R Language Training Courses

Анализът на данни е наука за анализиране на необработени данни, за да се получат прозрения и тенденции. Tableau е водещ инструмент за бизнес разузнаване и визуализация на данни, докато SQL е най-често използваният език за заявки към бази данни. Заедно с два от най-популярните програмни езици за наука за данни, Python и R, Tableau и SQL предоставят стабилно решение от край до край, което може да помогне за ефективното визуализиране и анализиране на данните.Това водено от инструктор обучение на живо (онлайн или на място) е насочено към анализатори на данни и всеки, който се интересува да научи как да използва и интегрира Tableau, Python, R и SQL за визуализация и анализ на данни.До края на това обучение участниците ще могат:

Извършете анализ на данни, като използвате Python, R и SQL. Създавайте прозрения чрез визуализация на данни с Tableau. Вземете управлявани от данни решения за бизнес операции.

Формат на курса

Интерактивна лекция и дискусия. Много упражнения и практика. Практическо внедряване в лабораторна среда на живо.

Опции за персонализиране на курса

За да поискате персонализирано обучение за този курс, моля свържете се с нас, за да уговорим.

R is a very popular, open source environment for statistical computing, data analytics and graphics. This course introduces R programming language to students.  It covers language fundamentals, libraries and advanced concepts.  Advanced data analytics and graphing with real world data. Audience Developers / data analytics Duration 3 days Format Lectures and Hands-on

Data analytics is a crucial tool in business today. We will focus throughout on developing skills for practical hands on data analysis. The aim is to help delegates to give evidence-based answers to questions:  What has happened?

• processing and analyzing data
• producing informative data visualizations

What will happen?

• forecasting future performance
• evaluating forecasts

What should happen?

• turning data into evidence-based business decisions
• optimizing processes

The course itself can be delivered either as a 6 day classroom course or remotely over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.

It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data. This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements. By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.

Format of the Course

• Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding

R е популярен език за програмиране в финансовата индустрия. Той се използва в финансови приложения, вариращи от основни програми за търговия до системи за управление на риска. В това обучение, ръководено от инструктори, участниците ще научат как да използват R за разработване на практически приложения за решаване на редица специфични проблеми, свързани с финансите. В края на обучението участниците ще могат да:

Разбиране на основите на R програмния език Изберете и използвайте R пакети и техники за организиране, визуализиране и анализ на финансови данни от различни източници (CSV, Excel, бази данни, уеб и т.н.) Изграждане на приложения, които решават проблеми, свързани с разпределението на активи, анализ на риска, инвестиционни резултати и др. Решаване на проблеми, интегриране на разпространението и оптимизиране на R приложение

публиката

Разработчиците Аналитиците Количеството

Формат на курса

Частна лекция, частна дискусия, упражнения и тежка практика

Забележка

Това обучение има за цел да осигури решения за някои от основните проблеми, с които се сблъскват финансовите специалисти. Въпреки това, ако имате конкретна тема, инструмент или техника, която искате да допълните или да разработите по-нататък, моля, свържете се с нас, за да организирате.

R е език за програмиране и софтуерна среда за статистическа компютърност. Заедно с R и Excel, потребителите са в състояние да прилагат R Tidyverse стандарти и по-мощни R функции за подобряване на анализа на данни в Excel. Това обучение, ръководено от инструктори (онлайн или онлайн) е насочено към анализатори на данни, които искат да програмират в R за Excel. В края на обучението участниците ще могат да:

Събиране и преместване на данни между Excel и R. Използвайте R Tidyverse и R функции за решения за анализ на данни в Excel. Актуализиране на уменията си в областта на науката на данните чрез изучаване на R.

Формат на курса

Интерактивна лекция и дискусия. Много упражнения и упражнения. Изпълнение на ръката в живо лабораторна среда.

Опции за персонализиране на курса

За да поискате персонализирано обучение за този курс, моля, свържете се с нас, за да организирате.

Audience Business owners (marketing managers, product managers, customer base managers) and their teams; customer insights professionals. Overview The course follows the customer life cycle from acquiring new customers, managing the existing customers for profitability, retaining good customers, and finally understanding which customers are leaving us and why. We will be working with real (if anonymous) data from a variety of industries including telecommunications, insurance, media, and high tech. Format Instructor-led training over the course of five half-day sessions with in-class exercises as well as homework. It can be delivered as a classroom or distance (online) course.

This course is an introduction to applying neural networks in real world problems using R-project software.

This course is for data scientists and statisticians that already have basic R & C++ coding skills and R code and need advanced R coding skills. The purpose is to give a practical advanced R programming course to participants interested in applying the methods at work. Sector specific examples are used to make the training relevant to the audience

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.

Big Data is a term that refers to solutions destined for storing and processing large data sets. Developed by Google initially, these Big Data solutions have evolved and inspired other similar projects, many of which are available as open-source. R is a popular programming language in the financial industry.

The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the R programming platform and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results. Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.

Description:  This is a course designed to teach R users how to create web apps without needing to learn cross-browser HTML, Javascript, and CSS. Objective: Covers the basics of how Shiny apps work. Covers all commonly used input/output/rendering/paneling functions from the Shiny library.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.

This course is part of the Data Scientist skill set (Domain: Data and Technology)

R  е свободен език за програмиране с отворен код за статистически компютри, анализ на данни и графики. Изследванията се използват от нарастващ брой мениджъри и аналитици на данни в корпорациите и академиите. R има широк спектър от пакети за извличане на данни.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.

This course covers advanced topics in R programming.

In this instructor-led, live training, participants will learn advanced techniques for Machine Learning with R as they step through the creation of a real-world application. By the end of this training, participants will be able to:

• Understand and implement unsupervised learning techniques
• Apply clustering and classification to make predictions based on real world data.
• Visualize data to quicly gain insights, make decisions and further refine analysis.
• Improve the performance of a machine learning model using hyper-parameter tuning.
• Put a model into production for use in a larger application.
• Apply advanced machine learning techniques to answer questions involving social network data, big data, and more.

In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the banking industry. R will be used as the programming language. Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of live projects. Audience

• Developers
• Data scientists
• Banking professionals with a technical background

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn the fundamentals of R programming as they walk through coding in R using financial examples. By the end of this training, participants will be able to:

• Understand the basics of R programming
• Use R to manipulate their data to perform basic financial operations

Audience

• Programmers
• Finance professionals
• IT Professionals

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

R е популярен език за програмиране в финансовата индустрия. Той се използва в финансови приложения, вариращи от основни програми за търговия до системи за управление на риска. В този инструктор-управлява, на живо обучение, участниците ще научат основите на финансовата търговия, тъй като те стъпват през изграждането и прилагането на основни търговски стратегии и действия в R с помощта на кванстрат. В края на обучението участниците ще могат да:

Разбиране на основните понятия в търговията Създаване и прилагане на първата си търговска стратегия с помощта на R Анализиране на ефективността на стратегията си с помощта на R

публиката

Програмисти [ 0 ] Професионалисти Това са професионалисти

Формат на курса

Частна лекция, частна дискусия, упражнения и тежка практика

R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn advanced programming concepts in R as they walk through coding in R using financial examples. By the end of this training, participants will be able to:

• Implement advanced R programming techniques
• Use R to manipulate their data to perform more advanced financial operations

Audience

• Programmers
• Finance professionals
• IT Professionals

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the finance industry. R will be used as the programming language. Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of team projects. By the end of this training, participants will be able to:

• Understand the fundamental concepts in machine learning
• Learn the applications and uses of machine learning in finance
• Develop their own algorithmic trading strategy using machine learning with R

Audience

• Developers
• Data scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn how to implement deep learning models for finance using R as they step through the creation of a deep learning stock price prediction model. By the end of this training, participants will be able to:

• Understand the fundamental concepts of deep learning
• Learn the applications and uses of deep learning in finance
• Use R to create deep learning models for finance
• Build their own deep learning stock price prediction model using R

Audience

• Developers
• Data scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn how to implement deep learning models for banking using R as they step through the creation of a deep learning credit risk model. By the end of this training, participants will be able to:

• Understand the fundamental concepts of deep learning
• Learn the applications and uses of deep learning in banking
• Use R to create deep learning models for banking
• Build their own deep learning credit risk model using R

Audience

• Developers
• Data scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Shiny is an open source R package that provides a web framework for building interactive web applications using R. In this instructor-led, live training, participants will learn how to combine data science and web development using Shiny, R, and HTML. By the end of this training, participants will be able to:

• Build interactive web applications with R using Shiny

Audience

• Data scientists
• Web developers
• Statisticians

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice