Course: MATLAB Workshops - Data Science and Data Visualization with MATLAB
- Beginn: 04.02.2025
- Ende: 18.02.2025
- Ort: online only
Matlab Workshops (Online): Data Science and Data Visualization with MATLAB (ECTS: 1 per workshop)
Workshop 1: Data Science Fundamentals with MATLAB
Date and Time: Feb 4th ,13:00-17:00
Duration: 4 hours instructor-led course + 3.5 hours self-study before the course
Requirements: For this course only basic familiarity with MATLAB is needed. If you want to refresh your knowledge you can complete the MATLAB Onramp (self-paced online course; 2h). During the course and the homework assignments you can work in MATLAB Online, so no installation is required on your computer. If you want to work with desktop MATLAB, make sure you use MATLAB R2023b or newer.
Agenda:
- Data Cleaning, Importing, and Preprocessing
- Importing data from various sources (CSV, Excel)
- Handling missing data
- Practical examples and hands-on exercise
- Working with Tables and Timetables (Flipped-Classroom)
- Creating and manipulating tables and timetables
- Accessing and modifying data
- Self-study materials: Participants should have finished https://matlabacademy.mathworks.com/de/details/tables/otmltab before the course
- Basic Data Visualization (Self-Study/Flipped-Classroom)
- Creating simple plots (line, scatter, bar, etc.)
- Customizing plots (titles, labels, legends)
- Self-study materials: Participants should have finished https://matlabacademy.mathworks.com/de/details/explore-data-with-matlab-plots/otmledp before the course
- Advanced and Efficient Plotting Techniques
- Subplots and tiledlayout
- Advanced plot types
- Efficient plotting strategies for large datasets
- Paper-quality plots
Prework Links:
- https://matlabacademy.mathworks.com/de/details/tables/otmltab
- https://matlabacademy.mathworks.com/de/details/explore-data-with-matlab-plots/otmledp
Workshop 2: Advanced Data Science Techniques
Date and Time: Feb 11th ,13:00-17:00
Duration: 4 hours instructor-led course + 1 hour self-study before the course
Requirements: For this course basic to intermediate familiarity with MATLAB or Python is suggested. You should already have an idea how to load, process, and visualize data (i.e. the course topics from Day 1). During the course and the homework assignments you can work in MATLAB Online, so no installation is required on your computer. If you want to work with desktop MATLAB, make sure you use MATLAB R2023b or newer.
Agenda:
- Basic And Advanced Statistical Analysis
- Descriptive statistics
- Probability distributions and basic testing
- Self-study materials: Participants should have finished https://matlabacademy.mathworks.com/de/details/statistics-onramp/orst before the course
- ANOVA and other statistical testing models
- Big Data Handling with MATLAB
- Using Datastores to handle collections of data
- Using dedicated big-data types (Tall) and workflows related to them
- Parallel computing
- Regression and Machine Learning
- Linear and nonlinear regression
- Introduction to machine learning with MATLAB
Prework Links:
Workshop 3: Using Matlab with Python
Date and Time: Feb 18th ,14:00-17:00
Duration: 3 hours instructor-led course
Requirements: For this course some initial familiarity with MATLAB and Python is needed. Basic language syntax and concepts are not part of this course, so if you need to refresh your knowledge you can complete the MATLAB Onramp again (self-paced online course; 2h).
Agenda:
- Jupyter Notebooks with MATLAB and Python
- Introduction to Jupyter Notebooks with MATLAB
- Best practices for using Jupyter Notebooks in data science workflows
- Using Python from MATLAB
- Setting up the Python environment in MATLAB
- Calling Python functions from MATLAB
- Exchanging data between MATLAB and Python
- Hands-on examples and exercises
- Using MATLAB from Python
- Setting up the MATLAB Engine API for Python
- Calling MATLAB functions from Python
- Interchanging data between Python and MATLAB
Pre-Workshop Preparation
Participants should work through the self-paced study courses in the matlabacademy (matlabacademy.mathworks.com) linked in the agenda for each day. You can get access to a MATLAB trial license in advance if needed, please give us a note. These self-study topics are then discussed, reiterated and expanded upon in the flipped-classroom sections of the workshop. During pre-work period participants are encouraged to contact the speaker(s) via email or teams with initial questions/setup problems.
Speakers
Dr. Mihaela Jarema MathWorks Academia Team/Scientific Computing, Munich, mjarema@mathworks.com
Dr. Kathi Kugler, MathWorks Academia Team/AI & Machine Learning, Munich, kkugler@mathworks.com
Dr. Thomas Künzel, MathWorks Academia Team/Scientific Computing, Aachen, tkuenzel@mathworks.com
Maria Gavilan Alfonso, MathWorks Education Marketing, Natick/US, mgavilan@mathworks.com
Contact monika.lam@tuebingen.mpg.de for registration details.