Complimentary online MATLAB training: fundamentals, data processing, machine learning, etc

Courtesy of the Masters of Management in Finance Program within the Desautels Faculty of Management, all McGill faculty, staff, and students have access to Complimentary Online MATLAB Training from now until March 31, 2018.

All online courses are self-paced, interactive, and accessible through a browser. MATLAB is embedded in the course environment, enabling users to complete practice exercises and get instant feedback. Courses are modular, so faculty and students can pick and choose among topics of interest.

How to Enroll: Simply visit the MATLAB Training for McGill University site and click the green “Get started” button.

Faculty at many universities are using these courses to supplement classroom instruction. Students can learn MATLAB on their own time, thus freeing up valuable class meetings for domain-specific discussions and applications. In addition, students can print progress reports and certificates of completion to share with their instructors.

Available Courses:

MATLAB Onramp: Our introductory course makes a perfect homework or lab assignment – with no grading required! Taking less than 2 hours to complete, the Onramp course enables users to gain basic MATLAB skills and to become comfortable in the MATLAB environment.

Core MATLAB functionality and special topics are covered in the following courses (see descriptions below):

  • MATLAB Fundamentals
  • MATLAB Programming Techniques
  • MATLAB for Data Processing and Visualization
  • Machine Learning with MATLAB
  • MATLAB for Financial Applications

MATLAB Fundamentals
“This course provides a comprehensive introduction to the MATLAB® technical computing environment. No prior programming experience or knowledge of MATLAB is assumed. Themes of data analysis, visualization, modeling, and programming are explored throughout the course.”

MATLAB Programming Techniques
“This course provides hands-on experience using the features in the MATLAB® language to writeefficient, robust, and well-organized code. These concepts form the foundation for writing full applications, developing algorithms, and extending built-in MATLAB capabilities. Details of performance optimization, as well as tools for writing, debugging, and profiling code are covered.”

Machine Learning with MATLAB
“This course shows how to use unsupervised learning techniques to discover features in large data sets and supervised learning techniques to build predictive models.”

MATLAB for Data Processing and Visualization
“This course focuses on the details of data management and visualization techniques, from reading arbitrarily formatted text data files to producing customized publication-quality graphics. The course emphasizes how to create scripts that extend the basic features provided by MATLAB®.”

MATLAB for Financial Applications
“This course provides a comprehensive introduction to the MATLAB® technical computing environment for financial professionals. The course is intended for beginning users and those looking for a review. Themes of data analysis, visualization, modeling, and programming are explored throughout the course, with an emphasis on practical application to finance, such as time-series analysis, Monte Carlo simulation, portfolio management, and analysis.”

Please share the link with your colleagues and students within the McGill community so that all can take advantage of the courses. Please let me know if you have any questions.

Thanks again and looking forward to continuing to work with you and your colleagues to advance your teaching and research goals.



Jerry Brusher, Ph.D.
Education Technical Marketing