| "Linguagens do Zero" |
| "Muita gente diz que o ENEM no cobra gramtica, mas, independentemente de a cobrana no ser direta, para fazer uma boa prova de Linguagens e uma redao nota mil, seu conhecimento nessa parte fundamental. Alm disso, muitos vestibulares possuem questes de gramtica, e outros tipos de produo textual que no sejam a dissertao-argumentativa. Pensando nisso, o QG do ENEM, plataforma de cursos online, preparou o curso Linguagens do Zero com a professora Gab Jardim. So aulas que abordam desde tipologias textuais e noes sintticas at semntica. + Videoaulas de Linguagens bsica+ Aulas voltadas para o ENEM+ Foco nos assuntos mais importantes do Ensino Mdio"
Price: 54.99 |
| "Qumica Premium 2019" |
| "Qumica difcil, n? Mas voc pode e vai se dar muito bem no ENEM e tirar um noto em Qumica. Seu caso especfica? Ento, vem com o QG e o professores Helton Moreira, Joo Carlos, Alan Belvino e Roberto Mazzei. A melhor forma de entender Qumica por meio de exerccios. Neste curso, os professores focam nas resolues de questes complexas do ENEM e de vestibulares de todo o pas. RECURSOS E BENEFCIOS+ Resoluo de Exerccios+ Foco nos assuntos mais importantes para os vestibulares especficos e para o ENEM 2019"
Price: 69.99 |
| "Fsica Premium 2019" |
| "Quer se dar muito bem na prova de Fsica do ENEM? Ou vai fazer prova especfica de Fsica? Ento, vem com o QG. Preparamos esse curso online de Fsica com tudo que voc precisa saber para se dar bem no Exame Nacional do Ensino Mdio e nos vestibulares especficos que rolam pelo pas! So vdeoaulas com muita teoria, resolues de exerccios e mensagem direta ao monitor.,+ Aulas ministradas pelo professores Fabrcio Pinheiro e Rafael Cafezeiro+ Foco nos assuntos mais importantes para os vestibulares especficos e para o ENEM 2019"
Price: 69.99 |
| "Matemtica Premium" |
| "Quer se dar muito bem na prova de Matemtica do ENEM? Ou vai fazer prova especfica de Matemtica? Ento, vem com o QG e o professor Sandro Davison. Uma boa nota na prova de Matemtica do ENEM para quem almeja carreiras em exatas, pode fazer toda a diferena! E nos vestibulares especficos ento... nem se fala! Pensando nisso, preparamos esse curso online de Matemtica com tudo que voc precisa saber para se dar bem no Exame Nacional do Ensino Mdio e nos vestibulares que rolam pelo pas! So vdeoaulas com muita teoria, resolues de exerccios de especificas e foco nos assuntos mais importantes para os vestibulares especficos e para o ENEM 2019."
Price: 69.99 |
| "Biologia Premium" |
| "Quer se dar muito bem na prova de Biologia do ENEM? Vai fazer prova especfica de Biologia? Ento, vem com o QG e os professores Rafael Cafezeiro e Fabrcio Pinheiro. Preparamos um curso online de Biologia unindo assuntos do dia a dia com o conceito da matria. So vdeoaulas com muita teoria, resolues de exerccios e mensagem direta ao monitor."
Price: 54.99 |
| "Fsica do Zero" |
| "Quer dominar de uma vez por todas a Fsica do Ensino Mdio? Ento, vem com o QG do Enem. O bom conhecimento da matria, desde o bsico, extremamente fundamental para um bom resultado na prova de Cincias da Natureza do ENEM. Preparamos um curso online com aulas de tudo que voc precisa saber para se dar bem no Exame Nacional do Ensino Mdio!RECURSOS E BENEFCIOSVideoaulas de Fsica bsicaAulas voltadas para o ENEMFoco nos assuntos mais importantes do Ensino Mdio"
Price: 39.99 |
| "- Youtube complete Course" |
| ", , , . :1. 2. Creator Studio3. 4. 5. 6. 7. 8. 9. 10. 11."
Price: 99.99 |
| "Criando WebSites PHP sem saber programar usando o PHPRunner" |
| "O objetivo do curso instruir sobre como criar um site internet com recursos avanados sem que seja necessrio ao aluno conhecimentos sobre linguagem de programao , para isto iremos utilizar a ferramenta PHPRunner.O software permite:Customizao do layout e dos estilosCriar pginas apenas de tabelas de banco de dados e criar relacionamento entre elasCriar pginas PHP sem a necessidade de conhecimento da linguagemExecutar o Website sem a necessidade de instalar servidorCriar executvel que roda o website podendo ser distribudo inclusive com um instaladorDefinir os tipos dos campos dos formulriosCriao de site totalmente responsivoEstaremos demonstrando passo a passo estas funcionalidades."
Price: 39.99 |
| "Controles DevExpress para Asp.Net WebForms" |
| "A DevExpress uma empresa que desenvolve e comercializa componentes de alta qualidade, seus componentes possuem inmeras propriedades e recursos que estendem as funcionalidades das plataformas de desenvolvimento, atendendo as necessidades que os desenvolvedores precisam para superar as expectativas dos clientes. Costumamos dizer que os componentes DevExpress reinventam a programao Asp.NET no Microsoft Visual Studio.Neste curso estaremos apresentando detalhadamente muitos desses controles, e sua implementao.Visite a pgina de demonstrao dos controles Asp.Net no site da DevExpress"
Price: 39.99 |
| "Autenticao em redes sociais com o Firebase UI e Firestore" |
| "Neste minicurso , vamos aprender como colocar autenticao (Login) em redes sociais (como o FaceBook, Google, Email, Autenticao por notificao por telefone e outros) em um site usando o Google Firebase e resgatar dados dos usurios autenticados e armazen-los no Google Firestore. Ao final, sero listados todos os usurios cadastrados utilizando os recursos de Realtime do Firestore. Utilizamos o Firebase UI WEB para implentar a tela de login."
Price: 39.99 |
| "Rest Api com o Adonis JS" |
| "O AdonisJS um FrameWork JavaScript utilizado para criar aplicaes Web e Apis Rest, a vantagem do uso que fica mais fcil consumir a Api em aplicaes que utilizam Node.js (como o React e o Ionic) , assim como o AdonisJS, no sendo necessrio o uso de outra tecnologia. muito semelhante ao Php Laravel, na verdade tipo um clone, portanto , quem est habituado a usar Laravel no ter dificuldade de aprender."
Price: 39.99 |
| "Consumindo uma Rest Api com o Ionic 4" |
| "Neste curso, vamos demonstrar como utilizar o Ionic 4 para desenvolver um blog ( Usurios e Postagens) , com dados recebidos e enviados a partir de uma Rest Api, tambm conheceremos algumas funcionalidades da nova verso do Ionic, Abaixo , a estrutura da API:UsersGET - http://127.0.0.1:3333/usuariosPOST - http://127.0.0.1:3333/usuarios -> username,email,password,photoPUT - http://127.0.0.1:3333/usuarios/1 -> username,email,password,photoDELETE - http://127.0.0.1:3333/usuarios/1PostagensGET - http://127.0.0.1:3333/postagensPOST - http://127.0.0.1:3333/postagens -> titulo,corpo,imagem,usuarioidPUT - http://127.0.0.1:3333/usuarios/1 -> id,titulo,corpo,imagem,usuarioidDELETE - http://127.0.0.1:3333/postagens/1GET - http://127.0.0.1:3333/postagensusuarios/1"
Price: 39.99 |
| "Criando Rest Api com o Adonis Js e consumindo com o Ionic 4" |
| "O AdonisJS um FrameWork JavaScript utilizado para criar aplicaes Web e Apis Rest, a vantagem do uso que fica mais fcil consumir a Api em aplicaes que utilizam Node.js (como o React e o Ionic) , assim como o AdonisJS, no sendo necessrio o uso de outra tecnologia. muito semelhante ao Php Laravel, na verdade tipo um clone, portanto , quem est habituado a usar Laravel no ter dificuldade de aprender.O Ionic Framework Framework Open Source para desenvolvimento de aplicaes mveis para Android ou IOSNeste curso, vamos criar uma Rest Api (um blog com Usurios e Postagens) com o AdonisJS e utilizar o Ionic 4 para desenvolver uma aplicao com dados recebidos e enviados a partir da Api.Abaixo , a estrutura da API:UsersGET - http://127.0.0.1:3333/usuariosPOST - http://127.0.0.1:3333/usuarios -> username,email,password,photoPUT - http://127.0.0.1:3333/usuarios/1 -> username,email,password,photoDELETE - http://127.0.0.1:3333/usuarios/1PostagensGET - http://127.0.0.1:3333/postagensPOST - http://127.0.0.1:3333/postagens -> titulo,corpo,imagem,usuarioidPUT - http://127.0.0.1:3333/usuarios/1 -> id,titulo,corpo,imagem,usuarioidDELETE - http://127.0.0.1:3333/postagens/1GET - http://127.0.0.1:3333/postagensusuarios/1Tambm conheceremos algumas funcionalidades da nova verso do Ionic 4."
Price: 39.99 |
| "Criando chat estilo WhatsApp com Ionic4 e Firebase Firestore" |
| "Neste curso, vamos ensinar a criar uma app mobile com o Ionic 4 , um chat onde mensagens so mostradas em tempo real (realtime) com recursos parecidos com o Whatsapp , esta uma funcionalidade do banco de dados do Google Firebase/Firestore.Ser utilizado durante o curso os novos recursos da ltima verso do Ionic (4.12), como a utilizao de rotas (Routes) para a navegao entre as pginas, formulrios para insero e atualizao de usurios e mensagens e criao de pginas e componentes.Vamos utilizar o AngularFire , um framework javascript para gerenciamento de dados do Firebase Firestore, necessrios para a conexo ao servio de banco de dados em Realtime do Google, o Firebase Firestore.O cdigo fonte do projeto desenvolvido est disponvel no github, o link para baixar est entre os arquivos do curso."
Price: 39.99 |
| "Wine: Everything You Want to Know, Taught by a Winemaker" |
| "Are you interested in wine, but you're not sure where to start? This course is for you.""Thank you so much for all the work you have put into this course. Very informative.""""I just want to let you know that I appreciate the work you've put into this course and are continuing to put in to it to add to its already bountiful, richness!!! I am learning a lot and know others are too.""""Great intro to wines and the winemaking process.""""I very much enjoyed taking this course, and found it very informative.""""I found this course very informative and the instructor was disarmingly charming while still imparting significant knowledge in viticulture and winemaking. The course modules are succinct, allowing me to watch in bite-sized chunks. Terms were clearly defined, and the language was accurate but not filled with the normal pretentiousness one often finds associated with wine. A definite recommendation for wine newbies, but also for folks who know wine well and want to know more about the vineyard.""This course has 3,987 students in 118 countries and it's growing daily! (Updated 12/14/2019)This is a comprehensive, easy-to-understand course on all aspects of wine. What will we cover?Wine definedA short history of wine and where it came fromVisit a native grapevine in its natural habitatA full year in the vineyard, exploring practices and tasks of vineyard workersHow the heck wine is madeBuilding your confidence in buying the right winesHow the heck to taste it ""properly"" (spoiler alert: however you want)Wine ""lingo"" and how to wade through the jargonHow and where to buy wine on a budgetFrequently asked questions about wine (and if your question isn't not on the list, I'll answer it within 1 day)An interview with a wine retailer covering what to look for in wine storesPrinciples of pairing wine and food (coming soon)A list of recommended wine resources (books, apps, seasonal gift ideas, etc.)How to tell what kind of wines you would or wouldn't like (coming soon)What are the features?Lifetime access. No limits.iPhone, iPad, and Android accessibilityCertificate of CompletionSlides from the course lectures in pdf formatDownload the course to your mobile device: watch and interact while you're on the goYou'll get my personal email for any burning wine questions or recommendations you have for adding content to the course (within a day!)Why take this course?Enhance your enjoyment of wine, in your own unique wayFeel the hubris of wine confidence, and put that wine snob you know to shame =) Just kidding, we're not about shaming hereBut heck, you can become a wine snob yourself, if you'd likeI personally enjoy the term ""wine geek"" much more. In this course we'll teach you how to geek out on wine.How is the course structured?Informative video lectures in the form of talking head clips and some powerpoint slidesTake this course with a friend! Pop that bottle open and park yourself!It's structured to be informative and fun. Even more so with wine. Cheers!Make sure to check out the lectures marked as Free Previews!Enjoy!"
Price: 49.99 |
| "isiXhosa - Everyday Conversation - Beginners (1/3)" |
| "This course is the first of three courses from Beginners to Intermediate to Advanced ConversationalXhosa.TheBeginners course includes 29 videos which can be completed at your own pace, it is completely up to you, you will have lifetime access to this course you may download the pdfs to take with you forever. The aim of this course is to introduce you to the Xhosa language and make you proficient in basic conversational xhosa, it also starts covering important sections in everyday topics.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."
Price: 24.99 |
| "isiXhosa - Everyday Conversation - Intermediate (2/3)" |
| "This course is the second of three courses from Beginners to Intermediate to Advanced ConversationalXhosa.TheIntermediate course includes 25 videos which can be completed at your own pace, it is completely up to you, you will have lifetime access to this course you may download the pdfs to take with you forever. The aim of this course is to build up a students conversational Xhosa and make you proficient in intermediate conversation, it also starts covering important sections in everyday, practical topics.The aim of this course is to not only to upskill a beginner and that the next step in learning Xhosa, but to also be a strong foundation for anyone wanting to take the next step in their journey to mastering the language."
Price: 19.99 |
| "isiXhosa - Everyday Conversation - Advanced (3/3)" |
| "This course is the last of three courses from Beginners to Intermediate to Advanced ConversationalXhosa.TheAdvanced course includes 32 videos which can be completed at your own pace, it is completely up to you, you will have lifetime access to this course you may download the pdfs to take with you forever. The aim of this course is to build up a students conversational Xhosa and make you proficient in advanced conversation, it also covers important sections in everyday, practical topics.The aim of this course is to upskill an intermediate speaker who is taking their next step on their journey to mastering the Xhoas language.This course is also a useful introduction for medical practitioners wanting to better speak with Xhosa patients."
Price: 19.99 |
| "Advanced Trading Analysis with R" |
| "Learn advanced trading analysis through a practical course with R statistical software using S&P 500 Index ETF prices for back-testing. It explores main concepts from proficient 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 Advanced Trading Analysis Expert in this Practical Course with RRead or download S&P 500 Index ETF prices data and perform advanced trading analysis operations by installing related packages and running script code on RStudio IDE.Implement trading strategies through trend-following indicators such as simple moving averages, moving averages convergence-divergence and mean-reversion indicators such as Bollinger bands, relative strength index, statistical arbitrage through z-score.Maximize historical risk adjusted performance by optimizing strategy parameters through an exhaustive grid search of all indicators parameters combinations.Evaluate simulated strategy optimization trials historical risk adjusted performance through annualized return, annualized standard deviation and annualized Sharpe ratio metrics.Minimize strategy parameters optimization overfitting or data snooping through multiple hypothesis testing adjustment.Approximate population mean statistical inference two tails tests multiple probability values.Adjust population mean multiple probability values through family-wise error rate or Bonferroni procedure and false discovery rate or Benjamini-Hochberg procedure.Reduce strategy parameters optimization overfitting or data snooping through individual time series bootstrap hypothesis testing multiple comparison adjustment.Simulate population mean probability distribution through random fixed block re-sampling with replacement.Estimate bootstrap population mean statistical inference percentile confidence interval and two tails test percentile probability value.Correct individual bootstrap population mean probability value multiple comparison through family-wise error rate adjustment.Become an Advanced Trading Analysis Expert and Put Your Knowledge in PracticeLearning advanced trading analysis is indispensable for finance careers in areas such as advanced quantitative research, quantitative development, and quantitative trading mainly within investment banks and hedge funds. It is also essential for academic careers in advanced quantitative finance. And it is necessary for experienced investors advanced quantitative 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 back-testing to achieve greater effectiveness. Content and OverviewThis practical course contains 38 lectures and 5.5 hours of content. Its designed for advanced trading 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 advanced trading analysis operations by installing related packages and running script code on RStudio IDE.Then, youll implement trading strategy based on its category. Next, youll explore main strategy categories such as trend-following and mean-reversion. For trend-following strategy category, youll use indicators such as simple moving averages and moving averages convergence-divergence. For mean-reversion strategy category, youll use indicators such as Bollinger bands, relative strength index and statistical arbitrage through z-score. After that, youll optimize strategy parameters by maximizing historical risk adjusted performance through an exhaustive grid search of all indicators parameters combinations. Later, youll explore main strategy parameters optimization objectives such as net trading profit and loss, maximum drawdown and profit to maximum drawdown metrics. Then, youll do strategy reporting by evaluating optimization trials simulated risk adjusted performance using historical data. Next, youll explore main strategy reporting areas such as performance metrics. For performance metrics, youll use annualized return, annualized standard deviation and annualized Sharpe ratio.After that, youll do multiple hypothesis testing adjustment to reduce historical parameters optimization over-fitting or data snooping. Later, youll define multiple hypothesis testing statistical inference. Then, youll define probability value estimation. For probability value estimation, youll do multiple population mean two tails tests. Next, youll define multiple probability values estimation adjustment. For multiple probability values estimation adjustment, youll do family-wise error rate or Bonferroni procedure and false discovery rate or Benjamini-Hochberg procedure multiple probability values estimations adjustments.Later, youll do individual time series bootstrap hypothesis testing multiple comparison adjustment to reduce historical parameters optimization over-fitting or data snooping. Then, youll do individual time series bootstrap for population mean probability distribution simulation through random fixed block re-samples with replacement. Next, youll define bootstrap parameters estimation statistical inference. After that, youll define point estimation. For point estimation, youll do population mean point estimation. Later, youll define bootstrap confidence intervals estimation. For bootstrap confidence intervals estimation, youll do bootstrap population mean percentile confidence interval estimation. Then, youll define bootstrap hypothesis testing. Next, youll define bootstrap probability value estimation. For bootstrap probability value estimation, youll do bootstrap population mean percentile two tails test. Finally, youll define individual bootstrap probability value estimation multiple comparison adjustment. For individual bootstrap probability value estimation multiple comparison adjustment, youll do family-wise error rate individual probability value estimation multiple comparison adjustment."
Price: 49.99 |
| "Advanced Trading Analysis with Python" |
| "Learn advanced trading analysis through a practical course with Python programming language using S&P 500 Index ETF prices for back-testing. It explores main concepts from proficient 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 Advanced Trading Analysis Expert in this Practical Course with PythonRead or download S&P 500 Index ETF prices data and perform advanced trading analysis operations by installing related packages and running code on Python PyCharm IDE.Implement trading strategies through trend-following indicators such as simple moving averages, moving averages convergence-divergence and mean-reversion indicators such as Bollinger bands, relative strength index, statistical arbitrage through z-score.Maximize historical risk adjusted performance by optimizing strategy parameters through an exhaustive grid search of all indicators parameters combinations.Evaluate simulated strategy optimization trials historical risk adjusted performance through annualized return, annualized standard deviation and annualized Sharpe ratio metrics.Minimize strategy parameters optimization overfitting or data snooping through multiple hypothesis testing adjustment.Approximate population mean statistical inference two tails tests multiple probability values.Adjust population mean multiple probability values through family-wise error rate or Bonferroni procedure and false discovery rate or Benjamini-Hochberg procedure.Reduce strategy parameters optimization overfitting or data snooping through individual time series bootstrap hypothesis testing multiple comparison adjustment.Simulate population mean probability distribution through random fixed block re-sampling with replacement.Estimate bootstrap population mean statistical inference percentile confidence interval and two tails test percentile probability value.Correct individual bootstrap population mean probability value multiple comparison through family-wise error rate adjustment.Become an Advanced Trading Analysis Expert and Put Your Knowledge in PracticeLearning advanced trading analysis is indispensable for finance careers in areas such as advanced quantitative research, quantitative development, and quantitative trading mainly within investment banks and hedge funds. It is also essential for academic careers in advanced quantitative finance. And it is necessary for experienced investors advanced quantitative 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 7 hours of content. Its designed for advanced trading 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 advanced trading analysis operations by installing related packages and running code on Python PyCharm IDE.Then, youll implement trading strategy based on its category. Next, youll explore main strategy categories such as trend-following and mean-reversion. For trend-following strategy category, youll use indicators such as simple moving averages and moving averages convergence-divergence. For mean-reversion strategy category, youll use indicators such as Bollinger bands, relative strength index and statistical arbitrage through z-score. After that, youll optimize strategy parameters by maximizing historical risk adjusted performance through an exhaustive grid search of all indicators parameters combinations. Later, youll explore main strategy parameters optimization objectives such as final portfolio equity metric. Then, youll do strategy reporting by evaluating optimization trials simulated risk adjusted performance using historical data. Next, youll explore main strategy reporting areas such as performance metrics. For performance metrics, youll use annualized return, annualized standard deviation and annualized Sharpe ratio.After that, youll do multiple hypothesis testing adjustment to reduce historical parameters optimization over-fitting or data snooping. Later, youll define multiple hypothesis testing statistical inference. Then, youll define probability value estimation. For probability value estimation, youll do multiple population mean two tails tests. Next, youll define multiple probability values estimation adjustment. For multiple probability values estimation adjustment, youll do family-wise error rate or Bonferroni procedure and false discovery rate or Benjamini-Hochberg procedure multiple probability values estimations adjustments.Later, youll do individual time series bootstrap hypothesis testing multiple comparison adjustment to reduce historical parameters optimization over-fitting or data snooping. Then, youll do individual time series bootstrap for population mean probability distribution simulation through random fixed block re-samples with replacement. Next, youll define bootstrap parameters estimation statistical inference. After that, youll define point estimation. For point estimation, youll do population mean point estimation. Later, youll define bootstrap confidence intervals estimation. For bootstrap confidence intervals estimation, youll do bootstrap population mean percentile confidence interval estimation. Then, youll define bootstrap hypothesis testing. Next, youll define bootstrap probability value estimation. For bootstrap probability value estimation, youll do bootstrap population mean percentile two tails test. Finally, youll define individual bootstrap probability value estimation multiple comparison adjustment. For individual bootstrap probability value estimation multiple comparison adjustment, youll do family-wise error rate individual probability value estimation multiple comparison adjustment."
Price: 49.99 |
| "Advanced Forecasting Models with Excel" |
| "Learn advanced forecasting models through a practical course with Microsoft Excel using S&P 500 Index ETF prices historical data. It explores main concepts from proficient to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your advanced investment management or sales forecasting research. All of this while exploring the wisdom of best academics and practitioners in the field.Become an Advanced Forecasting Models Expert in this Practical Course with ExcelIdentify Box-Jenkins 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.Recognize autoregressive integrated moving average model autoregressive and moving average orders through autocorrelation and partial autocorrelation functions.Estimate autoregressive integrated moving average models such as random walk with drift and differentiated first order autoregressive.Identify seasonal autoregressive integrated moving average model seasonal integration order through level and seasonally differentiated time series first order seasonal stationary deterministic test.Estimate seasonal autoregressive integrated moving average models such as seasonal random walk with drift and seasonally differentiated first order autoregressive.Select non-seasonal or seasonal autoregressive integrated moving average model with lowest Akaike, corrected Akaike and Schwarz Bayesian information loss criteria.Evaluate autoregressive integrated moving average models forecasting accuracy through mean absolute error, root mean squared error scale-dependent and mean absolute percentage error, mean absolute scaled error scale-independent metrics.Identify generalized autoregressive conditional heteroscedasticity modelling need through autoregressive integrated moving average model squared residuals or forecasting errors second order stationary Ljung-Box lagged autocorrelation test.Recognize non-Gaussian generalized autoregressive conditional heteroscedasticity modelling need through autoregressive integrated moving average and generalized autoregressive conditional heteroscedasticity model with highest forecasting accuracy standardized residuals or forecasting errors multiple order stationary Jarque-Bera normality test.Estimate autoregressive integrated moving average models with residuals or forecasting errors assumed as Gaussian or Students t distributed and with Bollerslev simple or Glosten-Jagannathan-Runkle threshold generalized autoregressive conditional heteroscedasticity effects such as random walk with drift and differentiated first order autoregressive.Assess autoregressive integrated moving average model with highest forecasting accuracy standardized residuals or forecasting errors strong white noise modelling requirement.Become an Advanced Forecasting Models Expert and Put Your Knowledge in PracticeLearning advanced forecasting models is indispensable for finance careers in areas such as portfolio management and risk management. It is also essential for academic careers in advanced applied statistics, econometrics and quantitative finance. And its necessary for advanced sales 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 advanced forecast modelling to achieve greater effectiveness. Content and OverviewThis practical course contains 43 lectures and 8 hours of content. Its designed for advanced forecasting models knowledge level and a basic understanding of Microsoft Excel is useful but not required.At first, youll learn how to perform advanced 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 Box-Jenkins autoregressive integrated moving average models. Next, youll identify autoregressive integrated moving average models integration order through level and differentiated time series first order trend stationary deterministic test and Phillips-Perron unit root test. After that, youll identify autoregressive integrated moving average models autoregressive and moving average orders through autocorrelation and partial autocorrelation functions. For autoregressive integrated moving average models, youll define random walk with drift and differentiated first order autoregressive models. Later, youll define seasonal autoregressive integrated moving average models. Then, youll identify seasonal autoregressive integrated moving average models seasonal integration order through level and seasonally differentiated time series first order seasonal stationary deterministic test. Next, youll identify seasonal autoregressive integrated moving average models seasonal autoregressive and seasonal moving average orders through autocorrelation and partial autocorrelation functions. For seasonal autoregressive integrated moving average models, youll define seasonal random walk with drift and seasonally differentiated first order autoregressive. After that, youll select non-seasonal or seasonal autoregressive integrated moving average model with lowest information loss criteria. For information loss criteria, youll define Akaike, corrected Akaike and Schwarz Bayesian information criteria. Later, youll evaluate autoregressive integrated moving average 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.Next, youll define generalized autoregressive conditional heteroscedasticity models. Then, youll identify generalized autoregressive conditional heteroscedasticity modelling need through autoregressive integrated moving average model squared residuals or forecasting errors second order stationary Ljung-Box lagged autocorrelation test. After that, youll identify generalized autoregressive conditional heteroscedasticity model autoregressive and moving average orders through autocorrelation and partial autocorrelation functions. Later, youll define autoregressive integrated moving average models with residuals or forecasting errors assumed as Gaussian or normally distributed and with Bollerslev simple or Glosten-Jagannathan-Runkle threshold generalized autoregressive conditional heteroscedasticity effects. For generalized autoregressive conditional heteroscedasticity models, youll define random walk with drift and differentiated first order autoregressive. Then, youll evaluate generalized autoregressive conditional heteroscedasticity models forecasting accuracy.After that, youll define non-Gaussian generalized autoregressive conditional heteroscedasticity models. Next, youll identify non-Gaussian generalized autoregressive conditional heteroscedasticity modelling need through autoregressive integrated moving average and generalized autoregressive conditional heteroscedasticity model with highest forecasting accuracy standardized residuals or forecasting errors multiple order stationary Jarque-Bera normality test. Then, youll define autoregressive integrated moving average models with residuals or forecasting errors assumed as Students t distributed and with Bollerslev simple or Glosten-Jagannathan-Runkle threshold generalized autoregressive conditional heteroscedasticity effects. Later, youll evaluate non-Gaussian generalized autoregressive conditional heteroscedasticity models forecasting accuracy. Finally, youll evaluate autoregressive integrated moving average and non-Gaussian generalized autoregressive conditional heteroscedasticity model with highest forecasting accuracy standardized residuals or forecasting errors strong white noise modelling requirement."
Price: 49.99 |
| "Advanced Portfolio Analysis with R" |
| "Learn advanced portfolio analysis through a practical course with R statistical software using asset classes benchmark indexes replicating funds historical data for back-testing. It explores main concepts from proficient 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 Advanced Portfolio Analysis Expert in this Practical Course with RRead or download asset classes benchmark indexes replicating funds data to perform advanced portfolio analysis operations by installing related packages and running script code on RStudio IDE.Compare asset classes benchmark indexes replicating funds returns and risks tradeoffs for fixed income or bonds and equities or stocks.Estimate asset classes expected returns through historical annualized returns and risks through historical returns annualized standard deviation. Calculate portfolios Sharpe ratios performance metrics.Estimate benchmark global portfolio returns from periodically rebalanced equal weighted assets allocation.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 benchmark portfolio.Minimize portfolio assets allocation weights optimization back-testing overfitting or data snooping through multiple hypothesis testing adjustment.Approximate two population mean statistical inference two tails tests multiple probability values.Adjust two population mean multiple probability values through family-wise error rate or Bonferroni procedure and false discovery rate or Benjamini-Hochberg procedure.Reduce portfolio assets allocation weights optimization back-testing overfitting or data snooping through individual time series bootstrap hypothesis testing multiple comparison adjustment.Simulate two population mean probability distributions through random fixed block re-sampling with replacement.Estimate two bootstrap population mean statistical inference percentile confidence interval and two tails tests percentile probability values.Correct two individual bootstrap population mean probability values multiple comparisons through family-wise error rate adjustment.Become an Advanced Portfolio Analysis Expert and Put Your Knowledge in PracticeLearning advanced 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 advanced quantitative finance. And it is necessary for experienced investors advanced optimized asset allocation strategies research.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using asset classes benchmark indexes replicating funds historical data for back-testing to achieve greater effectiveness. Content and OverviewThis practical course contains 36 lectures and 4 hours of content. Its designed for advanced 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 asset classes benchmark indexes replicating funds data to perform advanced portfolio analysis operations by installing related packages and running script code on RStudio IDE.Then, youll define asset classes by comparing their benchmark indexes replicating funds returns and risks tradeoffs. For asset classes, youll define fixed income or bonds and equities or stocks. Regarding fixed income or bonds asset class, youll use U.S. total bond market and international total bond market benchmark indexes replicating funds. Regarding equities or stocks asset class, youll use U.S. total stock market and international total stock market benchmark indexes replicating funds. Next, youll define returns and risks. For expected returns, youll calculate historical annualized returns. For risks, youll estimate historical returns annualized standard deviations. Later, youll define portfolio optimization through global assets allocation. After that, youll calculate Sharpe ratios portfolios performance metrics. Then, youll estimate benchmark global portfolio returns from periodically rebalanced equal weighted assets allocation. Next, youll optimize assets 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. Later, youll calculate global portfolio returns within testing range using previously optimized periodically rebalanced assets allocation weights and compare them with equal weighted benchmark portfolio.After that, youll reduce global portfolios assets allocation weights optimization back-testing overfitting or data snooping through multiple hypothesis testing adjustment. Then, youll define multiple hypothesis testing statistical inference. Next, youll define probability value estimation. For probability value estimation, youll do two multiple population mean two tails tests. Later, youll define multiple probability values estimation adjustment. For two multiple probability values estimation adjustment, youll do family-wise error rate or Bonferroni procedure and false discovery rate or Benjamini-Hochberg procedure multiple probability values estimations adjustments.Next, youll reduce global portfolios assets allocation weights optimization back-testing overfitting or data snooping through individual time series bootstrap hypothesis testing multiple comparison adjustment. For time series bootstrap, youll do two population mean probability distribution simulations through random fixed block re-samples with replacement. Then, youll define bootstrap parameters estimation statistical inference. Later, youll define point estimation. For point estimation, youll do two population mean point estimations. After that, youll define bootstrap confidence interval estimation. For bootstrap confidence interval estimation, youll do two bootstrap population mean percentile confidence intervals estimations. Then, youll define bootstrap hypothesis testing. Next, youll define bootstrap probability value estimation. For probability value estimation, youll do two bootstrap population mean percentile two tails tests. Finally, youll define individual bootstrap probability value estimation multiple comparison adjustment. For two individual bootstrap probability value estimations multiple comparison adjustments, youll do family-wise error rate individual probability value estimation multiple comparison adjustments."
Price: 49.99 |
| "Advanced Portfolio Analysis with Python" |
| "Learn advanced portfolio analysis through a practical course with Python programming language using asset classes benchmark indexes replicating funds historical data for back-testing. It explores main concepts from proficient 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 Advanced Portfolio Analysis Expert in this Practical Course with PythonRead or download asset classes benchmark indexes replicating funds data to perform advanced portfolio analysis operations by installing related packages and running code on Python PyCharm IDE.Compare asset classes benchmark indexes replicating funds returns and risks tradeoffs for fixed income or bonds and equities or stocks.Estimate asset classes expected returns through historical annualized returns and risks through historical returns annualized standard deviation. Calculate portfolios Sharpe ratios performance metrics.Estimate benchmark global portfolio returns from periodically rebalanced equal weighted assets allocation.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 benchmark portfolio.Minimize portfolio assets allocation weights optimization back-testing overfitting or data snooping through multiple hypothesis testing adjustment.Approximate two population mean statistical inference two tails tests multiple probability values.Adjust two population mean multiple probability values through family-wise error rate or Bonferroni procedure and false discovery rate or Benjamini-Hochberg procedure.Reduce portfolio assets allocation weights optimization back-testing overfitting or data snooping through individual time series bootstrap hypothesis testing multiple comparison adjustment.Simulate two population mean probability distributions through random fixed block re-sampling with replacement.Estimate two bootstrap population mean statistical inference percentile confidence interval and two tails tests percentile probability values.Correct two individual bootstrap population mean probability values multiple comparisons through family-wise error rate adjustment.Become an Advanced Portfolio Analysis Expert and Put Your Knowledge in PracticeLearning advanced 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 advanced quantitative finance. And it is necessary for experienced investors advanced optimized asset allocation strategies research.But as learning curve can become steep as complexity grows, this course helps by leading you step by step using asset classes benchmark indexes replicating funds historical data for back-testing to achieve greater effectiveness. Content and OverviewThis practical course contains 36 lectures and 4.5 hours of content. Its designed for advanced 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 asset classes benchmark indexes replicating funds data to perform advanced portfolio analysis operations by installing related packages and running code on Python PyCharm IDE.Then, youll define asset classes by comparing their benchmark indexes replicating funds returns and risks tradeoffs. For asset classes, youll define fixed income or bonds and equities or stocks. Regarding fixed income or bonds asset class, youll use U.S. total bond market and international total bond market benchmark indexes replicating funds. Regarding equities or stocks asset class, youll use U.S. total stock market and international total stock market benchmark indexes replicating funds. Next, youll define returns and risks. For expected returns, youll calculate historical annualized returns. For risks, youll estimate historical returns annualized standard deviations. Later, youll define portfolio optimization through global assets allocation. After that, youll calculate Sharpe ratios portfolios performance metrics. Then, youll estimate benchmark global portfolio returns from periodically rebalanced equal weighted assets allocation. Next, youll optimize assets 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. Later, youll calculate global portfolio returns within testing range using previously optimized periodically rebalanced assets allocation weights and compare them with equal weighted benchmark portfolio.After that, youll reduce global portfolios assets allocation weights optimization back-testing overfitting or data snooping through multiple hypothesis testing adjustment. Then, youll define multiple hypothesis testing statistical inference. Next, youll define probability value estimation. For probability value estimation, youll do two multiple population mean two tails tests. Later, youll define multiple probability values estimation adjustment. For two multiple probability values estimation adjustment, youll do family-wise error rate or Bonferroni procedure and false discovery rate or Benjamini-Hochberg procedure multiple probability values estimations adjustments.Next, youll reduce global portfolios assets allocation weights optimization back-testing overfitting or data snooping through individual time series bootstrap hypothesis testing multiple comparison adjustment. For time series bootstrap, youll do two population mean probability distribution simulations through random fixed block re-samples with replacement. Then, youll define bootstrap parameters estimation statistical inference. Later, youll define point estimation. For point estimation, youll do two population mean point estimations. After that, youll define bootstrap confidence interval estimation. For bootstrap confidence interval estimation, youll do two bootstrap population mean percentile confidence intervals estimations. Then, youll define bootstrap hypothesis testing. Next, youll define bootstrap probability value estimation. For probability value estimation, youll do two bootstrap population mean percentile two tails tests. Finally, youll define individual bootstrap probability value estimation multiple comparison adjustment. For two individual bootstrap probability value estimations multiple comparison adjustments, youll do family-wise error rate individual probability value estimation multiple comparison adjustments."
Price: 49.99 |
| "Python by Example" |
| "Python By Example will help you learn the Python programming language from the ground up. We will be using Python 3 in this course. It is currently split into four parts. In part one, you will learn how the basic building blocks of Python, such as strings, lists, dictionaries and tuples. You will also learn how to handle exceptions, create list comprehensions, make functions, classes, etc.In part two, we take an abbreviated tour of the Python Standard Library. This set of screencasts cover handpicked modules from the library that I have found useful in my every day programming life.For part three, we move into intermediate level material such as lambdas, decorators, debugging, profiling and testing.Finally in part four we jump into 3rd party modules and packages. In this section, you will learn how to install these modules from the Python Package Index (PyPI) as well as how to use some of these modules. For example, you will learn how to use SQLAlchemy, virtualenv and pylint among others.I hope this has piqued your interest. I am looking forward to helping you learn Python too!"
Price: 24.99 |
| "pfSense Fundamentals - Secure Your Network With pfSense" |
| "pfSense is a full featured, open source firewall specific BSD build. You can download an image for free, and install it on your own hardware, or in your virtualized environment of choice, or purchase a very reasonably priced pre-configured device.Even though pfSense is built on FreeBSD, you don't have to know BSD or Linux to manage your firewall. You are encouraged to do everything you need through the browser based Graphical User Interface (GUI).As with all Udemy courses:You have a 30 day, no questions asked, money back guarantee if you're not fully satisfied with the course.You have lifetime full access to the course and all updates and additions.In this course, you'll learn:The fundamentals of what a firewall isOverviewInterfacesOutside (Untrusted)Demilitarized Zone (Medium Trust)Internal (Trusted)Stateful Packet Inspection (SPI)Application Layer FirewallWhy you need a firewallWhat pfSense isThe operating system it's built onPro's and con's of open sourceThe main features included with pfSenseOverviewManagement through the Web based Graphical User Interface (GUI)FirewallNetwork Address Translation (NAT)User ManagementConfigure pfBlockerNGInstalling pfBlockerNGWhich traffic to analyze for pfBlockerNGConfiguring pfBlockerNGInstall Snort IDS/IPSInstall SnortChoose Snort Rule SetsDownload Rule Set updatesAssign Rule Sets to interfacesMaintaining Your FirewallBacking up and restoring from backupUpdatingTroubleshooting IssuesDive in and learn pfSense today!"
Price: 29.99 |
| "Revolutionary Course Creation Method - Beat Your Competition" |
| "This is a revolutionary method. Create courses that keep students watching.I'm going to turn you into a course creation expert.- Learn how to create professional courses that stand out against most other courses.- Create engaging courses students are more likely to complete.- Students will love your courses and are highly likely to tell others to join.My name is Ian Stables. I've created more than 20 courses on Udemy. I currently have more than 32,000 students.The majority of courses are either entire slide shows, talking head throughout, or a combination of these. The definition of boring is: The same thing over and over again. This may be the reason students don't finish courses. People don't learn well when bored.Your courses need to be engaging. They have to keep student's interested.This course will show you how to create engaging courses. With the use of variety, the mind of your student will be kept engaged. By using the same methods television use, you can keep your student's interest. This is the reason television keeps us glued to the screen.It used to take me a long time to create a course.First there was the course plan. Trying to make sure everything was included.Then there would be all the slides to create, searching for pictures, adding the animation, and so on.The recording came next. This was often a series of many retakes. I'd practice a few times and then go for the actual recording. Many times, I'd make mistakes and have to start again. Very agonising.After all this, I'd end up with a course very similar to most others out there.I looked for ways to make the process easier and to get a better result. I read many books, took courses, watched hours of Youtube videos.After some time, I got the brain wave I was looking for. I was excited. At last, I had found a better way to create professional courses that would keep the interest of my students.All I do now, is create a simple plan, start recording, and then add the magic. The end result is a professional looking course that is engaging to students.Your are about to learn a three-step course creation method. You will be able to create professional courses that grab attention. You'll also be able to do it easier and quicker.The three steps are:1. Plan2. Record3. Add the magicYou will not need to spend a long time creating a slide show. No need to create any slides with this method. (Unless you want to.)I'll also share with you all the tips and tricks I've discovered.- Quality equipment and software at low prices- My simple lighting cure- My super quick way to plan courses- My simple way to relax on camera- How I always know what to say (Without a script)- The trick to one take lecture recordings- How to make lectures engaging and professionalLet me show you how to create professional online courses that stand out from most courses out there.Enroll now"
Price: 144.99 |
| "How to Massively Increase Course Sales - Change One Thing" |
| "Change the one thing that will transform your course sales. (Also works for Kindle books.)When instructors want to improve course sales, they try to improve their course description, improve their promo video, or look for a new marketing secret. While these things are important, it's not the game changer they're looking for.The game changer is the one thing most instructors overlook. When you focus on this one thing, your course sales can radically change.What is this one thing? Answer: The course title.I discovered this years ago when I published my second Kindle book on Amazon. I called it, Cleaning Without Scrubbing.I ran a marketing campaign. The result? Very little results.I looked at the cover picture. It looked good.I considered the book description. I was happy with it. I couldn't see how I could make it better. It was good enough.Was it my marketing campaign? No. I knew it worked for other authors.I decided to change the title. It liked the one I had. However, I knew it couldn't be anything else. So I changed it to, The Easy Way to Clean.I ran the same marketing campaign as I did before.The results blew me away. I got sixty-six book sales in less than eight hours. This continued to outsell every other book I published on Amazon for more than two years. I have more than fifty Kindle books.I only changed the title. Nothing else was changed.The title is the one thing you can change to massively change your results.Think about it. The only thing deciding factor students see, in Udemy search results, is the course title. If they don't click on your course title, then no sale.When you get your course title right, your results can radically change.Over the years, I've discovered what works and what doesn't.In this course, I'll show you what you can do to make your course title sell. You'll discover these things:- Get your course at the top of Udemy search results- Make them want your course, before they've read your description or watched your promo video.- How to make your course irresistible- Make them believe your course really delivers results- Use the words proven to massively boost sales- Offer students the magic pill- How to change your course title so it sellsI want you to succeed. Throughout the course, I will always be here to answer your questions. Just post your questions in the Q&A section at any time. I'll answer them as soon as possible.Change the one thing that really can transform your course sales.Enroll now."
Price: 144.99 |
| "Typing Course - How to Touch Type Faster - New Way to Learn" |
| "Learn to touch type the new way: Get more done in less time.Typing is a skill needed in many jobs, in college, for authors, and more.It's a valuable skill for life. Touch typing can be a lot faster than two fingers. This means you'll get your typing tasks finished a lot quicker.Learn this skill now and complete your typing tasks in far less time.My name is Ian Stables. I'm a self-taught touch typist. I've tried the hard way and the easy way. This is the easy way.Many try to learn the wrong way. They try to learn all the letters at once. They use pages of text to practice. This is not the most effecient way. That's the painful and slow way.This method is based on latest research on skill building. Based on the research of Peter Hollins and others, this course follows a short steps new approach.You'll ge practising two keys at a time. You won't be bored. Each combination will only be practiced for 30 seconds. This is the most efficent way to learn to type. The result is fast keyboard typing skills in far less time.You'll learn:- Where the keys are- Where to place your hands... without looking- Best way to practice and how long- How to build up speed with accuracy- The simple learning accelerator- Learn where fingers go without looking. Learn two at a time- Type numbers without looking- Best way to practice capital letters- The way to get fasterLearn this valuable skill today. Get more done in far less time. Enroll now."
Price: 149.99 |
| "Record and Sell Your Own Voice overs on Fiverr" |
| "Create Your Own Voice Overs And Tap Into One Of The The Hottest Proven Selling Gigs On Fiverr.This is the exact step-by-step system I use to earn thousands of dollars each month by simply reading scripts and recording voice overs.If you have a service to sell, the obvious thing to do is to create your own website.But why go all the hassle and expense... and then the pain of continually optimizing the site using SEO, when there is already a huge services site out there, very well known and ready to make you a good income?Fvrr a glbl online marketplace where people from all over the world can offer a variety of different tasks nd rv to customers for the minimum price of $5 per job. Each job can include extra features which the customer can also choose to purchase. This is where the real money is made and you'll discover exactly how to do this and how you can easily turn a single $5 gig into a gig that people pay you $200+ and turn them into customers that are happy pay for your services again and again...Go on the site and you'll see that there are loads of voiceovers already but that's not a reason, to not get involved yourself. You have got a unique voice, we all have, and once you start pulling in regular clients, they'll come back to you time and time again, as only you can offer the voice and service that you provide.The best thing about providing Voice overs is that you can earn a lot of money from gig extras...Let's say that you charge $5 for reading a script of 50-100 words, most scripts will be far more than 100 words so a customer will be required to purchase more gigs.You can also charge extra to add the voiceover to an existing video or you could even offer to add some background music?You can add an additional charge for express delivery so your customer receives the completed voice over quicker.You don't need to be a computer wiz or have any technical experience. You simply just read a script, record your voice and get paid!Nothing is held back, so you can get started immediately and start earning money as soon as today!Let me breakdown everything you're going to get..."
Price: 19.99 |
| "Conquer Your Fear of Public Speaking in 60 Minutes!" |
| "Do you get nervous at the thought of speaking in public, in front of a crowded room, up on stage or at an outside event?You may feel comfortable talking to someone one-on-one but when it comes to public speaking you feel anxious and uncomfortable at the thought of standing in front of a group of people and delivering a speech or presentation?Well, don't worry, this is quite normal but if you want to deliver the best speech or presentation that you can, you need to prepare yourself and follow a few simple steps that will make you feel calm, clear headed and confident.This way you won't be worrying about what you have to say, if you make mistakes or what other people will think of you.You will just be focused on delivering your message confidently and connecting with your audience in a way that makes them listen to your every word and leave them feeling impressed with how you presented yourself and how memorable your speech or presentation was.If you're looking to improve your public speaking for an upcoming event then it's likely that you want to discover as many helpful tips and techniques in as short a time as possible, right?That's why I have created this course for YOU! You won't need to spend days or even weeks to go through this course, you can go through this entire course within just 60 minutes and download a checklist of 100 amazing, very well researched public speaking tips that you can easily refer to anytime you like.You'll be amazed at how confident you feel and you'll actually be looking forward to speaking in public rather than fearing it!So, if you're ready...Click the button now to get started and I'll see you on the inside."
Price: 39.99 |
