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Introduction to Computational ... - MIT OpenCourseWare
- https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0002-introduction-to-computational-thinking-and-data-science-fall-2016/
- 6.0002 is the continuation of 6.0001 Introduction to Computer Science and Programming in Python and is intended for students with little or no programming experience.
6.0002 Introduction to Computational Thinking and Data ...
- https://www.eecs.mit.edu/academics-admissions/academic-information/subject-updates-ft-2014/60002
- DESCRIPTION Provides an introduction to using computation to understand real-world phenomena. Topics include plotting, stochastic programs, probability and statistics, random walks, Monte Carlo simulations, modeling data, optimization problems, and clustering. Combination of 6.0001 and 6.0002 counts as REST subject.
6.0001/2 CAT-SOOP - Massachusetts Institute of Technology
- https://sicp-s1.mit.edu/spring20/information
- Apr 04, 2020 · 6.0002 (6 units): second half of term, with 3 microquizzes and a final exam in-class. All course material is linked from this site. The amount of work 6.0001 and 6.0002 require is equivalent to a 12 credit, full semester class. 3) Goals
6.0001 and 6.0002 including Information About Advanced ...
- https://www.eecs.mit.edu/node/6215
- 6.0001 is a six unit subject taught in the first half of both the fall and spring semesters. Combined with 6.0002, which is taught in the second half of each term, it satisfies a REST requirement. The combination also satisfies degree requirements for several departments, including courses 9, …
6.0001+2
- https://sicp-s1.mit.edu/spring21
- May 21, 2021 · Help Queue Programming Resources General MIT Help Forum 6.0002 MITx 6.0002. ... Finished with 6.0002 Psets! Recitation Schedule. Login to view: Zoom Fridays at: 10am, 11am, 1pm Recitation Feedback Form. Calendar and Materials 6.0002 - Spring 2021 View 6.0001 Calendar
MIT6 0002F16 Lec2 Algorithms And Data Structures ...
- https://www.scribd.com/document/482247522/MIT6-0002F16-lec2-pdf
- Op#miza#on Problems, John Gu7ag MIT Department of Electrical Engineering and Computer Science 6.0002 LECTURE 2 1 Relevant Reading for Today’s Lecture § Chapter 13 6.0002 LECTURE 2 2 The Pros and Cons of Greedy § Easy to implement § Computa<onally efficient § But …