Welcome to MIT 18.S191 aka 6.S083 aka 22.S092, Spring 2021 edition! For older semester, see the Fall 2020 branch or older content.
This is an introductory course on Computational Thinking. We use the Julia programming language to approach real-world problems in varied areas applying data analysis and computational and mathematical modeling. In this class you will learn computer science, software, algorithms, applications, and mathematics as an integrated whole.
Topics include:
- Image analysis
- Machine Learning?
- Network theory
- Climate modeling
Lecturers: Alan Edelman, David P. Sanders, Charles E. Leiserson, Henri F. Drake
Teaching assistants: Bola Malek
Technical assistants: Fons van der Plas, Logan Kilpatrick
Guest lecturers: to be announced
Course materials will be published on this website on Monday 1:00pm. Each week is a new chapter, which includes:
- Asynchronous video lectures (total 60 minutes)
- Interactive visualizations
- Exercises
On Monday 1:00pm - 2:30pm, after the material is published, there will also be:
- Q&A on Discord
- Live overview lecture (30 minutes)
On Wednesday 1:00pm 2:30pm (MIT students only), you will meet with fellow students and your TA to:
- Review the lecture
- Work on problem sets in small groups or individually, with the opportunity to ask questions to your TA
Start date: February 16, 2021
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Discord: discussion (we encourage you to hang out here during class!)
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Piazza: (MIT only) questions, discussion with staff, announcements
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Canvas: (MIT only) homework submissions. If you're a non-MIT student, don't worry, the homework has built-in answers checks, or you can find a partner to cross-grade homeworks via Discord.
The final grade is 80% problem sets, and 20% MITx quick questions.
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Problem sets are released on Tuesdays and due before Sunday (11:59pm). They have equal weight; your lowest score will be dropped.
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MITx exercises (quick questions) are due before Wednesday (11:59pm), but are best done on Monday, during or right after the lectures.