Introductory R (Basic to Intermediate) Training Course
R is a widely used, open-source environment designed for statistical computing, data analytics, and graphics. This course provides students with an introduction to the R programming language, covering its core fundamentals, libraries, and advanced concepts.
Delivered as an instructor-led live training (available either online or onsite), this programme is tailored for beginner-level data analysts eager to leverage R to manipulate data, carry out fundamental data analysis, and produce insightful visualizations.
Upon completion of this training, participants will be able to:
- Grasp the fundamental principles of R Programming.
- Implement essential data science processes.
- Generate visual representations of data.
Format of the Course
- Interactive lectures and group discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live-lab environment.
Course Customization Options
- To request a customized training session for this course, please reach out to us to make arrangements.
Course Outline
Day One: Language Basics
- Course Introduction
- About Data Science
- Definition of Data Science
- The Process of Doing Data Science.
- Introducing R Language
- Variables and Types
- Control Structures (Loops / Conditionals)
- R Scalars, Vectors, and Matrices
- Defining R Vectors
- Matrices
- String and Text Manipulation
- Character data type
- File IO
- Lists
- Functions
- Introducing Functions
- Closures
- lapply/sapply functions
- DataFrames
- Labs for all sections
Day Two: Intermediate R Programming
- DataFrames and File I/O
- Reading data from files
- Data Preparation
- Built-in Datasets
- Visualization
- Graphics Package
- plot() / barplot() / hist() / boxplot() / scatter plot
- Heat Map
- ggplot2 package (qplot(), ggplot())
- Exploration With Dplyr
- Labs for all sections
Requirements
- A foundational background in programming is preferred.
Audience
- Data analysts
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793
Introductory R (Basic to Intermediate) Training Course - Enquiry
Testimonials (2)
knowledge of the trainer, tailor based, all topics covered
eleni - EUAA
Course - Forecasting with R
The real life applications using Statcan and CER as examples.
Matthew - Natural Resources Canada
Course - Data Analytics With R
Related Courses
Advanced R
14 HoursThis instructor-led, live training in Nigeria (online or onsite) is aimed at intermediate-level advanced R users who wish to use R to build faster workflows, improve code quality, and handle more complex analysis tasks.
By the end of this training, participants will be able to: create reusable functions, improve data workflows, debug and optimize code, and produce reproducible reports.
Algorithmic Trading with Python and R
14 HoursThis instructor-led, live training in Nigeria (online or onsite) is designed for business analysts who wish to automate trading using algorithmic strategies, Python, and R.
By the end of this training, participants will be able to:
- Utilize algorithms to rapidly buy and sell securities at specialized increments.
- Lower transaction costs by leveraging algorithmic trading.
- Automatically monitor stock prices and execute trades.
Programming with Big Data in R
21 HoursBig Data refers to solutions designed for storing and processing large datasets. Initially developed by Google, these Big Data solutions have evolved and inspired similar projects, many of which are available as open-source. R is a popular programming language in the financial industry.
Cluster Analysis with R and SAS
14 HoursThis instructor-led, live training in Nigeria (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.
Data and Analytics - from the ground up
42 HoursData analytics is a vital instrument for modern business operations. This course prioritises the development of practical, hands-on data analysis skills. Our objective is to equip delegates with the ability to provide evidence-based answers to key 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
Data Analysis with Python, R, Power Query, and Power BI
21 HoursThis instructor-led, live training in Nigeria (online or onsite) is aimed at beginner-level professionals who wish to clean and analyze data, make statistical projections, and create insightful visualizations using these tools.
By the end of this training, participants will be able to:
- Understand the basics of Python, R, Power Query, and Power BI for data analysis.
- Clean and organize datasets using Python and Power Query.
- Perform statistical analysis and projections with R.
- Create professional dashboards and reports with Power BI.
- Integrate and analyze data from multiple sources effectively.
Data Analytics With R
21 HoursR is a widely used, open-source platform designed for statistical computing, data analytics, and graphics. This course introduces participants to the R programming language, covering its fundamental principles, key libraries, and advanced techniques. Students will engage in advanced data analytics and visualization exercises using real-world datasets.
Target Audience
Developers and data analysts
Duration
3 days
Course Format
Interactive lectures and practical hands-on sessions
Forecasting with R
14 HoursThis instructor-led, live training in Nigeria (online or onsite) is aimed at intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.
By the end of this training, participants will be able to:
- Understand the fundamentals of forecasting techniques in R.
- Apply exponential smoothing and ARIMA models for time series analysis.
- Utilize the ‘forecast’ package to generate accurate forecasting models.
- Automate forecasting workflows for business and research applications.
KNIME with Python and R for Machine Learning
14 HoursThis instructor-led live training in Nigeria (online or on-site) is designed for 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 operational purposes.
- Implement end-to-end data science projects.
NLP: Natural Language Processing with R
21 HoursIt 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
Advanced Machine Learning with R
21 HoursIn this live, instructor-led training, participants will master advanced Machine Learning techniques using R while building a real-world application step-by-step.
Upon completion of this training, participants will be able to:
- Comprehend and implement unsupervised learning techniques
- Utilise clustering and classification methods to make predictions based on real-world data.
- Visualise data to quickly gain insights, make informed decisions, and further refine analysis.
- Enhance the performance of a machine learning model through hyper-parameter tuning.
- Deploy a model into production for integration into a larger application.
- Apply advanced machine learning techniques to address challenges involving social network data, big data, and more.
R Programming for Finance
28 HoursR is a widely used programming language within the financial sector. It powers various financial applications, from core trading systems to risk management platforms.
In this instructor-led live training, participants will learn how to leverage R to develop practical solutions for specific financial challenges.
Upon completing this training, participants will be able to:
- Grasp the fundamentals of the R programming language
- Select and apply R packages and techniques to organize, visualize, and analyze financial data from diverse sources (CSV, Excel, databases, web, etc.)
- Build applications that address issues such as asset allocation, risk analysis, investment performance, and more
- Troubleshoot, integrate, deploy, and optimize R applications
Audience
- Developers
- Analysts
- Quants
Course Format
- A blend of lectures, discussions, exercises, and extensive hands-on practice
Note
- This training focuses on providing solutions to common challenges faced by finance professionals. However, if you have a specific topic, tool, or technique you would like to include or expand upon, please contact us to arrange.
R Markdown for Dynamic Documents and Reproducible Reporting
14 HoursR Markdown is an authoring framework that combines executable R code with narrative text to create dynamic and reproducible documents.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level R users who wish to generate automated, dynamic reports using R Markdown for internal documentation, research publications, or web publishing.
By the end of this training, participants will be able to:
- Create R Markdown documents with embedded R code chunks and formatted text.
- Generate outputs in multiple formats including HTML, PDF, and Word.
- Use parameterized reports and conditional logic to generate dynamic content.
- Customize document appearance with themes, templates, and LaTeX for professional presentation.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Shiny App Web Development with R
14 HoursShiny is an R package that empowers users to create interactive and dynamic web applications directly within R, eliminating the need for JavaScript expertise or complex web frameworks.
This instructor-led live training (available online or onsite) is designed for intermediate-level R users looking to build and deploy custom web applications using Shiny for data visualization, user interaction, and reporting.
By the conclusion of this training, participants will be able to:
- Develop interactive web applications using Shiny and R.
- Design user interfaces featuring reactive elements and dynamic inputs.
- Integrate data visualizations and reporting capabilities into Shiny applications.
- Deploy and share Shiny apps locally or online via Shiny Server or Posit Cloud.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation within a live laboratory environment.
Customization Options
- To request customized training for this course, please contact us to arrange it.
Shiny, R and HTML: Merging Data Science and Web Development
7 HoursShiny is an open-source R package that offers a web framework for constructing interactive web applications using R.
In this instructor-led live training, participants will discover how to integrate data science and web development by leveraging Shiny, R, and HTML.
Upon completing this training, participants will be capable of:
- Developing interactive web applications in R with Shiny
Audience
- Data scientists
- Web developers
- Statisticians
Course Format
- A blend of lectures, discussions, exercises, and extensive hands-on practice