Lokale, instruktorierte Live-R (R Language) -Trainings demonstrieren durch praktische Übungen verschiedene Aspekte der R-Sprache, einschließlich der Grundlagen der R-Programmierung, fortgeschrittenen R-Programmierung und R für Datenanalyse und Datenvisualisierung Unsere Trainings beschäftigen sich mit realen Problemen und Lösungen in Bereichen wie Finanzen, Bankwesen und Versicherungen NobleProg R Trainingskurse reichen von Anfängerkursen bis hin zu Fortgeschrittenenkursen und sind beliebt bei Unternehmen, die R für die Entwicklung von Machine Learning und Deep Learning Anwendungen einsetzen möchten R-Training ist als "Live-Training vor Ort" oder "Fern-Live-Training" verfügbar Onsite Live Training kann vor Ort bei Kunden durchgeführt werden Österreich oder in NobleProg Corporate Trainingszentren in Österreich Remote-Live-Training wird über einen interaktiven Remote-Desktop durchgeführt NobleProg Ihr lokaler Trainingsanbieter.
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Erfahrungsberichte
Auf alle Themenwünsche eingegangen und viel Zeit für die Beantwortung genommen.
HSH Nordbank AG
Kurs: Prognosen mit R
Die freien Übungen.
Sabine Stammberger
Kurs: Prognosen mit R
Er war sehr informativ und hilfsbereit.
Pratheep Ravy
Kurs: Predictive Modelling with R
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Ich bekomme Antworten auf alle meine Fragen.
Natalia Gladii
Kurs: Data Analytics With R
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Viele Probleme, die nach dem Training erforscht werden können
Klaudia Kłębek
Kurs: Data Mining z wykorzystaniem R
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Der Trainer war so sachkundig und schloss Bereiche ein, an denen ich interessiert war.
Mohamed Salama
Kurs: Data Mining & Machine Learning with R
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Sehr auf die Bedürfnisse zugeschnitten.
Yashan Wang
Kurs: Data Mining with R
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Ich habe es wirklich genossen, 1: 1 mit Gunner zu arbeiten.
Bryant Ives
Kurs: Introduction to R
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Ich mochte die neuen Einblicke in tiefes maschinelles Lernen.
Josip Arneric
Kurs: Neural Network in R
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Wir haben etwas über NN im Allgemeinen gelernt, und was für mich am interessantesten war, waren die neuen Typen von NN, die heutzutage populär sind.
Tea Poklepovic
Kurs: Neural Network in R
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Mir gefielen die Graphen in R :))).
Faculty of Economics and Business Zagreb
Kurs: Neural Network in R
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Der flexible und freundliche Stil. Ich lernte genau, was für mich nützlich und relevant war.
Jenny Tickner
Kurs: Advanced R
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Ich genoss die bereitgestellten Excel-Tabellen mit den Übungen mit Beispielen. Das bedeutete, dass, wenn Tamil anderen Leuten helfen würde, ich mit den nächsten Teilen weitermachen könnte.
Luke Pontin
Kurs: Data and Analytics - from the ground up
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Lernen, wie man Excel richtig einsetzt.
Torin Mitchell
Kurs: Data and Analytics - from the ground up
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Die Art, wie der Trainer komplexe Themen verständlich machte.
Adam Drewry
Kurs: Data and Analytics - from the ground up
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Detaillierte und umfassende Anleitung von erfahrenen und klar kenntnisreichen Experten zum Thema gegeben.
Justin Roche
Kurs: Data and Analytics - from the ground up
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Tamil ist sehr kenntnisreich und nette Person, ich habe viel von ihm gelernt.
Aleksandra Szubert
Kurs: Data and Analytics - from the ground up
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Ich mochte die erste Sitzung. Sehr intensiv und schnell.
Digital Jersey
Kurs: Data and Analytics - from the ground up
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Am meisten mochte ich die Geduld Tamils.
Laszlo Maros
Kurs: Data and Analytics - from the ground up
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Ich habe wirklich von den praktischen Beispielen des wirklichen Lebens profitiert.
Wioleta (Vicky) Celinska-Drozd
Kurs: Data and Analytics - from the ground up
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Viel Wissen - theoretisch und praktisch.
Anna Alechno
Kurs: Forecasting with R
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Ich mochte sein Wissen und seine praktischen Beispiele wirklich.
Irina Tulgara
Kurs: Forecasting with R
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Überblick und Verständnis, wie groß das Thema ist.
British American Shared Services Europe BAT GBS Finance, WER/Centre/EEMEA
Kurs: Forecasting with R
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gute Interaktion mit dem Trainer, dynamischer Wissensaustausch
NIIT Limited
Kurs: Data Analytics With R
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Praktische Beispiele waren am hilfreichsten.
Sean Kaukas
Kurs: Introduction to R
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Michael der Trainer ist sehr sachkundig und geschickt in Bezug auf das Thema Big Data und R. Er ist sehr flexibel und passt das Training schnell an die Bedürfnisse der Kunden an. Er ist auch sehr in der Lage, technische und fachliche Probleme unterwegs zu lösen. Fantastisches und professionelles Training!
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Kurs: Programming with Big Data in R
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Ich habe die Einführung neuer Pakete sehr genossen.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Kurs: Programming with Big Data in R
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Der Tutor, Herr Michael Yan, interagierte sehr gut mit dem Publikum, die Anweisung war klar. Der Tutor ist auch bemüht, weitere Informationen basierend auf den Anforderungen der Schüler während des Trainings hinzuzufügen.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Kurs: Programming with Big Data in R
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Das Thema und das Tempo waren perfekt.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Kurs: Programming with Big Data in R
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Guter Überblick über R und gute Themenvielfalt. Trainer war glücklich, alle Fragen zu beantworten.
Symphony EYC
Kurs: R
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Ich habe das Wissen des Trainers sehr genossen.
Stephanie Seiermann
Kurs: R
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Es war sehr informativ und professionell gehalten. Wojteks Wissensniveau war so weit fortgeschritten, dass er grundsätzlich jede Frage beantworten konnte und er bereit war, sich darum zu bemühen, das Training auf meine persönlichen Bedürfnisse abzustimmen.
Sonja Steiner - BearingPoint GmbH
Kurs: R Programming for Data Analysis
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viele Übungen, die ich direkt in meiner Arbeit anwenden kann.
Alior Bank S.A.
Kurs: Sieci Neuronowe w R
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Beispiele für echte Daten.
Alior Bank S.A.
Kurs: Sieci Neuronowe w R
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neuralnet, pROC in einer Schleife.
Alior Bank S.A.
Kurs: Sieci Neuronowe w R
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Ich mochte die Übungen zur Zeitreihenmodellierung sehr.
Teleperformance
Kurs: Data Analytics With R
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Neues Werkzeug, das "R" ist und ich finde es interessant zu wissen, dass ein solches Werkzeug für die Datenanalyse existiert.
Michael Lopez - Teleperformance
Kurs: Data Analytics With R
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Das Tool war interessant und ich sehe die Verwendung. Ich würde gerne mehr darüber erfahren.
Teleperformance
Kurs: Data Analytics With R
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Viel Übung.
Centrum Innowacji ProLearning Agnieszka Kołodziejczyk
Kurs: R
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Umfangreiche Kenntnisse des Trainers und Erfahrung, verschiedene Beispiele
Anna Wysocka - Centrum Innowacji ProLearning Agnieszka Kołodziejczyk
Kurs: R
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Die Angelegenheit war gut präsentiert und ordentlich.
Marylin Houle - Ivanhoe Cambridge
Kurs: Introduction to R with Time Series Analysis
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Er hat wirklich alles gut erklärt und Beispiele verwendet.
royal bank of Canada
Kurs: R
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Ich habe das Selbstlernen durch Übungen und die geteilten Tipps und Verknüpfungen genossen.
Competition Bureau
Kurs: R for Data Analysis and Research
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Ich profitierte von den ausführlichen Notizen, die ich nach dem Kurs durchhalten und durcharbeiten konnte.
Public Health Wales NHS Trust
Kurs: Introduction to Data Visualization with Tidyverse and R
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Das Tempo war genau richtig und die entspannte Atmosphäre ließ die Kandidaten sich wohl fühlen, Fragen zu stellen.
Rhian Hughes - Public Health Wales NHS Trust
Kurs: Introduction to Data Visualization with Tidyverse and R
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Ich profitierte von den guten Beispielen und der Möglichkeit, mitzumachen.
Environmental and Climate Change Canada
Kurs: Foundation R
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Ich habe die vorbeigebletzten Übungen wirklich genossen.
Yunfa Zhu - Environmental and Climate Change Canada
Kurs: Foundation R
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Der Trainer, das Essen und der Raum waren alle toll.
Canada Revenue Agency
Kurs: R
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R Language Unterkategorien
R Language Kurspläne
Name des Kurses
Dauer
Überblick
Name des Kurses
Dauer
Überblick
21 Stunden
This instructor-led, live training in Österreich (online or onsite) is aimed at data analysts who wish to program in R for Excel.
By the end of this training, participants will be able to:
- Toggle and move data between Excel and R.
- Use R Tidyverse and R features for data analytic solutions in Excel.
- Extend their data analytical skills by learning R.
By the end of this training, participants will be able to:
- Toggle and move data between Excel and R.
- Use R Tidyverse and R features for data analytic solutions in Excel.
- Extend their data analytical skills by learning R.
21 Stunden
Publikum
Business (Marketingmanager, Produktmanager, Kundenstammmanager) und ihre Teams; Kundeneinblicke Profis.
Überblick
Der Kurs folgt dem Kundenlebenszyklus, indem neue Kunden gewonnen, die bestehenden Kunden auf Rentabilität hin verwaltet, gute Kunden gehalten und schließlich verstanden werden, welche Kunden uns verlassen und warum. Wir werden mit echten (wenn auch anonymen) Daten aus einer Vielzahl von Branchen arbeiten, darunter Telekommunikation, Versicherungen, Medien und High-Tech.
Format
Vom Kursleiter geführtes Training über fünf halbtägige Sitzungen mit Übungen im Unterricht sowie Hausaufgaben. Es kann als Unterrichts- oder Fernkurs (online) angeboten werden.
Business (Marketingmanager, Produktmanager, Kundenstammmanager) und ihre Teams; Kundeneinblicke Profis.
Überblick
Der Kurs folgt dem Kundenlebenszyklus, indem neue Kunden gewonnen, die bestehenden Kunden auf Rentabilität hin verwaltet, gute Kunden gehalten und schließlich verstanden werden, welche Kunden uns verlassen und warum. Wir werden mit echten (wenn auch anonymen) Daten aus einer Vielzahl von Branchen arbeiten, darunter Telekommunikation, Versicherungen, Medien und High-Tech.
Format
Vom Kursleiter geführtes Training über fünf halbtägige Sitzungen mit Übungen im Unterricht sowie Hausaufgaben. Es kann als Unterrichts- oder Fernkurs (online) angeboten werden.
14 Stunden
Dieser Kurs ist eine Einführung in die Anwendung neuronaler Netze bei realen Problemen mit R-Project-Software.
7 Stunden
Dieser Kurs ist ausgelegt für Data Scientists and Statistiker die breits Grundkenntnisse in "R & C++ coding skills und R-Code haben und fortgeschrittene "R-coding-skills" benötigen.
Es handelt sich um einen praxisorientierten Fortgeschrittenen-Kurs in der Programmiersprache "R" für alle diejenigen, die die Methoden für die Arbeit benötigen.
Bereichsspezifische Beispiele erhöhen die Relevanz der Schulung für die Teilnehmer
Es handelt sich um einen praxisorientierten Fortgeschrittenen-Kurs in der Programmiersprache "R" für alle diejenigen, die die Methoden für die Arbeit benötigen.
Bereichsspezifische Beispiele erhöhen die Relevanz der Schulung für die Teilnehmer
14 Stunden
R ist eine freie Open-Source-Programmiersprache für statistische Berechnungen, Datenanalysen und Grafiken. R wird von einer wachsenden Anzahl von Managern und Datenanalysten in Unternehmen und Hochschulen verwendet. R bietet eine Vielzahl von Paketen für das Data Mining.
21 Stunden
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 Stunden
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.
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 Stunden
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 Stunden
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 Stunden
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.
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 Stunden
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 Stunden
[R](https://www.r-project.org/) 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
Audience
Developers / data analytics
Duration
3 days
Format
Lectures and Hands-on
14 Stunden
This course is part of the Data Scientist skill set (Domain: Data and Technology)
14 Stunden
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.
14 Stunden
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 Stunden
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 Stunden
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
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
42 Stunden
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](https://www.nobleprog.co.uk/instructor-led-online-training-courses) over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
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](https://www.nobleprog.co.uk/instructor-led-online-training-courses) over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
21 Stunden
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.
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 Stunden
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
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
28 Stunden
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 use R to develop practical applications for solving a number of specific finance related problems.
By the end of this training, participants will be able to:
- Understand the fundamentals of the R programming language
- Select and utilize R packages and techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
- Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
- Troubleshoot, integrate deploy and optimize an R application
Audience
- Developers
- Analysts
- Quants
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
In this instructor-led, live training, participants will learn how to use R to develop practical applications for solving a number of specific finance related problems.
By the end of this training, participants will be able to:
- Understand the fundamentals of the R programming language
- Select and utilize R packages and techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
- Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
- Troubleshoot, integrate deploy and optimize an R application
Audience
- Developers
- Analysts
- Quants
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
21 Stunden
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
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 Stunden
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 basics of financial trading as they step through building and implementing basic trading strategies and actions in R using quantstrat.
By the end of this training, participants will be able to:
- Understand the fundamental concepts in trading
- Create and implement their first trading strategy using R
- Analyze the performance of their strategy using R
Audience
- Programmers
- Finance professionals
- IT Professionals
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn the basics of financial trading as they step through building and implementing basic trading strategies and actions in R using quantstrat.
By the end of this training, participants will be able to:
- Understand the fundamental concepts in trading
- Create and implement their first trading strategy using R
- Analyze the performance of their strategy using R
Audience
- Programmers
- Finance professionals
- IT Professionals
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
21 Stunden
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
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 Stunden
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
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 Stunden
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
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 Stunden
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
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 Stunden
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
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
7 Stunden
The objective of the course is to enable participants to gain a mastery of the fundamentals of R and how to work with data.
Last Updated:
Zukünftige R Language Kurse
Deep Learning for Finance (with R)
14-02-2022 09:30
28 hours
Deep Learning for Banking (with R)
15-02-2022 09:30
28 hours
Foundation R
23-02-2022 09:30
7 hours
Shiny, R and HTML: Merging Data Science and Web Development
25-02-2022 09:30
7 hours
Machine Learning for Finance (with R)
22-03-2022 09:30
28 hours
Andere Länder
Consulting
R Language Schulung, R Language boot camp, R Language Abendkurse, R Language Wochenendkurse, R Language Kurs, R Language Training, R Language Seminar, R Language Seminare, R Language Privatkurs, R Language Coaching, R Language Lehrer
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.jpg "european southern observatory (eso)")
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