known investment managers benchmark portfolios.Evaluate global portfolios performance through global risk factors model and estimate their expected return, expected excess return and expected return contribution from global risk factors exposure while assessing investment costs impact on portfolio performance.Become an Investment Portfolio Analysis Expert and Put Your Knowledge in PracticeLearning investment portfolio analysis is indispensable for finance careers in areas such as asset management, private wealth management, and risk management within institutional investors represented by banks, insurance companies, pension funds, hedge funds, investment advisors, endowments and mutual funds. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors optimized asset allocation strategies research and development.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using index replicating funds historical data for back-testing and to achieve greater effectiveness. Content and OverviewThis practical course contains 43 lectures and 8.5 hours of content. Its designed for all investment portfolio analysis knowledge levels and a basic understanding of Microsoft Excel is useful but not required.At first, youll learn how to perform investment portfolio analysis operations using built-in functions and array calculations. Next, youll learn how to do portfolio optimization parameters estimation and linear regression calculation using Microsoft Excel Add-ins.Then, youll define main asset classes by comparing their benchmark indexes replicating funds returns and risks tradeoffs. After that, youll segment main asset classes into traditional and alternative ones. For traditional asset classes, youll define cash and cash equivalents, fixed income or bonds and equities or stocks. Regarding cash and cash equivalents traditional asset class, youll use U.S. total money market benchmark index replicating fund. Regarding cash and cash equivalents traditional asset class, youll use U.S. total money market benchmark index replicating fund is used. Regarding fixed income or bonds traditional asset class, U.S. total bond market, U.S. short term bond market, U.S. long term bond market and international total bond market benchmark indexes replicating funds. Regarding equities or stocks traditional asset class, youll use U.S. total stock market, U.S. large cap stock market, U.S. small cap stock market, U.S. small cap growth stock market, U.S. small cap value stock market, international total stock market, international developed stock market and international emerging stock market benchmark indexes replicating funds. For alternative asset classes, youll define commodities, real estate and currencies or foreign exchange. Regarding commodities alternative asset class, youll use oil and gold prices benchmark indexes replicating funds. Regarding real estate alternative asset class, youll use U.S. real estate investment trust market benchmark index replicating fund. Regarding currencies or foreign exchange alternative asset class, youll use U.S. dollar major currencies benchmark index replicating fund.Next, youll define returns and risks using U.S. large cap stocks market benchmark index replicating fund. After that, youll calculate expected returns through historical returns mean and median. Then, youll estimate risks through historical returns standard deviation, mean absolute deviation and market participants implied volatility. Later, youll approximate portfolio expected excess returns through capital asset pricing model (CAPM), Fama-French-Carhart factors model and arbitrage pricing theory model (APT). Next, youll hedge portfolio systematic risk through options trading strategies and evaluate hedge fund index performance together with the assessment of returns and risks amplification through portfolio leverage. After that, youll define portfolio optimization through global assets allocation. Next, youll calculate Sharpe ratio, Treynor ratio, Sortino ratio and Kelly ratio portfolio performance metrics. Then, youll estimate benchmark global portfolios returns from periodically rebalanced equal weighted asset allocations and those from well-known investment managers. Later, youll optimize global asset allocation weights within training range for mean maximization, standard deviation minimization, mean maximization and standard deviation minimization, mean maximization and value at risk minimization objectives based on Markowitz portfolio theory. After that, youll calculate global portfolio returns within testing range using previously optimized periodically rebalance asset allocation weights and compare them with equal weighted and well-known investment managers benchmark portfolios.Later, youll evaluate optimized portfolios performance through global risk factors model. After that, youll estimate optimized portfolios expected returns, expected excess returns and global risk factors exposure returns contribution. Finally, youll assess investment costs impact on portfolio performance."
Price: 24.99

"Forecasting Models with Excel"

"Full Course Content Last Update 06/2018Learn forecasting models through a practical course with Microsoft Excel using S&P 500 Index ETF prices historical data. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your business forecasting research. All of this while exploring the wisdom of best academics and practitioners in the field.Become a Forecasting Models Expert in this Practical Course with ExcelEstimate simple forecasting methods such as arithmetic mean, random walk, seasonal random walk and random walk with drift.Evaluate simple forecasting methods forecasting accuracy through mean absolute error, root mean squared error scale-dependent and mean absolute percentage error, mean absolute scaled error scale-independent metrics.Approximate simple moving averages and exponential smoothing methods with no trend or seasonal patterns such as Brown simple exponential smoothing method.Estimate exponential smoothing methods with only trend patterns such as Holt linear trend, exponential trend, Gardner additive damped trend and Taylor multiplicative damped trend methods.Approximate exponential smoothing methods with trend and seasonal patterns such as Holt-Winters additive, Holt-Winters multiplicative and Holt-Winters damped methods.Select exponential smoothing method with lowest Akaike, corrected Akaike and Schwarz Bayesian information loss criteria.Identify Box-Jenkins autoregressive integrated moving average model integration order through level and differentiated first order trend stationary time series deterministic test and Phillips-Perron unit root test.Recognize autoregressive integrated moving average model autoregressive and moving average orders through autocorrelation and partial autocorrelation functions.Estimate non-seasonal autoregressive integrated moving average models such as random walk with drift, differentiated first order autoregressive, Brown simple exponential smoothing, simple exponential smoothing with growth, Holt linear trend and Gardner additive damped trend models.Approximate seasonal autoregressive integrated moving average models such as seasonal random walk, seasonal random trend and seasonally differentiated first order autoregressive models.Choose autoregressive integrated moving average model with lowest Akaike, corrected Akaike and Schwarz Bayesian information loss criteria.Assess highest forecasting accuracy autoregressive integrated moving average model residuals or forecasting errors white noise requirement through Ljung-Box lagged autocorrelation test.Become a Forecasting Models Expert and Put Your Knowledge in PracticeLearning forecasting models is indispensable for business or financial data science applications in areas such as sales and financial forecasting, inventory optimization, demand and operations planning, and cash flow management. It is also essential for academic careers in data science, applied statistics, operations research, economics, econometrics and quantitative finance. And its necessary for business forecasting research.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500 Index ETF prices historical data for forecast modelling to achieve greater effectiveness.Content and OverviewThis practical course contains 42 lectures and 8 hours of content. Its designed for all forecasting models knowledge levels and a basic understanding of Microsoft Excel is useful but not required.At first, youll learn how to perform forecasting models operations using built-in functions and array calculations. Next, youll learn how to do optimal parameter estimation or fine tuning and linear regression calculation using Microsoft Excel Add-ins.Then, youll define simple forecasting methods such as arithmetic mean, random walk, seasonal random walk and random walk with drift. Next, youll evaluate simple methods forecasting accuracy through scale-dependent and scale-independent error metrics. For scale-dependent metrics, youll define mean absolute error and root mean squared error. For scale-independent metrics, youll define mean absolute percentage error and mean absolute scaled error.Next, youll define simple moving averages and exponential smoothing methods. For exponential smoothing methods with no trend or seasonal patterns, youll define Brown simple exponential smoothing method. For exponential smoothing methods with only trend patterns, youll define Holt linear trend, exponential trend, Gardner additive damped trend and Taylor multiplicative damped trend methods. For exponential smoothing methods with trend and seasonal patterns, youll define Holt-Winters additive, Holt-Winters multiplicative and Holt-Winters damped methods. After that, youll select exponential smoothing method with lowest information loss criteria. For information loss criteria, youll define Akaike, corrected Akaike and Schwarz Bayesian information loss criteria. Later, youll evaluate simple moving average and exponential smoothing methods forecasting accuracy through scale-dependent and scale-independent error metrics. For scale-dependent metrics, youll define mean absolute error and root mean squared error. For scale-independent metrics, youll define mean absolute percentage error and mean absolute scaled error.After that, youll define Box-Jenkins autoregressive integrated moving average models. Then, youll identify autoregressive integrated moving average model integration order through level and differentiated time series first order trend stationary deterministic test and Phillips-Perron unit root test. Next, youll identify autoregressive integrated moving average model autoregressive and moving average orders through autocorrelation and partial autocorrelation functions. For non-seasonal autoregressive integrated moving average models, youll define random walk with drift, differentiated first order autoregressive, Brown simple exponential smoothing, simple exponential smoothing with growth, Holt linear trend and Gardner additive damped trend models. For seasonal autoregressive integrated moving average models, youll define seasonal random walk, seasonal random trend and seasonally differentiated first order autoregressive models. After that, youll select autoregressive integrated moving average model with lowest information loss criteria. For information loss criteria, youll define Akaike, corrected Akaike and Schwarz Bayesian information loss criteria. Later, youll evaluate models forecasting accuracy through scale-dependent and scale-independent error metrics. For scale-dependent metrics, youll define mean absolute error and root mean squared error. For scale-independent metrics, youll define mean absolute percentage error and mean absolute scaled error. Finally, youll assess highest forecasting accuracy autoregressive integrated moving average model residuals or forecasting errors white noise requirement through Ljung-Box lagged autocorrelation test."
Price: 24.99

"Forecasting Models with R"

"Full Course Content Last Update 04/2018Learn forecasting models through a practical course with R statistical software using S&P 500 Index ETF prices historical data. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your business forecasting research. All of this while exploring the wisdom of best academics and practitioners in the field.Become a Forecasting Models Expert in this Practical Course with RRead S&P 500 Index ETF prices data and perform forecasting models operations by installing related packages and running script code on RStudio IDE.Estimate simple forecasting methods such as arithmetic mean, random walk, seasonal random walk and random walk with drift.Evaluate simple forecasting methods forecasting accuracy through mean absolute error, root mean squared error scale-dependent and mean absolute percentage error scale-independent metrics.Approximate simple moving averages and exponential smoothing methods with no trend or seasonal patterns such as Brown simple exponential smoothing method.Estimate exponential smoothing methods with only trend patterns such as Holt linear trend, exponential trend, Gardner additive damped trend and Taylor multiplicative damped trend methods.Approximate exponential smoothing methods with trend and seasonal patters such as Holt-Winters additive, Holt-Winters multiplicative and Holt-Winters damped methods.Automatically select exponential smoothing method with lowest information loss criteria.Asses simple moving average and exponential smoothing methods forecasting accuracy through Hyndman-Koehler mean absolute scaled error scale-independent metric.Identify Box-Jenkins autoregressive integrated moving average model integration order through level and differentiated first order trend stationary time series augmented Dickey-Fuller and Phillips-Perron unit root tests.Recognize autoregressive integrated moving average model autoregressive and moving average orders through autocorrelation and partial autocorrelation functions.Estimate non-seasonal autoregressive integrated moving average models such as random walk, random walk with drift, differentiated first order autoregressive, Brown simple exponential smoothing, simple exponential smoothing with growth, Holt linear trend and Gardner additive damped trend models.Approximate seasonal autoregressive integrated moving average models such as seasonal random walk, seasonal random trend, general seasonal, general first order autoregressive seasonal, seasonally differentiated first order autoregressive and Holt-Winters additive models.Automatically choose autoregressive integrated moving average model with lowest information loss criteria.Evaluate autoregressive integrated moving average models forecasting accuracy through scale-dependent, scale-independent metrics, Akaike, corrected Akaike and Schwarz Bayesian information loss criteria.Assess lowest information loss criteria autoregressive integrated moving average model residuals or forecasting errors white noise requirement through Ljung-Box lagged autocorrelation test.Become a Forecasting Models Expert and Put Your Knowledge in PracticeLearning forecasting models is indispensable for business or financial data science applications in areas such as sales and financial forecasting, inventory optimization, demand and operations planning, and cash flow management. It is also essential for academic careers in data science, applied statistics, operations research, economics, econometrics and quantitative finance. And its necessary for business forecasting research.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500 Index ETF prices historical data for forecast modelling to achieve greater effectiveness.Content and OverviewThis practical course contains 40 lectures and 6 hours of content. Its designed for all forecasting models knowledge levels and a basic understanding of R statistical software is useful but not required.At first, youll learn how to read S&P 500 Index ETF prices historical data to perform forecasting models operations by installing related packages and running script code on RStudio IDE.Then, youll define simple forecasting methods such as arithmetic mean, random walk, seasonal random walk and random walk with drift. Next, youll evaluate simple methods forecasting accuracy through scale-dependent and scale-independent error metrics. For scale-dependent metrics, youll define mean absolute error and root mean squared error. For scale-independent metrics, youll define mean absolute percentage error.Next, youll define simple moving averages and exponential smoothing methods. For exponential smoothing methods with no trend or seasonal patterns, youll define Brown simple exponential smoothing method. For exponential smoothing methods with only trend patterns, youll define Holt linear trend, exponential trend, Gardner additive damped trend and Taylor multiplicative damped trend methods. For exponential smoothing methods with trend and seasonal patterns, youll define Holt-Winters additive, Holt-Winters multiplicative and Holt-Winters damped methods. After that, youll automatically select exponential smoothing method with lowest information loss criteria. Later, youll evaluate simple moving average and exponential smoothing methods forecasting accuracy through Hyndman-Koehler scale-independent mean absolute scaled error metric.After that, youll define Box-Jenkins autoregressive integrated moving average models. Then, youll identify autoregressive integrated moving average model integration order through level and differentiated time series first order trend stationary augmented Dickey-Fuller and Phillips-Perron unit root tests. Next, youll identify autoregressive integrated moving average model autoregressive and moving average orders through autocorrelation and partial autocorrelation functions. For non-seasonal autoregressive integrated moving average models, youll define random walk, random walk with drift, differentiated first order autoregressive, Brown simple exponential smoothing, simple exponential smoothing with growth, Holt linear trend and Gardner additive damped trend models. For seasonal autoregressive integrated moving average models, youll define seasonal random walk, seasonal random trend, general seasonal, general first order autoregressive seasonal, seasonally differentiated first order autoregressive and Holt-Winters additive models. After that, youll automatically select autoregressive integrated moving average model with lowest information loss criteria. Later, youll evaluate models forecasting accuracy and information loss criteria. For information loss criteria, youll define Akaike, corrected Akaike and Schwarz Bayesian information loss criteria. Finally, youll assess lowest information loss criteria autoregressive integrated moving average model residuals or forecasting errors white noise requirement through Ljung-Box lagged autocorrelation test."
Price: 24.99

"Stock Technical Analysis with R"

"Full Course Content Last Update 12/2017Learn stock technical analysis through a practical course with R statistical software using S&P 500 Index ETF historical data for back-testing. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do research as experienced investor. All of this while referencing best practitioners in the field.Become a Stock Technical Analysis Expert in this Practical Course with RRead or download S&P 500 Index ETF prices data and perform technical analysis operations by installing related packages and running script code on RStudio IDE.Compute lagging stock technical indicators or overlays such as moving averages, Bollinger bands, parabolic stop and reverse.Calculate leading stock technical indicators or oscillators such as average directional movement index, commodity channel index, moving averages convergence/divergence, rate of change, relative strength index, stochastic momentum index and Williams %R.Determine single technical indicator based stock trading opportunities through price, double, bands, centerline and signal crossovers.Define multiple technical indicators based stock trading occasions through price crossovers confirmed by bands crossovers.Outline long-only stock trading strategies based on single or multiple technical indicators trading openings.Assess stock trading strategies performance by comparing their annualized return, standard deviation and Sharpe ratio against buy and hold benchmark.Become a Stock Technical Analysis Expert and Put Your Knowledge in PracticeLearning stock technical analysis is indispensable for finance careers in areas such as equity research and equity trading. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors stock technical trading research and development.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500 Index ETF prices historical data for back-testing to achieve greater effectiveness.Content and OverviewThis practical course contains 46 lectures and 7 hours of content. Its designed for all stock technical analysis knowledge levels and a basic understanding of R statistical software is useful but not required.At first, youll learn how to read or download S&P 500 Index ETF prices historical data to perform technical analysis operations by installing related packages and running script code on RStudio IDE.Next, youll calculate lagging stock technical indicators such as simple moving averages (SMA), exponential moving averages (EMA), Bollinger bands (BB), parabolic stop and reverse (SAR). After that, youll compute leading stock technical indicators such as average directional movement index (ADX), commodity channel index (CCI), moving averages convergence/divergence (MACD), rate of change (ROC), relative strength index (RSI), stochastic momentum index (SMI) and Williams %R.Then, youll define single technical indicator based stock trading openings through price, double, bands, centerline and signal crossovers. Next, youll determine multiple technical indicators based trading opportunities through price crossovers which need to be confirmed by second technical indicator band crossover. Later, youll give shape to long-only stock trading strategies using single or multiple technical indicators trading occasions.Finally, youll evaluate stock trading strategies performance with buy and hold as initial benchmark and comparing their annualized return for performance, annualized standard deviation for volatility or risk and annualized Sharpe ratio for risk adjusted return."
Price: 24.99

"Stock Technical Analysis with Python"

"Full Course Content Last Update 06/2017Section 1 Content Last Update 04/2020Learn stock technical analysis through a practical course with Python programming language using S&P 500 Index ETF historical data for back-testing. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do research as experienced investor. All of this while referencing best practitioners in the field.Become a Stock Technical Analysis Expert in this Practical Course with PythonRead or download S&P 500 Index ETF prices data and perform technical analysis operations by installing related packages and running code on Python IDE.Compute lagging stock technical indicators or overlays such as moving averages, Bollinger bands, parabolic stop and reverse.Calculate leading stock technical indicators or oscillators such as average directional movement index, commodity channel index, moving averages convergence/divergence, rate of change, relative strength index, stochastic oscillator and Williams %R. Determine single technical indicator based stock trading opportunities through price, double, bands, centerline and signal crossovers.Define multiple technical indicators based stock trading occasions through price crossovers confirmed by bands crossovers.Outline long (buy) or short (sell) stock trading strategies based on single or multiple technical indicators trading openings.Evaluate stock trading strategies performances by comparing them against buy and hold benchmark.Become a Stock Technical Analysis Expert and Put Your Knowledge in PracticeLearning stock technical analysis is indispensable for finance careers in areas such as equity research and equity trading. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors stock technical trading research and development.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500 Index ETF prices historical data for back-testing to achieve greater effectiveness.Content and OverviewThis practical course contains 45 lectures and 8.5 hours of content. Its designed for all stock technical analysis knowledge levels and a basic understanding of Python programming language is useful but not required.At first, youll learn how to read or download S&P 500 Index ETF prices historical data to perform technical analysis operations by installing related packages and running code on Python IDE. Next, youll calculate lagging stock technical indicators such as simple moving averages (SMA), exponential moving averages (EMA), Bollinger bands (BB), parabolic stop and reverse (SAR). After that, youll compute leading stock technical indicators such as average directional movement index (ADX), commodity channel index (CCI), moving averages convergence/divergence (MACD), rate of change (ROC), relative strength index (RSI), stochastic oscillator (Full STO) and Williams %R.Then, youll define single technical indicator based stock trading openings through price, double, bands and signal crossovers. Next, youll determine multiple technical indicators based trading opportunities through price crossovers which need to be confirmed by second technical indicator band crossover. Later, youll give shape to stock trading strategies which are long (buying) or short (selling) using single or multiple technical indicators trading occasions.Finally, youll evaluate stock trading strategies performance with buy and hold as initial benchmark and comparing their annualized return for performance, annualized standard deviation for volatility or risk and annualized Sharpe ratio for risk adjusted return."
Price: 24.99

"Stock Technical Analysis with Excel"

"Full Course Content Last Update 06/2019Learn stock technical analysis through a practical course with Microsoft Excel using S&P 500 Index ETF historical data for back-testing. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do research as experienced investor. All of this while referencing best practitioners in the field.Become a Stock Technical Analysis Expert in this Practical Course with ExcelCompute lagging stock technical indicators or overlays such as moving averages, Bollinger bands, parabolic stop and reverse.Calculate leading stock technical indicators or oscillators such as average directional movement index, commodity channel index, moving averages convergence/divergence, rate of change, relative strength index, stochastic momentum index, stochastic oscillator and Williams %R. Determine single technical indicator based stock trading opportunities through price, double, bands, centerline and signal crossovers.Define multiple technical indicators based stock trading occasions through price crossovers confirmed by bands crossovers.Outline long-only stock trading strategies based on single or multiple technical indicators trading openings.Assess stock trading strategies performance by comparing their annualized return, standard deviation and Sharpe ratio against buy and hold benchmark.Become a Stock Technical Analysis Expert and Put Your Knowledge in PracticeLearning stock technical analysis is indispensable for finance careers in areas such as equity research and equity trading. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors stock technical trading research and development.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500 Index ETF prices historical data for back-testing to achieve greater effectiveness.Content and OverviewThis practical course contains 43 lectures and 8 hours of content. Its designed for all stock technical analysis knowledge levels and a basic understanding of Microsoft Excel is useful but not required.At first, youll learn how to perform stock technical analysis operations using Microsoft Excel built-in functions and array calculations. Next, youll calculate lagging stock technical indicators such as simple moving averages, exponential moving averages, Bollinger bands, parabolic stop and reverse. After that, youll compute leading stock technical indicators such as average directional movement index, commodity channel index, moving averages convergence/divergence, rate of change, relative strength index, stochastic momentum index, stochastic oscillator and Williams %R.Then, youll define single technical indicator based stock trading openings through price, double, bands, centerline and signal crossovers. Next, youll determine multiple technical indicators based trading opportunities through price crossovers which need to be confirmed by second technical indicator band crossover. Later, youll give shape to long-only stock trading strategies using single or multiple technical indicators trading occasions.Finally, youll evaluate stock trading strategies performance with buy and hold as initial benchmark and comparing their annualized return for performance, annualized standard deviation for volatility or risk and annualized Sharpe ratio for risk adjusted return."
Price: 24.99

"Forecasting Models with Python"

"Full Course Content Last Update 06/2018Learn forecasting models through a practical course with Python programming language using S&P 500 Index ETF prices historical data. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your business forecasting research. All of this while exploring the wisdom of best academics and practitioners in the field.Become a Forecasting Models Expert in this Practical Course with PythonRead S&P 500 Index ETF prices data and perform forecasting models operations by installing related packages and running code on Python PyCharm IDE.Estimate simple forecasting methods such as arithmetic mean, random walk, seasonal random walk and random walk with drift.Evaluate simple forecasting methods forecasting accuracy through mean absolute error and root mean squared error scale-dependent metrics.Approximate simple moving averages and exponential smoothing methods with no trend or seasonal patterns such as Brown simple exponential smoothing method.Estimate exponential smoothing methods with only trend patterns such as Holt linear trend, exponential trend, Gardner additive damped trend and Taylor multiplicative damped trend methods.Approximate exponential smoothing methods with trend and seasonal patters such as Holt-Winters additive seasonality and Holt-Winters multiplicative seasonality methods.Select exponential smoothing method with lowest Akaike and Schwarz Bayesian information loss criteria.Asses simple moving average and exponential smoothing methods forecasting accuracy through mean absolute error and root mean squared error scale-dependent metrics.Identify Box-Jenkins autoregressive integrated moving average model integration order through level and differentiated first order trend stationary time series augmented Dickey-Fuller unit root test.Recognize autoregressive integrated moving average model autoregressive and moving average orders through autocorrelation and partial autocorrelation functions.Estimate non-seasonal autoregressive integrated moving average models such as random walk with drift, differentiated first order autoregressive, Brown simple exponential smoothing, Holt linear trend and Gardner additive damped trend models.Approximate seasonal autoregressive integrated moving average models such as seasonal random walk with drift, seasonally differentiated first order autoregressive and Holt-Winters additive seasonality models.Choose autoregressive integrated moving average model with lowest Akaike and Schwarz Bayesian information loss criteria.Evaluate autoregressive integrated moving average models forecasting accuracy through mean absolute error and root mean squared error scale-dependent metrics.Assess highest forecasting accuracy autoregressive integrated moving average model residuals or forecasting errors white noise requirement through Ljung-Box lagged autocorrelation test.Become a Forecasting Models Expert and Put Your Knowledge in PracticeLearning forecasting models is indispensable for business or financial data science applications in areas such as sales and financial forecasting, inventory optimization, demand and operations planning, and cash flow management. It is also essential for academic careers in data science, applied statistics, operations research, economics, econometrics and quantitative finance. And its necessary for business forecasting research.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500 Index ETF prices historical data for forecast modelling to achieve greater effectiveness.Content and OverviewThis practical course contains 41 lectures and 5.5 hours of content. Its designed for all forecasting models knowledge levels and a basic understanding of Python programming language is useful but not required.At first, youll learn how to read S&P 500 Index ETF prices historical data to perform forecasting models operations by installing related packages and running code on Python PyCharm IDE.Then, youll define simple forecasting methods such as arithmetic mean, random walk, seasonal random walk and random walk with drift. Next, youll evaluate simple methods forecasting accuracy through mean absolute error and root mean squared error scale-dependent metrics.Next, youll define simple moving averages and exponential smoothing methods. For exponential smoothing methods with no trend or seasonal patterns, youll define Brown simple exponential smoothing method. For exponential smoothing methods with only trend patterns, youll define Holt linear trend, exponential trend, Gardner additive damped trend and Taylor multiplicative damped trend methods. For exponential smoothing methods with trend and seasonal patterns, youll define Holt-Winters additive seasonality and Holt-Winters multiplicative seasonality methods. After that, youll select exponential smoothing method with lowest Akaike and Schwarz Bayesian information loss criteria. Later, youll evaluate simple moving average and exponential smoothing methods forecasting accuracy through mean absolute error and root mean squared error scale-dependent metrics.After that, youll define Box-Jenkins autoregressive integrated moving average models. Then, youll identify autoregressive integrated moving average model integration order through level and differentiated time series first order trend stationary augmented Dickey-Fuller unit root test. Next, youll identify autoregressive integrated moving average model autoregressive and moving average orders through autocorrelation and partial autocorrelation functions. For non-seasonal autoregressive integrated moving average models, youll define random walk with drift, differentiated first order autoregressive, Brown simple exponential smoothing, Holt linear trend and Gardner additive damped trend models. For seasonal autoregressive integrated moving average models, youll define seasonal random walk with drift, seasonally differentiated first order autoregressive and Holt-Winters additive seasonality models. After that, youll select autoregressive integrated moving average model with lowest Akaike and Schwarz Bayesian information loss criteria. Later, youll evaluate models forecasting accuracy through mean absolute error and root mean squared error scale-dependent metrics. Finally, youll assess highest forecasting accuracy autoregressive integrated moving average model residuals or forecasting errors white noise requirement through Ljung-Box lagged autocorrelation test."
Price: 24.99

"Investment Portfolio Analysis with R"

"Full Course Content Last Update 01/2018Learn investment portfolio analysis through a practical course with R statistical software using index replicating ETFs and Mutual Funds historical data for back-testing. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your research as experienced investor. All of this while exploring the wisdom of Nobel Prize winners and best practitioners in the field.Become an Investment Portfolio Analysis Expert in this Practical Course with RRead or download main asset classes benchmark indexes replicating funds data to perform investment portfolio analysis operations by installing related packages and running script code on RStudio IDE.Compare main asset classes benchmark indexes replicating funds returns and risks tradeoffs for cash, bonds, stocks, commodities, real estate and currencies.Estimate portfolio expected returns, historical and market participants implied volatility.Approximate portfolio expected excess returns using capital asset pricing model (CAPM), Fama-French-Carhart factors model and arbitrage pricing theory model (APT).Hedge portfolio systematic risk through options trading strategies benchmark indexes replicating funds.Evaluate hedge fund index performance and assess portfolio returns and risks amplification through leverage.Calculate portfolio performance metrics such as Sharpe, Treynor, Sortino, and Kelly ratios.Estimate benchmark global portfolios returns from periodically rebalanced equal weighted asset allocations and those from well-known investment managers.Optimize global portfolios asset allocation weights for mean maximization, standard deviation minimization, mean maximization and standard deviation minimization, mean maximization and value at risk minimization objectives within training range based on Markowitz portfolio theory.Approximate global portfolios returns from periodically rebalanced optimized asset allocations within testing range and compare them with equal weighted and well-known investment managers benchmark portfolios.Evaluate global portfolios performance through global risk factors model and estimate their expected return, expected excess return and expected return contribution from global risk factors exposure while assessing investment costs impact on portfolio performance.Become an Investment Portfolio Analysis Expert and Put Your Knowledge in PracticeLearning investment portfolio analysis is indispensable for finance careers in areas such as asset management, private wealth management, and risk management within institutional investors represented by banks, insurance companies, pension funds, hedge funds, investment advisors, endowments and mutual funds. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors optimized asset allocation strategies research and development.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using index replicating funds historical data for back-testing and to achieve greater effectiveness.Content and OverviewThis practical course contains 44 lectures and 6.5 hours of content. Its designed for all investment portfolio analysis knowledge levels and a basic understanding of R statistical software is useful but not required.At first, youll learn how to read or download index replicating funds historical data to perform investment portfolio analysis operations by installing related packages and running script code on RStudio IDE.Then, youll define main asset classes by comparing their benchmark indexes replicating funds returns and risks tradeoffs. After that, youll segment main asset classes into traditional and alternative ones. For traditional asset classes, youll define cash and cash equivalents, fixed income or bonds and equities or stocks. Regarding cash and cash equivalents traditional asset class, youll use U.S. total money market benchmark index replicating fund. Regarding cash and cash equivalents traditional asset class, youll use U.S. total money market benchmark index replicating fund is used. Regarding fixed income or bonds traditional asset class, U.S. total bond market, U.S. short term bond market, U.S. long term bond market and international total bond market benchmark indexes replicating funds. Regarding equities or stocks traditional asset class, youll use U.S. total stock market, U.S. large cap stock market, U.S. small cap stock market, U.S. small cap growth stock market, U.S. small cap value stock market, international total stock market, international developed stock market and international emerging stock market benchmark indexes replicating funds. For alternative asset classes, youll define commodities, real estate and currencies or foreign exchange. Regarding commodities alternative asset class, youll use oil and gold prices benchmark indexes replicating funds. Regarding real estate alternative asset class, youll use U.S. real estate investment trust market benchmark index replicating fund. Regarding currencies or foreign exchange alternative asset class, youll use U.S. dollar major currencies benchmark index replicating fund.Next, youll define returns and risks using U.S. large cap stocks market benchmark index replicating fund. After that, youll calculate expected returns through historical returns mean and media. Then, youll estimate risks through historical returns standard deviation, mean absolute deviation and market participants implied volatility. Later, youll approximate portfolio expected excess returns through capital asset pricing model (CAPM), Fama-French-Carhart factors model and arbitrage pricing theory model (APT). Next, youll hedge portfolio systematic risk through options trading strategies and evaluate hedge fund index performance together with the assessment of returns and risks amplification through portfolio leverage.After that, youll define portfolio optimization through global assets allocation. Next, youll calculate Sharpe ratio, Treynor ratio, Sortino ratio and Kelly ratio portfolio performance metrics. Then, youll estimate benchmark global portfolios returns from periodically rebalanced equal weighted asset allocations and those from well-known investment managers. Later, youll optimize global asset allocation weights within training range for mean maximization, standard deviation minimization, mean maximization and standard deviation minimization, mean maximization and value at risk minimization objectives based on Markowitz portfolio theory. After that, youll calculate global portfolio returns within testing range using previously optimized periodically rebalance asset allocation weights and compared with equal weighted and well-known investment managers benchmark portfolios.Later, youll evaluate optimized portfolios performance through global risk factors model. After that, youll estimate optimized portfolios expected returns, expected excess returns and global risk factors exposure returns contribution. Finally, youll assess investment costs impact on portfolio performance."
Price: 24.99

"Investment Portfolio Analysis with Python"

"Full Course Content Last Update 03/2018Learn investment portfolio analysis through a practical course with Python programming language using index replicating ETFs and Mutual Funds historical data for back-testing. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your research as experienced investor. All of this while exploring the wisdom of Nobel Prize winners and best practitioners in the field.Become an Investment Portfolio Analysis Expert in this Practical Course with PythonRead or download main asset classes benchmark indexes replicating funds data to perform investment portfolio analysis operations by installing related packages and running code on Python IDE.Compare main asset classes benchmark indexes replicating funds returns and risks tradeoffs for cash, bonds, stocks, commodities, real estate and currencies.Estimate portfolio expected returns, historical and market participants implied volatility.Approximate portfolio expected excess returns using capital asset pricing model (CAPM), Fama-French-Carhart factors model and arbitrage pricing theory model (APT).Hedge portfolio systematic risk through options trading strategies benchmark indexes replicating funds.Evaluate hedge fund index performance and assess portfolio returns and risks amplification through leverage.Calculate portfolio performance metrics such as Sharpe, Treynor, Sortino, and Kelly ratios.Estimate benchmark global portfolios returns from periodically rebalanced equal weighted asset allocations and those from well-known investment managers.Optimize global portfolios asset allocation weights for mean maximization, standard deviation minimization, mean maximization and standard deviation minimization, mean maximization and value at risk minimization objectives within training range based on Markowitz portfolio theory.Approximate global portfolios returns from periodically rebalanced optimized asset allocations within testing range and compare them with equal weighted and well-known investment managers benchmark portfolios.Evaluate global portfolios performance through global risk factors model and estimate their expected return, expected excess return and expected return contribution from global risk factors exposure while assessing investment costs impact on portfolio performance.Become an Investment Portfolio Analysis Expert and Put Your Knowledge in PracticeLearning investment portfolio analysis is indispensable for finance careers in areas such as asset management, private wealth management, and risk management within institutional investors represented by banks, insurance companies, pension funds, hedge funds, investment advisors, endowments and mutual funds. It is also essential for academic careers in quantitative finance. And it is necessary for experienced investors optimized asset allocation strategies research and development.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using index replicating funds historical data for back-testing and to achieve greater effectiveness.Content and OverviewThis practical course contains 44 lectures and 7.5 hours of content. Its designed for all investment portfolio analysis knowledge levels and a basic understanding of Python programming language is useful but not required.At first, youll learn how to read or download index replicating funds historical data to perform investment portfolio analysis operations by installing related packages and running code on Python IDE.Then, youll define main asset classes by comparing their benchmark indexes replicating funds returns and risks tradeoffs. After that, youll segment main asset classes into traditional and alternative ones. For traditional asset classes, youll define cash and cash equivalents, fixed income or bonds and equities or stocks. Regarding cash and cash equivalents traditional asset class, youll use U.S. total money market benchmark index replicating fund. Regarding cash and cash equivalents traditional asset class, youll use U.S. total money market benchmark index replicating fund is used. Regarding fixed income or bonds traditional asset class, U.S. total bond market, U.S. short term bond market, U.S. long term bond market and international total bond market benchmark indexes replicating funds. Regarding equities or stocks traditional asset class, youll use U.S. total stock market, U.S. large cap stock market, U.S. small cap stock market, U.S. small cap growth stock market, U.S. small cap value stock market, international total stock market, international developed stock market and international emerging stock market benchmark indexes replicating funds. For alternative asset classes, youll define commodities, real estate and currencies or foreign exchange. Regarding commodities alternative asset class, youll use oil and gold prices benchmark indexes replicating funds. Regarding real estate alternative asset class, youll use U.S. real estate investment trust market benchmark index replicating fund. Regarding currencies or foreign exchange alternative asset class, youll use U.S. dollar major currencies benchmark index replicating fund.Next, youll define returns and risks using U.S. large cap stocks market benchmark index replicating fund. After that, youll calculate expected returns through historical returns mean and media. Then, youll estimate risks through historical returns standard deviation, mean absolute deviation and market participants implied volatility. Later, youll approximate portfolio expected excess returns through capital asset pricing model (CAPM), Fama-French-Carhart factors model and arbitrage pricing theory model (APT). Next, youll hedge portfolio systematic risk through options trading strategies and evaluate hedge fund index performance together with the assessment of returns and risks amplification through portfolio leverage.After that, youll define portfolio optimization through global assets allocation. Next, youll calculate Sharpe ratio, Treynor ratio, Sortino ratio and Kelly ratio portfolio performance metrics. Then, youll estimate benchmark global portfolios returns from periodically rebalanced equal weighted asset allocations and those from well-known investment managers. Later, youll optimize global asset allocation weights within training range for mean maximization, standard deviation minimization, mean maximization and standard deviation minimization, mean maximization and value at risk minimization objectives based on Markowitz portfolio theory. After that, youll calculate global portfolio returns within testing range using previously optimized periodically rebalance asset allocation weights and compared with equal weighted and well-known investment managers benchmark portfolios.Later, youll evaluate optimized portfolios performance through global risk factors model. After that, youll estimate optimized portfolios expected returns, expected excess returns and global risk factors exposure returns contribution. Finally, youll assess investment costs impact on portfolio performance."
Price: 24.99

"Cisco CCNA 200-301 - Practicas de configuracion en espaol"

"Eres un profesional dentro del rea de las tecnologas de la informacin y quieres Certificarte en Redes Cisco?Buscando un curso que no solo tenga teora si no que tambin puedas realizar practicas para afianzar tus conocimientos?Cansado de no entender cmo funcionan los protocolos de capa 2 y 3, adems de routing y todo lo que conlleva a la configuracin de equipos Cisco?Bienvenido al curso de ""Cisco CCNA 200-301 - Practica de configuracin en espaol"", curso que te preparar para obtener los conocimientos bsicos y avanzados para la preparacin del examen ""Cisco CCNA 200-301"" (Ex CCNA R&S 200-125)La certificacin Cisco CCNA es una de las importantes en la industria de las tecnologas de la informacin, que te abrir numerosas puertas de oportunidades en el mundo laboral. En este curso podrs realizar prcticas de configuracin de dispositivos Cisco, por medio del software de simulacin de redes llamado ""Cisco Packet Tracer"" y enfrentar as de mejor manera el examen de certificacin de Cisco.Este curso se enfoca en la explicacin de todos los tpicos que se preguntan en el examen CCNA 200-301 y qu practicaras de manera simultnea en cada clase.Todo el material de estudio, est pensado para la certificacin Cisco, como adems de su aplicacin en el trabajo diario de tu vida laboral, como la configuracin de Switch y Router Cisco.Este curso es de Gran Utilidad para la certificacin Cisco CCNA, que se preocupa de la practica de todas las clases para un mayor entendimiento y que sea de forma fcil y amena. Este curso es complementario para a los cursos oficiales de Cisco, y pretende ser una ayuda para la comprensin por medio de laboratorios asociado a cada concepto que se va aprendiendoNo esperes ms y empecemos a aprender juntos desde hoy mismo! Aprendamos Practicando!"
Price: 34.99

"Kingdom Glory: Release the Presence of God as a Christian"

"Hello, Welcome to the Kingdom Glory training series which is a highly interactive course that will propel you into the Glory and train you how to release the Kingdom of God in an unprecedented fashion! In these sessions there are three main themes throughout the course: Learning your Authority, Learning your Identity and Learning the Heart of God. Along with these teachings you will also have powerful activation's to put into practice what you have just learned to make it a part of your life. Also, there is a session that is a complete Bethel Treasure Hunt training where you will be trained in the gifts of the Spirit with an actual group to learn how to release God into any situation in life so that revival becomes a normal lifestyle!About the Author: Alexander Logia is a Bethel School of Supernatural Ministry graduate and is currently a ministry Associate with Kevin Dedmon and Jason Chin. Recently married, Alexander lives in Redding as an overseer for Treasure Hunts and Firestarters at Bethel Church. He has been doing crusades throughout Africa and Philippines with a passion to see worldwide harvest through the preaching of the gospel in a demonstration of the Holy Spirit and power. Thousands of people have been healed, saved and delivered in his ministry in various nations around the world-Fund Revival Around the World: As you join this training series you will also be sowing into the ministry and helping fund crusades and missions work in various nations. We ultimately want to take this glorious gospel to all creation and see Jesus get His full reward! Thank you for your support and we pray that you are abundantly blessed !"
Price: 24.99

"Activate Your Miracle Consciousness"

"You may have been trying for a really long time to find the place within where miracles become an everyday occurrence so you can step into your greatest potential and access all of your longest held dreams, desires, and wishes.I have learned through over 20 years of research, study, and practice how to turn my life into a life where miracles surround me every day. I have learned how to tap into my own inner abundance to create what I call Miracle Consciousness.I would love to share with you what I have learned so you can turn your life into one that generates miracles everyday.In this course you will learn how to activate your Miracle Consciousness in an easy to follow step-by-step process. Once you understand how to embody your own Miracle Consciousness, you will never look outside of yourself again to bring anything into your life. You will manifest things with ease and grace and be living a joyful life always. You Have the Power to Tap Into Your Inner Reserves of Abundance""This course is taught in an easy to understand step-by-step video format that will guide you to the place within that all your miracles stem from.Create a Magical Life with Ease""Manifest things you have been wanting for a really long timeStep into your greatest potentialLive in freedom, passion, happiness, and joy everydayTap into your inner abundanceMake your outer life reflect your new inner stateContinue building the energy of your creationMagnetize with your heart energyMove through uncomfortable emotions with easeHave an inner foundation on which you can always rely"
Price: 19.99

"Spiritual Awakening Mastery Course"

"The Spiritual Awakening Mastery Course is designed to take you step-by-step through your spiritual awakening process. If you are experiencing a spiritual awakening, you know it can be challenging. In this course you will learn how to move through difficulties with ease. If you have an awareness of what is going on, then you have the ability to change your circumstances into what you are wanting. This course has 8 modules and over 3.5 hours of instruction. In this course you will learn: Why you are awakeningStages of a spiritual awakeningSymptoms of an awakening and how to healYour spiritual giftsHandling practical mattersDivine relationshipsLiving your missionManifest with Ease This course will teach you to live your truth and follow your heart. You are discovering yourself on a deep inner level and are transforming out of old patterning and beliefs. Loving yourself is an important part of the spiritual awakening journey. You will learn through this course how to love you and treat yourself gently and with care always. Be everything that you are and love yourself deeply. Allow yourself to play and be in a state of wonder and excitement every day, that is what this spiritual journey is taking you into. You must take this course if you are experiencing a spiritual awakening and need guidance on how you can get through it while being happy, centered, and empowered."
Price: 19.99

Previous Next

Video Network

Music

News