We will be gradually adding course materials to this page as we receive them from the instructors.
Introduction to the Linux command line
- Bash Scripting and Tools: lesson notes
Working with data and visualization
- Working with Text Data: ZIP file with data and presentation
- Introduction to Apache Spark: Jupyter notebook with Python code
- Scientific Visualization: ZIP file with slides, scripts, and sample datasets
- Working with Spatial Data: PDF slides
High-performance computing and programming
- Introduction to high-performance computing (HPC): ZIP file with the slides and codes
- Introduction to C (and pointers) for Python Programmers: gzipped TAR file with the slides and source codes
- Speeding up Python code with C/C++: gzipped TAR file with the slides and source codes
- Python Libraries for Researchers: PDF slides
- Chapel parallel programming: PDF slides, notes for base language, notes for task parallelism, and notes for data parallelism
- MATLAB Parallel Computing: ZIP file with slides and exercises
Machine learning stream
- Introduction to Python: PowerPoint slides
- Regression Classifiers with Python: first Jupyter notebook, second Jupyter notebook, and PowerPoint slides
- Nearest Neighbours in Python with scikit-learn: lesson notes and datasets
- Gathering and Using Unstructured Data: PDF slides and source code
- Real Data Issues and How to Handle Them: ZIP file with data
- Practical Applications of Deep Learning with MATLAB: ZIP file with slides and other files. Some of the larger files were excluded to keep the file size small. If you want these large datasets, please contact the instructor rteramot at mathworks dot com.