[BIC-announce] Online MATLAB Training modules, accessible at McGill until March 31

[Ted Strauss]

Sharing these resources that are available to McGill for the next 3
months. It's
necessary to create an account using your McGill email on the Matlab site
to get access.





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*
<https://trainingenrollment.mathworks.com/selfEnrollment?code=8837TPS8WKDP>*
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
<https://trainingenrollment.mathworks.com/selfEnrollment?code=8837TPS8WKDP>
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.

*Deep Learning Onramp*: Get started quickly using deep learning methods to
perform image recognition.



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

o   MATLAB Fundamentals

o   MATLAB Programming Techniques

o   MATLAB for Data Processing and Visualization

o   Machine Learning with MATLAB

o   MATLAB for Financial Applications



After January 11, the following modules will also be added:


   - *Solving Ordinary Differential Equations with MATLAB*: Use MATLAB ODE
      solvers to numerically solve ordinary differential equations.
      - *Introduction to Linear Algebra with MATLAB*: Use matrix methods to
      solve systems of linear equations and perform eigenvalue decomposition.
      - *Introduction to Statistical Methods with MATLAB*: Get started
      quickly with basic descriptive statistics and data fitting.
      - Solving Nonlinear Equations with MATLAB: Use root finding methods
      to solve nonlinear equations


*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 write* *efficient, 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
<https://trainingenrollment.mathworks.com/selfEnrollment?code=8837TPS8WKDP>
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.






Ted Strauss / Manager, Data Resources
McConnell Brain Imaging Centre / Montreal Neurological Institute
McGill University

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