18.0002: Introduction to Computational Science and Engineering

Table of contents

  1. Course Info
  2. Realistic Prerequisites
  3. Subject Matter
  4. Course Staff
  5. Lectures
  6. Problem Sets
  7. Exams
  8. Resources
  9. Grading
  10. Advice to Future Students

Course Info

Class Size 26
Hours/Week 8.3 (13 responses)
Instructors Youssef Marzouk and Laurent Demanet
Overall Rating 5.6/7.0

Realistic Prerequisites

  • Students should know 18.01, and some knowledge of 18.02 (for instance by taking it at the same time at least) is useful as well.
  • Programming experience (in Python) is necessary. 6.0001 should be enough in this regard.

Subject Matter

  • The material was found to be very applied, broad, and useful.
  • The course covers “lots of applying models to real world simulations and applications.”

Course Staff

  • The course staff were always willing to help and responded quickly.
  • The staff were caring and approachable, going so far as to “answer questions slightly outside the scope of the class on their own time (Piazza).”

Lectures

  • The lectures “were the most helpful,” but some also found the finger exercises after each lecture to also be important for solidifying information.

Problem Sets

  • Students found the problem sets fun, challenging, and interesting in their applications to real world situations.
  • Students spent anywhere from 1.5 to 6 hours on a given pset (according to those who responded).

Exams

  • The microquizzes had “no significant time pressure” and the lectures were good preparation.
  • The microquizzes were open book, so students made sure to know where to find information when necessary.

Resources

  • MITx had everything that was needed, including the course notes as a PDF.
  • Sometimes students made use of other references such as numpy.

Grading

  • Grading was considered fair, and a microquiz grade was dropped. Some found it annoying that the grading was just a score, and not feedback.

Advice to Future Students

  1. “Try to focus more on the numerical methods and less on the models themselves. Model formulations are better treated in the classes specific to the model (e.g. take drag formula as given for now and wait for 16.03 (fluids) to understand fully).”
  2. “Don’t hesitate to reach out to the instructions about any questions or difficulties, or anything for that matter.”
  3. “Be prepared for some math beyond 18.01. However, the course is still very interesting and applicable to many fields.It is worth taking if the math isn’t a hinderance.”