Teaching Data Science with MATLAB
Data science is emerging as a field that is revolutionizing science and industries alike ... Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent.
National Academies of Sciences, Engineering, and Medicine, 2018
Educators teach data science with MATLAB by drawing on available course modules, onramp tutorials, and code examples. MATLAB offers a notebook environment, toolboxes, and apps for developing analytic models.
Using MATLAB students can combine statistics and machine learning with application specific techniques such as signal processing, image processing, text analytics, optimization and controls
Below is a curated list of course curricula, textbooks, online courses, industry applications and case studies, and resources for teaching data science with MATLAB at the undergraduate level. For resources specific to deep learning and machine learning, see:
Course Curricula
- Nathan Kutz, University of Washington: Scalable Integration of Scientific Computing and Data Science in Flipped, Open-Source Classrooms (.pptx, 353.3 MB)
- University of Washington: Data Science for Biologists
- Williams College: Linking Environmental Science Field Methods to Interpretable Results through MATLAB-Based Analysis
- City University of New York: Teaching Environmental Data Analysis Fundamentals in MATLAB
- University of Arizona: Developing an Introductory Data Analysis Class Using MATLAB
- Dartmouth College: Deep Learning
- Stanford University: Signal Processing for Machine Learning
- Colorado School of Mines: Introduction to Computer Vision
Textbooks
- Computational and Statistical Methods for Analysing Big Data with Applications
- Computational Statistics Handbook with MATLAB
- Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
- Measurement and Data Analysis for Engineering and Science
- Statistics in MATLAB: A Primer
- Text Mining with MATLAB
Online Courses
- Practical Data Science with MATLAB specialization on Coursera (4 course specialization)
- Machine Learning from Andrew Ng (Stanford University) on Coursera
- Machine Learning for Engineering and Science Applications from Prof. Balaji Srinivasan and Prof. Ganapathy (IIT Madras) on NPTEL
Industry Applications
- Electricity Load Forecasting
- Human Activity Recognition
- Predictive Maintenance
- Algorithmic Trading
- Image Classification (Machine Learning)
- Image Classification (Deep Learning)
- Heart Sound Classifier
Industry Case Studies
- Battelle Neural Bypass Technology Restores Movement to a Paralyzed Man’s Arm and Hand
- Detecting Oversteer in BMW Automobiles with Machine Learning
- ASML Develops Virtual Metrology Technology for Semiconductor Manufacturing with Machine Learning
MATLAB Resources
- MATLAB Onramp (two-hour introductory tutorial)
- Deep Learning Onramp (two-hour introductory tutorial)
- MATLAB Online (use MATLAB in your browser)
- MATLAB Grader (automatically grade MATLAB coding assignments)
- Statistics and Machine Learning Toolbox (Documentation)
- Deep Learning Toolbox (Documentation)
- Latest features and resources for data science, deep learning, and machine learning (recent release product features)
