Online or onsite, instructor-led live R (R Language) training courses demonstrate through hands-on practice various aspects of the R language, including the fundamentals of R programming, advanced R programming and R for Data Analysis and Data Visualization. Our training exercises touch on real-world problems and solutions in areas such as Finance, Banking and Insurance. NobleProg R training courses range from beginner courses to advanced courses and are popular among companies wishing to adopt R for developing Machine Learning and Deep Learning applications.
R training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live R Language training can be carried out locally on customer premises in Finland or in NobleProg corporate training centers in Finland.
NobleProg -- Your Local Training Provider
Testimonials
The flexible and friendly style. Learning exactly what was useful and relevant for me
Jenny Tickner
Course: Advanced R
The tutor, Mr. Michael Yan, interacted with the audience very well, the instruction was clear. The tutor also go extent to add more information based on the requests from the students during the training.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
the introduction of new packages
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize the training to meet clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
That Haytham started with the basics and gave us enough time to do the examples and ensure that we were at the same page before we moved on to the next topic.
Jaco Dreyer - Africa Health Research Institute
Course: R Fundamentals
I enjoyed that it was very hands-on, so we were constantly having the chance to try things on, rather than just sitting listening to a lecture (for example). I felt like I am now able to go away and start using R, which I haven't been able to do before
Kathy Baisley - Africa Health Research Institute
Course: R Fundamentals
Day 1 and Day 2 were really straight forward for me and really enjoyed that experience.
Mareca Sithole - Africa Health Research Institute
Course: R Fundamentals
The way the trainer made complex subjects easy to understand.
Adam Drewry
Course: Data and Analytics - from the ground up
learning how to use excel properly
Torin Mitchell
Course: Data and Analytics - from the ground up
I enjoyed the Excel sheets provided having the exercises with examples. This meant that if Kamil was held up helping other people, I could crack on with the next parts.
Luke Pontin
Course: Data and Analytics - from the ground up
Exercises on time series modeling
Teleperformance
Course: Data Analytics With R
I get answers on all my questions.
Natalia Gladii
Course: Data Analytics With R
very tailored to needs
Yashan Wang
Course: Data Mining with R
The trainer was so knowledgeable and included areas I was interested in
Mohamed Salama
Course: Data Mining & Machine Learning with R
The trainer was very concern about individual understanding.
Muhammad Surajo Sanusi - Birmingham City University
Course: Foundation R
I genuinely enjoyed the hands passed exercises.
Yunfa Zhu - Environmental and Climate Change Canada
Course: Foundation R
I was benefit from the good examples and opportunity to follow along.
Environmental and Climate Change Canada
Course: Foundation R
A lot of knowldege - theoretical and practical
Anna Alechno
Course: Forecasting with R
Good detail on what R is used for and how to start using it right away
Hoss Shenassa - Trimac Management Services LP
Course: Introduction to R with Time Series Analysis
The remote classroom setting worked very well
Trimac Management Services LP
Course: Introduction to R with Time Series Analysis
the matter was well presented and in an orderly manner.
Marylin Houle - Ivanhoe Cambridge
Course: Introduction to R with Time Series Analysis
Practical exercises with R were very helpful.
CEED Bulgaria
Course: Predictive Modelling with R
The exercises.
Elena Velkova - CEED Bulgaria
Course: Predictive Modelling with R
He was very informative and helpful.
Pratheep Ravy
Course: Predictive Modelling with R
Modeling and how to fit the data to model
USDA
Course: R for Data Analysis and Research
I enjoyed the self-learning through exercises and the tips and shortcuts shared.
Competition Bureau
Course: R for Data Analysis and Research
One hands-on exercise that is super relevant to work.
Fannie Mae
Course: R Programming for Excel
The trainer truly showed how powerful R is and why it is beneficial.
Vodacom
Course: Introduction to R
Hands on examples were the most helpful.
Sean Kaukas
Course: Introduction to R
Working with 1:1 with Gunnar.
Bryant Ives
Course: Introduction to R
Practice exercises were relevant and very helpful to reinforce the knowledge.
Andy Kwan - Environment and Climate Change Canada
Course: R
Follow-along exercises after slide presentation kept engagement.
Robin White - Environment and Climate Change Canada
Course: R
Michael was very knowledgeable and clear in his instruction of the training. Course was well structured to teach the desired subject as well as the right amount of room was left to adjust to fit our needs better. Over all, I am very happy with the course.
Brock Batey - Environment and Climate Change Canada
Course: R
Graphs in R :)))
Faculty of Economics and Business Zagreb
Course: Neural Network in R
We gained some knowledge about NN in general, and what was the most interesting for me were the new types of NN that are popular nowadays.
Tea Poklepovic
Course: Neural Network in R
new insights in deep machine learning
Josip Arneric
Course: Neural Network in R
Highly qualified trainer. Skilled both in data science and advanced R programming, capable of providing in-depth explanation of complex problems from both worlds. The knowledge was highly specialistic and will be extremely valuable to my work. Simply put: this was the best training course I have participated in.
Maria Świderek, Ministerstwo Zdrowia
Course: Advanced R Programming
Many examples and exercises related to the topic of the training.
Tomasz - Maria Świderek, Ministerstwo Zdrowia
Course: Advanced R Programming
It was very informative and professionally held. Wojteks knowledge level was so advanced that he could basically answer any question and he was willing to put effort into fitting the training to my personal needs.
Sonja Steiner - BearingPoint GmbH
Course: R Programming for Data Analysis
The trainer was very good. He presented the material in a really accessible way.
Hydrock
Course: Introduction to Data Visualization with Tidyverse and R
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course: Introduction to Data Visualization with Tidyverse and R
I was benefit from the detailed notes to keep and work through after the course.
Public Health Wales NHS Trust
Course: Introduction to Data Visualization with Tidyverse and R
R Language Subcategories in Finland
R Language Course Outlines in Finland
Course Name
Duration
Overview
Course Name
Duration
Overview
35 hours
This instructor-led, live training in Finland (online or onsite) is aimed at data analysts and anyone who is interested to learn how to use and integrate Tableau, Python, R, and SQL for data visualization and analysis.
By the end of this training, participants will be able to:
- Perform data analysis using Python, R, and SQL.
- Create insights through data visualization with Tableau.
- Make data-driven decisions for business operations.
21 hours
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 hours
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
- forecasting future performance
- evaluating forecasts
- turning data into evidence-based business decisions
- optimizing processes
21 hours
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.
- Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
21 hours
This instructor-led, live training in Finland (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.
28 hours
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
- Developers
- Analysts
- Quants
- Part lecture, part discussion, exercises and heavy hands-on practice
- 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.
14 hours
This instructor-led, live training in Finland (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.
14 hours
This instructor-led, live training in Finland (online or onsite) is aimed at data scientists and data analysts who wish to program in R and Python for outlier detection.
By the end of this training, participants will be able to:
- Identify whether data is an anomaly or is an expected value.
- Implement algorithms for anomaly detection.
- Use various techniques and methods to detect anomalies.
21 hours
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.
21 hours
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 hours
This instructor-led, live training in Finland (online or onsite) is aimed at data analysts who wish to program with R in SAS for cluster analysis.
By the end of this training, participants will be able to:
- Use cluster analysis for data mining
- Master R syntax for clustering solutions.
- Implement hierarchical and non-hierarchical clustering.
- Make data-driven decisions to help to improve business operations.
14 hours
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.
28 hours
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
- Developers
- Data scientists
- Part lecture, part discussion, exercises and heavy hands-on practice
28 hours
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
- Developers
- Data scientists
- Part lecture, part discussion, exercises and heavy hands-on practice
14 hours
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 hours
The objective of the course is to enable participants to gain a mastery of the fundamentals of R and how to work with data.
21 hours
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
- Programmers
- Finance professionals
- IT Professionals
- Part lecture, part discussion, exercises and heavy hands-on practice
21 hours
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 hours
This instructor-led, live training in Finland (online or onsite) is aimed at data scientists who wish to program in Python and R for KNIME.
By the end of this training, participants will be able to:
- Plan, build, and deploy machine learning models in KNIME.
- Make data driven decisions for operations.
- Implement end to end data science projects.
28 hours
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
- Part lecture, part discussion, exercises and heavy hands-on practice
28 hours
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
- Developers
- Data scientists
- Part lecture, part discussion, exercises and heavy hands-on practice
14 hours
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 hours
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 hours
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 hours
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.
21 hours
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
- Programmers
- Finance professionals
- IT Professionals
- Part lecture, part discussion, exercises and heavy hands-on practice
28 hours
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 hours
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
- Programmers
- Finance professionals
- IT Professionals
- Part lecture, part discussion, exercises and heavy hands-on practice
21 hours
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.
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