현지 강사 주도의 라이브 R (R Language) 교육 과정은 R 프로그래밍의 기본 사항, 고급 R 프로그래밍 및 데이터 분석 및 데이터 시각화를위한 R을 포함하여 실습을 통해 R 언어의 다양한 측면을 실습을 통해 제공합니다. 우리의 교육 트레이닝은 금융, 은행 및 보험과 같은 분야에서 현실 세계의 문제와 해결책을 다루고 있습니다. NobleProg R 교육 과정은 초급 과정에서 고급 과정에 이르기까지 다양하며 기계 학습 및 심층 학습 응용 프로그램 개발을 위해 R을 채택하려는 기업들에게 인기가 있습니다.
R 교육은 "현장 실습"또는 "원격 실습"으로 제공됩니다. 현장 실습은 고객 오피스에서 현지에서 실시 할 수 있고 또는 NobleProg 교육 센터에서도 수강 가능합니다. 원격 라이브 교육은 대화형 원격 데스크톱을 통해 수행됩니다.
회원 평가
그는 매우 유익하고 도움이되었습니다.
Pratheep Ravy
Course: Predictive Modelling with R
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내 모든 질문에 대한 답변을 얻습니다. Natalia Gladii - CBRE Corp
Natalia Gladii
Course: Data Analytics With R
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교육 후에 탐구 할 수있는 많은 문제 Klaudia Kłębek
Klaudia Kłębek
Course: Data Mining z wykorzystaniem R
Machine Translated
트레이너는 매우 지식이 많았고 내가 관심이있는 영역을 포함했습니다.
Mohamed Salama
Course: Data Mining & Machine Learning with R
Machine Translated
필요에 매우 맞춘
Yashan Wang
Course: Data Mining with R
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Gunnar와 1 : 1로 작업하십시오.
Bryant Ives
Course: Introduction to R
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깊은 기계 학습에 대한 새로운 통찰력
Josip Arneric
Course: Neural Network in R
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우리는 일반적으로 NN에 대한 지식을 얻었으며 요즘 인기있는 새로운 유형의 NN이 나에게 가장 흥미로운 것은 무엇입니까?
Tea Poklepovic
Course: Neural Network in R
Machine Translated
그래프는 R :)))
Faculty of Economics and Business Zagreb
Course: Neural Network in R
Machine Translated
유연하고 친절한 스타일. 나를 위해 유용하고 관련성이 높은 것을 정확하게 배웁니다
Jenny Tickner
Course: Advanced R
Machine Translated
나는 예제를 가지고 연습을하는 엑셀 시트를 즐겼다. 이것은 카밀이 다른 사람들을 돕기 위해 붙잡 혔을 때, 나는 다음 부분으로 갈라 갈 수 있다는 것을 의미했다
Luke Pontin
Course: Data and Analytics - from the ground up
Machine Translated
사용법을 배우는 것이 적절하게 탁월합니다
Torin Mitchell
Course: Data and Analytics - from the ground up
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강사가 복잡한 과목을 이해하기 쉽게 만든 방법
Adam Drewry
Course: Data and Analytics - from the ground up
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주제에 경험 있고 명확하게 지식이있는 전문가에 의해 주어진 상세하고 포괄적 인 지시
Justin Roche
Course: Data and Analytics - from the ground up
Machine Translated
Kamil은 매우 지식 있고 좋은 사람입니다. 나는 그에게서 많은 것을 배웠습니다.
Aleksandra Szubert
Course: Data and Analytics - from the ground up
Machine Translated
첫 번째 세션. 매우 집중적이고 빠른
Digital Jersey
Course: Data and Analytics - from the ground up
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카밀의 인내심
Laszlo Maros
Course: Data and Analytics - from the ground up
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실제 생활의 실례
Wioleta (Vicky) Celinska-Drozd
Course: Data and Analytics - from the ground up
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모든 주제 요청에 응답하고 답변하는 데 많은 시간을 보냈습니다. HSH Nordbank AG
HSH Nordbank AG
Course: Prognosen mit R
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무료 연습. Sabi
Sabine Stammberger
Course: Prognosen mit R
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많은 지식과 이론이 실용적입니다
Anna Alechno
Course: Forecasting with R
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그의 knowlede 및 실용 exemples
Irina Tulgara
Course: Forecasting with R
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주제가 얼마나 큰지 개요 및 이해
British American Shared Services Europe BAT GBS Finance, WER/Centre/EEMEA
Course: Forecasting with R
Machine Translated
트레이너와의 좋은 상호 작용, 지식의 역동적 인 교환 NIIT Limited
NIIT Limited
Course: Data Analytics With R
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보기에 손이 가장 도움이되었습니다
Sean Kaukas
Course: Introduction to R
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Michael의 강사는 Big Data 및 R의 주제에 대해 매우 잘 알고 있으며 숙련되어 있습니다. 그는 매우 유연하고 신속하게 고객의 필요를 충족시키기 위해 교육을 사용자 정의합니다. 그는 또한 이동 중에도 기술 및 주제 문제를 해결할 수있는 능력이 뛰어납니다. 환상적이고 전문적인 교육!!
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
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새로운 패키지의 도입Ottawa Researc
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
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교사 인 마이클 얀 (Michael Yan)은 청중과 매우 잘 교류했으며, 수업은 분명했습니다. 튜터는 또한 훈련 중 학생들의 요청에 따라 더 많은 정보를 추가합니다.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
Machine Translated
주제와 속도는 완벽했습니다Tim - Ottawa Resear
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
Machine Translated
연구의 좋은 개요와 주제의 좋은 범위. 강사는 모든 질문에 기꺼이 답했습니다Symphony EYC
Symphony EYC
Course: R
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트레이너에 대한 지식Stephanie Seie
Stephanie Seiermann
Course: R
Machine Translated
그것은 매우 유익하고 전문적으로 개최되었습니다. Wojteks의 지식 수준은 매우 진보하여 모든 질문에 기본적으로 대답 할 수 있었고 개인적인 필요에 맞게 훈련에 참여할 수있었습니다
Sonja Steiner - BearingPoint GmbH
Course: R Programming for Data Analysis
Machine Translated
내 일에 직접 사용할 수있는 많은 연습 문제.
Alior Bank S.A.
Course: Sieci Neuronowe w R
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실제 데이터의 예.
Alior Bank S.A.
Course: Sieci Neuronowe w R
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neuralnet, 루프에서 pROC.
Alior Bank S.A.
Course: Sieci Neuronowe w R
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시계열 모델링에 대한 연습.
Teleperformance
Course: Data Analytics With R
Machine Translated
새로운 도구 인 "R"과 나는 데이터 분석을위한 도구의 존재를 아는 것이 재미 있다는 것을 발견했습니다.
Michael Lopez - Teleperformance
Course: Data Analytics With R
Machine Translated
도구가 재미 있었고 사용법을 알았습니다. 나는 그것에 대해 더 많이 배우고 싶다. .
Teleperformance
Course: Data Analytics With R
Machine Translated
많은 연습.
Centrum Innowacji ProLearning Agnieszka Kołodziejczyk
Course: R
Machine Translated
트레이너와 경험에 대한 실질적인 지식, 다양한 예
Anna Wysocka - Centrum Innowacji ProLearning Agnieszka Kołodziejczyk
Course: R
Machine Translated
그 문제는 잘 표현되어 질서 정연하게 나타났다.
Marylin Houle - Ivanhoe Cambridge
Course: Introduction to R with Time Series Analysis
Machine Translated
그는 모든 것을 잘 설명하고 예제를 사용했습니다.
royal bank of Canada
Course: R
Machine Translated
나는 연습을 통해 자기 학습을 즐기고 팁과 단축키를 공유했습니다.
Competition Bureau
Course: R for Data Analysis and Research
Machine Translated
나는 유지 하 고 과정 후 통해 작업 하는 자세한 노트에서 혜택을 했다.
Public Health Wales NHS Trust
Course: Introduction to Data Visualization with Tidyverse and R
Machine Translated
속도는 딱 이었고 편안한 분위기는 후보자 들에 게 질문을 쉽게 느끼게 했습니다.
Rhian Hughes - Public Health Wales NHS Trust
Course: Introduction to Data Visualization with Tidyverse and R
Machine Translated
나는 함께 따를 수 있는 좋은 모범과 기회 로부터 유익을 얻을 수 있었다.
Environmental and Climate Change Canada
Course: Foundation R
Machine Translated
나는 진정으로 손을 통과 연습을 즐겼다.
Yunfa Zhu - Environmental and Climate Change Canada
Course: Foundation R
Machine Translated
트레이너, 음식, 그리고 공간은 모두 좋았어요.
Canada Revenue Agency
Course: R
Machine Translated
필자는 실제로 샘플 데이터를 사용 하 여 코드를 작성 하 고 나중에 참조할 스크립트에 주석을 답니다.
Canada Revenue Agency
Course: R
Machine Translated
교육 자료에 사용 되는 미리 만들어진 스크립트는 매우 유용 했다. 대화식 교육을 통해 각 주제를 명확히 이해할 수 있었습니다.
Canada Revenue Agency
Course: R
Machine Translated
R Language서브 카테고리
R Language코스 개요
코스 이름
Duration
Overview
코스 이름
Duration
Overview
21 시간
Overview
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.
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 시간
Overview
This course is an introduction to applying neural networks in real world problems using R-project software.
7 시간
Overview
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
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
[R](http://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 시간
Overview
This course is part of the Data Scientist skill set (Domain: Data and Technology)
14 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
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 시간
Overview
The objective of the course is to enable participants to gain a mastery of the fundamentals of R and how to work with data.
14 시간
Overview
This instructor-led, live training in 대한민국 (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.
By the end of this training, participants will be able to:
- Employ algorithms to buy and sell securities at specialized increments rapidly.
- Reduce costs associated with trade using algorithmic trading.
- Automatically monitor stock prices and place trades.
By the end of this training, participants will be able to:
- Employ algorithms to buy and sell securities at specialized increments rapidly.
- Reduce costs associated with trade using algorithmic trading.
- Automatically monitor stock prices and place trades.
향후R Language 코스
16-11-2021 10:00
21 hours
16-11-2021 10:00
21 hours
22-11-2021 10:00
21 hours
13-12-2021 10:00
28 hours
20-12-2021 10:00
28 hours
Other countries
Consulting
주말R Language코스, 밤의R Language트레이닝, R Language부트 캠프, R Language 강사가 가르치는, 주말R Language교육, 밤의R Language과정, R Language코칭, R Language강사, R Language트레이너, R Language교육 과정, R Language클래스, R Language현장, R Language개인 강좌, R Language1 대 1 교육
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