Be sure to review the program requirements overview.
Only courses on this page are approved to satisfy the requirements of the MSE in Data Science. Approval must be granted by the Oversight Committee for any course not listed on this page. To request a course be added to this list, please send an email to Lisa Wetzelberger with the course number, name, and description.
Introduction to Data Science (required)
| Offered fall and spring semesters | |
| EN.553.636 | Introduction to Data Science |
Core Areas
One course in each of the four Core Areas below. Courses chosen in this section must be distinct from the courses used to satisfy from the Electives section. Courses in italics are recommended.
| Course # | Dept | Course Title | Semester Typically Offered |
| EN.553.613 | AMS | Applied Statistics and Data Analysis | F |
| EN.553.614 | AMS | Applied Statistics and Data Analysis II | S |
| EN.553.630 | AMS | Introduction to Statistics | F/S |
| EN.553.632 | AMS | Bayesian Statistics | F |
| EN.553.639 | AMS | Time Series Analysis | S |
| EN.553.730 | AMS | Statistical Theory I | F |
| EN.553.731 | AMS | Statistical Theory II | S |
| EN.553.733 | AMS | Advanced Topics in Bayesian Analysis | S |
| EN.553.735 | AMS | Topics in Statistical Pattern Recognition (EN.553.735) | F |
| EN.553.738 | AMS | High-Dimensional Approximation, Probability, and Statistical Learning (EN.553.738) | S |
| EN.553.739 | AMS | Statistical Pattern Recognition Theory & Methods (EN.553.739) | S |
| EN.570.654 | EHE | Geostatistics: Understanding Spatial Data | S |
| EN.601.677 | CS | Causal Inference | F |
| Course # | Dept | Course Title | Semester Typically Offered |
| EN.520.612 | ECE | Machine Learning for Signal Processing (EN.520.612) | F |
| EN.520.637 | ECE | Foundations of Reinforcement Learning | F |
| EN.520.638 | ECE | Deep Learning | S |
| EN.520.647 | ECE | Information Theory | F |
| EN.520.648 | ECE | Compressed Sensing and Sparse Recovery | S |
| EN.520.651 | ECE | Random Signal Analysis (EN.520.651) | F |
| EN.520.666 | ECE | Information Extraction (EN.520.666) | S |
| EN.525.724 | EP-ECE | Introduction to Pattern Recognition (online) | F |
| EN.535.741 | EP-ME | Topics in Data Analysis | S |
| EN.553.602 | AMS | Research and Design in Applied Mathematics: Data Mining (EN.553.602) | S |
| EN.553.738 | AMS | High-Dimensional Approximation, Probability, and Statistical Learning (EN.553.738) | S |
| EN.553.740 | AMS | Machine Learning I (EN.553.740) | F |
| EN.553.741 | AMS | Machine Learning II (EN.553.741) | S |
| EN.570.654 | EHE | Geostatistics: Understanding Spatial Data | S |
| EN.601.634 | CS | Randomized and Big Data Algorithms | F |
| EN.601.674 | CS | Machine Learning: Learning Theory | F |
| EN.601.675 | CS | Machine Learning | F/S |
| EN.601.676 | CS | Machine Learning: Data to Models | S |
| EN.601.677 | CS | Causal Inference | F |
| EN.601.679 | CS | Machine Learning: Representation Learning | |
| EN.601.682 | CS | Machine Learning: Deep Learning | F |
| EN.601.780 | CS | Unsupervised Learning: Big Data to Low-Dimensional Representations | F |
| EN.625.692 | EP-ACM, EP-DS | Probabilistic Graphical Models | S |
| Course # | Dept | Course Title | Semester Typically Offered |
| EN.520.618 | ECE | Modern Convex Optimization | F |
| EN.553.665 | AMS | Introduction to Convexity (EN.553.665) | F |
| EN.553.761 | AMS | Nonlinear Optimization I (EN.553.761) | F |
| EN.553.762 | AMS | Nonlinear Optimization II (EN.553.762) | S |
| EN.553.763 | AMS | Stochastic Search and Optimization (EN.553.763) | S |
| EN.553.765 | AMS | Convex Optimization (Not Currently Offered) | |
| EN.553.766 | AMS | Combinatorial Optimization (EN.553.766) | S |
| EN.601.681 | CS | Machine Learning: Optimization | S |
| EN.625.615 | EP-ACM, EP-DS | Introduction to Optimization |
| Course # | Dept | Course Title | Semester Typically Offered |
| EN.520.617 | ECE | Computation for Engineers | S |
| EN.553.688 | AMS | Computing for Applied Mathematics (EN.553.688) | F/S |
| EN.601.619 | CS | Cloud Computing | |
| EN.601.620 | CS | Parallel Programming | F |
| EN.601.633 | CS | Intro Algorithms | F/S |
| EN.601.646 | CS | Sketching and Indexing for Sequence | S |
| EN.601.647 | CS | Computation Genomics: Sequences | F |
Electives
Four additional courses. Courses listed in the core areas may be taken to complete this requirement, provided that they are not double counted. The following provide additional options, grouped into categories (but the chosen courses may be taken from different categories).
Semester offered information is based on past offering of the courses and may be subject to changes in department programs in future years.
| Course # | Dept | Course Title | Semester Typically Offered |
| AS.410.633 | Biotech | Introduction to Bioinformatics (AS.410.633), | F/S |
| AS.410.635 | Biotech | Bioinformatics: Tools for Genome Analysis (AS.410.635) | F/S |
| AS.410.661 | Biotech | Methods in Proteomics (AS.410.661) | |
| AS.410.671 | Biotech | Gene Expression Data Analysis and Visualization (AS.410.671), | F |
| EN.520.659 | ECE | Machine Learning for Medical Application | S |
| EN.553.650 | AMS | Computational Molecular Medicine (EN.553.650) | S |
| EN.580.688 | BME | Foundations of Computational Biology and Bioinformatics | S |
| EN.605.620 | EP-CS | Algorithms for Bioinformatics | F/S |
| EN.605.621 | EP-CS | Foundations of Algorithms | F/S |
| EN.605.653 | EP-CS | Computational Genomics | F |
| EN.605.754 | EP-CS | Analysis of Gene Expression and High-Content Biological Data |
| Course # | Dept | Course Title | Semester Typically Offered |
| EN.520.614 | ECE | Image Processing and Analysis | F/S |
| EN.520.615 | ECE | Image Processing and Analysis II | S |
| EN.520.623 | ECE | Medical Image Analysis | S |
| EN.520.646 | ECE | Wavelets & Filter Banks | F |
| EN.520.648 | ECE | Compressed Sensing and Sparse Recovery | S |
| EN.525.733 | EP-ECE | Deep Learning for Computer Vision (online) | S |
| EN.553.693 | AMS | Mathematical Image Analysis | S |
| EN.601.661 | CS | Computer Vision | F/S |
| EN.601.783 | CS | Vision as Bayesian Inference | S |
| Course # | Dept | Course Title | Semester Typically Offered |
| EN.553.627 | AMS | Stochastic Processes in Finance I (EN.553.627) | F |
| EN.553.628 | AMS | Stochastic Processes in Finance II (EN.553.628) | S |
| EN.553.641 | AMS | Equity Markets and Quantitative Trading (EN.553.641) | S |
| EN.553.642 | AMS | Investment Science (EN.553.642) | F |
| EN.553.644 | AMS | Introduction to Financial Derivatives (EN.553.644) | F |
| EN.553.645 | AMS | Interest Rate and Credit Derivatives (EN.553.645) | S |
| EN.553.646 | AMS | Risk Measurement and Management in Financial Markets (EN.553.646) | F |
| EN.553.647 | AMS | Quantitative Portfolio Theory & Performance Analysis (EN.553.647) | S |
| EN.553.648 | AMS | Financial Engineering and Structured Products (EN.553.648) | S |
| EN.553.649 | AMS | Advanced Equity Derivatives | F |
| EN.553.753 | AMS | Commodities and Commodity Markets (EN.553.753) | S |
| PH.140.644 | Biostatistics | Statistical Machine Learning: Methods, Theory, and Applications |
| Course # | Dept | Course Title | Semester Typically Offered |
| EN.553.633 | AMS | Monte Carlo Methods (EN.553.633) | F |
| EN.553.738 | AMS | High-Dimensional Approximation, Probability, and Statistical Learning (EN.553.738) | S |
| EN.553.740 | AMS | Machine Learning I (EN.553.740) | F |
| EN.553.741 | AMS | Machine Learning II (EN.553.741) | S |
| EN.553.792 | AMS | Matrix Analysis (EN.553.792) | F |
| EN.601.634 | CS | Randomized and Big Data Algorithms | F |
| Course # | Dept | Course Title | Semester Typically Offered |
| EN.520.666 | ECE | Information Extraction (EN.520.666) | S |
| EN.520.680 | ECE | Speech and Auditory Processing by Humans and Machines (EN.520.680) | S |
| EN.601.665 | CS | Natural Language Processing | F |
| EN.601.769 | CS | Event Semantics in Theory and Practice | S |
| Course # | Dept | Course Title | Semester Typically Offered |
| EN.520.650 | ECE | Machine Intelligence (EN.520.650) | S |
| EN.580.691 | BME | Learning, Estimation and Control | |
| EN.601.615 | CS | Databases | |
| EN.601.663* | CS | Algorithms for Sensor-Based Robotics | |
| EN.601.666 | CS | Information Retrieval and Web Agents | |
| EN.650.683 | ISI | Cybersecurity Risk Management | S |
| *Please note the recommended pre-requisite course of EN.601.226 before registering for this course. |
Data Science Capstone Experience
For details and instructions, click here.
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