10-ENG : Engineering Computation

Concentrations:  Biomedical  ||  Energy  || Engineering Computation || Environment & Sustainability || Manufacturing Design ||  Materials || Process Data Analytics

Course 10-ENG: Bachelor of Science in Engineering with Concentration

Engineering Computation

Computation has become an increasingly important tool in engineering. Today computational techniques are more effective and less expensive than experiments for the solution of many engineering problems, and are useful complements to experiments for most of the remaining problems. Computation is commonly used to provide insights that go beyond purely experimental studies. This concentration covers fundamental concepts, techniques, tools, and applications of engineering computation.

Note: Students can get the CS minor by taking four additional courses (for details, see https://www.eecs.mit.edu/academics/undergraduate-programs/minor-in-computer-science/)

Students in this concentration are required to take four subjects from four categories. Although not required, students are encouraged to take

10.34 Numerical Methods Applied to Chemical Engineering

as one of their technical electives.

A. Introduction to Programming (select at least one)

Number Name Units GIR Prerequisites
6.100A Introduction to Computer Science Programming in Python 6    
6.100L Introduction to Computer Science and Programming 9    

B. Computational Mathematics (select at least one)

Number Name Units GIR Prerequisites
6.1200[J] Mathematics for Computer Science 12 REST Calculus I (GIR)
18.200/18.200A Principles of Discrete Applied Mathematics 15/12    

C. Introduction to Applications (select at least one)

Number Name Units GIR Prerequisites
6.9080 Introduction to EECS via Robotics   12 LAB 6.100A or permission of instructor
6.3400 Introduction to EECS via Communications Networks 12 LAB 6.100A
6.4900 Introduction to EECS via Medical Technology 12 LAB Calculus II (GIR) and Physics II (GIR)
6.9010 Introduction to EECS via Interconnected Embedded Systems 12 LAB  
6.C01 + 10.C01   Modeling with Machine Learning: from Algorithms to Applications; Machine Learning for Molecular Engineering 12   Calculus II (GIR) and 6.100A

 D. Computational Engineering (select at least one)

Number Name Units GIR Prerequisites
2.086 Numerical Computation for Mechanical Engineers   12 REST Calculus II (GIR) and Physics I (GIR)
6.4100 Artificial Intelligence   12   6.100A
10.437[J] Computational Chemistry   12    
18.085 Computational Science and Engineering I   12   Calculus II (GIR) and (18.03 or 18.032)
18.086 Computational Science and Engineering II   12   Calculus II (GIR) and (18.03 or 18.032)

Approved Graduate Subject Alternatives

Number Name Units GIR Prerequisites
2.097[J] Numerical Methods for Partial Differential Equations 12   18.03 or 18.06
10.34 Numerical Methods Applied to Chemical Engineering 9   Permission of instructor