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6.0002 Introduction to Computational Thinking and Data Science (Fall 2016, MIT OCW). Instructors: Prof. Eric Grimson and Prof. John Guttag.
FREE
This course includes
Hours of videos
416 years, 7 months
Units & Quizzes
15
Unlimited Lifetime access
Access on mobile app
Certificate of Completion
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. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language. (from ocw.mit.edu)
Course Currilcum
- Lecture 01 – Introduction and Optimization Problems Unlimited
- Lecture 02 – Optimization Problems Unlimited
- Lecture 03 – Graph-theoretic Models Unlimited
- Lecture 04 – Stochastic Thinking Unlimited
- Lecture 05 – Random Walks Unlimited
- Lecture 06 – Monte Carlo Simulation Unlimited
- Lecture 07 – Confidence Intervals Unlimited
- Lecture 08 – Sampling and Standard Error Unlimited
- Lecture 09 – Understanding Experimental Data Unlimited
- Lecture 10 – Understanding Experimental Data (cont.) Unlimited
- Lecture 11 – Introduction to Machine Learning Unlimited
- Lecture 12 – Clustering Unlimited
- Lecture 13 – Classification Unlimited
- Lecture 14 – Classification and Statistical Sins Unlimited
- Lecture 15 – Statistical Sins and Wrap Up Unlimited
