‘18.C06: Linear Algebra and Optimization’
Table of contents
- Course Info
- Realistic Prerequisites
- Subject Matter
- Course Staff
- Lectures
- Problem Sets
- Exams
- Resources
- Grading
- Advice to Future Students
Course Info
Class Size | 160 |
Hours/Week | 10.7 (54 responses) |
Instructors | Ankur Moitra, Pablo A. Parrilo |
Overall Rating | 5.2/7.0 |
Realistic Prerequisites
- Some programming background is highly recommended, such as Python in 6.100A.
- General calculus, such as 18.01 and 18.02, is also recommended.
Subject Matter
- Most felt that this class was deep and foundational.
- Students generally agree that the class is mostly applied, but this didn’t translate to practical in some cases.
Course Staff
- Reviews for the course staff were mixed.
- Some students felt that the course staff were not approachable, and unhelpful at times on Piazza and in person, especially when it came to Julia programming questions.
- Some students felt that the course staff were engaging and very understanding.
Lectures
- Students agree that the lectures were essential for learning the material.
- Lectures were recorded.
Problem Sets
- Challenging.
- Lectures were generally not enough to fully prepare for the psets, and often felt too disconnected from the lecture material.
Exams
- The exams were considered difficult to finish due to time pressure. However, the letter cutoffs were adjusted appropriately
- Problems usually ranged from easy to very difficult.
Resources
- Lectures were recorded, and lecture notes from a previous semester were made available on Canvas.
- There is no textbook.
Grading
- Students felt that grading was very fair and generous.
- Students complained about the amount of time for grades to come out.
Advice to Future Students
- “Go to lecture and especially recitations, do not skip.”
- “Invest time into learning Julia at the very beginning.”
- “Consider taking plain 18.06 instead.”