R Language Počítačové Kurzy

R Language Počítačové Kurzy

Online nebo na místě, živé kurzy R (R Language) vedené instruktory demonstrují prostřednictvím praktické praxe různé aspekty jazyka R, včetně základů programování R, pokročilého programování R a R pro analýzu dat a vizualizaci dat. Naše tréninková cvičení se dotýkají skutečných problémů a řešení v oblastech, jako jsou finance, bankovnictví a pojišťovnictví. Školicí kurzy NobleProg R se pohybují od kurzů pro začátečníky až po kurzy pro pokročilé a jsou oblíbené mezi společnostmi, které chtějí přijmout R pro vývoj aplikací Machine Learning a Deep Learning. R školení je k dispozici jako "online živé školení" nebo "na místě živé školení". Online živé školení (neboli "vzdálené živé školení") se provádí prostřednictvím interaktivní vzdálené plochy . Živá školení na místě lze provádět lokálně v prostorách zákazníka v České republice nebo ve firemních školicích střediscích NobleProg v České republice. NobleProg -- Váš místní poskytovatel školení

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R Language Podkategorie

R Language Návrh školení

Název školení
Doba trvání
Přehled
Název školení
Doba trvání
Přehled
35 hodin
Analytika dat je věda o analýze nezpracovaných dat za účelem získání přehledů a trendů. Tableau je přední nástroj pro business intelligence a vizualizaci dat, zatímco SQL je nejběžněji používaný jazyk pro dotazování databází. Společně se dvěma nejoblíbenějšími programovacími jazyky pro datovou vědu Python a R, Tableau a SQL poskytují robustní komplexní řešení, které může pomoci efektivně vizualizovat a analyzovat data.Toto živé školení vedené instruktorem (online nebo na místě) je zaměřeno na datové analytiky a kohokoli, kdo má zájem naučit se používat a integrovat Tableau, Python, R a SQL pro vizualizaci a analýzu dat.Na konci tohoto školení budou účastníci schopni:
    Proveďte analýzu dat pomocí Python, R a SQL. Vytvářejte přehledy prostřednictvím vizualizace dat pomocí Tableau. Rozhodujte pro obchodní operace na základě dat.
Formát kurzu
    Interaktivní přednáška a diskuze. Spousta cvičení a cvičení. Praktická implementace v prostředí živé laboratoře.
Možnosti přizpůsobení kurzu
    Chcete-li požádat o školení na míru pro tento kurz, kontaktujte nás a domluvíme se.
21 hodin
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
42 hodin
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.
21 hodin
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
28 hodin
R je populární programovací jazyk v finančním průmyslu. Používá se v finančních aplikacích od základních obchodních programů až po systémy řízení rizik. V tomto výcviku vedeném instruktorem se účastníci naučí, jak používat R k vývoji praktických aplikací pro řešení řady specifických problémů souvisejících s financí. Po ukončení tohoto tréninku budou účastníci schopni:
    Pochopte základní principy programovacího jazyka R Vyberte a použijte R balíčky a techniky pro organizaci, vizualizace a analýzu finančních údajů z různých zdrojů (CSV, [0), databází, webu atd.) Vytvořte aplikace, které řeší problémy související s přidělováním aktiv, analýzou rizik, investiční výkonností a dalšími Řešení problémů, integrovaná implementace a optimalizace aplikace R
publikum
    Vývojáři analytici množství
Formát kurzu
    Částečná přednáška, částečná diskuse, cvičení a těžká praxe
Poznámka
    Cílem tohoto školení je poskytnout řešení některých zásadních problémů, kterým čelí finanční profesionálové. Pokud však máte konkrétní téma, nástroj nebo techniku, kterou chcete doplnit nebo dále vypracovat, kontaktujte nás prosím, abyste to uspořádali.
21 hodin
R je programovací jazyk a softwarové prostředí pro statistické výpočty. Společně s R a Excel, uživatelé jsou schopni implementovat standardy R Tidyverse a silnější funkce R pro zlepšení analýzy dat v Excel. Tento instruktor vedený, živý trénink (online nebo on-site) je zaměřen na analytiky údajů, kteří chtějí programovat v R pro Excel. Po ukončení tohoto tréninku budou účastníci schopni:
    Shromažďovat a pohybovat data mezi Excel a R. Použijte R Tidyverse a R funkce pro řešení analýzy dat v Excel. Aktualizujte své dovednosti v oblasti datových věd pomocí učení R.
Formát kurzu
    Interaktivní přednáška a diskuse. Mnoho cvičení a praxe. Hands-on implementace v živém laboratoři prostředí.
Možnosti personalizace kurzu
    Chcete-li požádat o přizpůsobené školení pro tento kurz, kontaktujte nás, abyste uspořádali.
21 hodin
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.
14 hodin
This course is an introduction to applying neural networks in real world problems using R-project software.
7 hodin
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
14 hodin
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.
21 hodin
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.
14 hodin
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.
21 hodin
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.
21 hodin
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.
7 hodin
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.
28 hodin
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.
14 hodin
This course is part of the Data Scientist skill set (Domain: Data and Technology)
14 hodin
R  je open-source programovací jazyk pro statistické výpočetní techniky, analýzu dat a grafiku. Výzkum využívá rostoucí počet manažerů a analytiků v korporacích a akademii. R má širokou škálu balíčků pro data mining.
14 hodin
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.
21 hodin
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.
7 hodin
This course covers advanced topics in R programming.
21 hodin
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.
28 hodin
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
21 hodin
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
21 hodin
R je populární programovací jazyk v finančním průmyslu. Používá se v finančních aplikacích od základních obchodních programů až po systémy řízení rizik. V tomto instruktorově vedeném, živém tréninku se účastníci naučí základy finančního obchodu, jak postupují prostřednictvím budování a implementace základních obchodních strategií a akcí v R pomocí kvantstrat. Po ukončení tohoto tréninku budou účastníci schopni:
    Pochopte základní koncepty v obchodování Vytvořit a implementovat svou první obchodní strategii pomocí R Analýza výkonnosti jejich strategie pomocí R
publikum
    Programátory [ 0 ] profesionálové IT profesionálové
Formát kurzu
    Částečná přednáška, částečná diskuse, cvičení a těžká praxe
21 hodin
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
28 hodin
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
28 hodin
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
28 hodin
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
7 hodin
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

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