Computer Science, Economics, and Data Science (Course 6-14P)

Department of Electrical Engineering and Computer Science

Department of Economics

Master of Engineering in Computer Science, Economics, and Data Science

This Master of Engineering degree is awarded only to students who have already received, or who will simultaneously receive, the Bachelor of Science in Computer Science, Economics, and Data Science (Course 6-14). Refer to the undergraduate degree chart for requirements. 

The graduate component of the MEng program is described below.

Course 6-14P Graduate Requirements

Required Subjects
6.THMMaster of Engineering Program Thesis24
6.9830Professional Perspective Internship1
Restricted Electives
Four graduate subjects totaling at least 42 units, which include two subjects from the EECS advanced subjects and two from the economics advanced subjects42
Two subjects from the list of mathematics restricted electives24
Total Units91

Economics Advanced Subjects

Microeconomic Theory I
and Microeconomic Theory II
14.131Psychology and Economics12
14.137[J]Psychology and Economics12
14.161Strategy and Information12
14.200Industrial Organization: Competitive Strategy and Public Policy12
14.260Organizational Economics12
14.270Economics and E-Commerce12
Statistical Method in Economics
and Estimation and Inference for Linear Causal and Structural Models
14.387Applied Econometrics6
14.388Inference on Causal and Structural Parameters Using ML and AI12
14.420Environmental Policy and Economics12
14.444[J]Energy Economics and Policy12
14.540International Trade12
14.640Labor Economics and Public Policy12
14.750Political Economy and Economic Development12
14.760Firms, Markets, Trade and Growth12

 EECS Advanced Subjects

6.3702Introduction to Probability12
6.3722Introduction to Statistical Data Analysis12
6.3732[J]Statistics, Computation and Applications12
6.4132[J]Principles of Autonomy and Decision Making12
6.5080Multicore Programming12
6.5210[J]Advanced Algorithms12
6.5220[J]Randomized Algorithms12
6.5230Advanced Data Structures12
6.5250[J]Distributed Algorithms12
6.5310Geometric Folding Algorithms: Linkages, Origami, Polyhedra12
6.5340Topics in Algorithmic Game Theory12
6.5400[J]Theory of Computation12
6.5620[J]Cryptography and Cryptanalysis12
6.6630[J]Control of Manufacturing Processes12
6.7200[J]Optimization Methods12
6.7210[J]Introduction to Mathematical Programming12
6.7240Game Theory with Engineering Applications12
6.7260Network Science and Models12
6.7300[J]Introduction to Modeling and Simulation12
6.7310[J]Introduction to Numerical Methods12
6.7320[J]Parallel Computing and Scientific Machine Learning12
6.7330[J]Numerical Methods for Partial Differential Equations12
6.7450[J]Data-Communication Networks12
6.7470Information Theory12
6.7700[J]Fundamentals of Probability12
6.7710Discrete Stochastic Processes12
6.7720[J]Discrete Probability and Stochastic Processes12
6.7800Inference and Information12
6.7810Algorithms for Inference12
6.7900Machine Learning12
6.7910[J]Statistical Learning Theory and Applications12
6.7930[J]Machine Learning for Healthcare12
6.7940Dynamic Programming and Reinforcement Learning12
6.8300Advances in Computer Vision12
6.8610Quantitative Methods for Natural Language Processing12

Mathematics Restricted Electives

Probability and Statistics (maximum of 1)
6.3800Introduction to Inference12
18.650[J]Fundamentals of Statistics12
Discrete Mathematics
18.200APrinciples of Discrete Applied Mathematics12
Linear Algebra
18.700Linear Algebra12
Complex Variables (maximum of 1)
18.04Complex Variables with Applications12
18.0751Methods for Scientists and Engineers12
Real Analysis (maximum of 1)
18.1001Real Analysis12
18.1002Real Analysis12
Other Subjects
18.0851Computational Science and Engineering I12
18.0861Computational Science and Engineering II12
18.330Introduction to Numerical Analysis12
18.781Theory of Numbers12