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6.00SC Introduction to Computer Science and Programming (Spring 2011, MIT OCW). Instructor: Professor John Guttag.

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September 25, 2023

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September 25, 2023

Duration:

Unlimited Duration

FREE

This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration

Description

6.00SC Introduction to Computer Science and Programming (Spring 2011, MIT OCW). Instructor: Professor John Guttag.

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language. (from ocw.mit.edu)

Course Curriculum

    • Lecture 01 – Introduction to 6.00 Unlimited
    • Lecture 02 – Core Elements of a Program Unlimited
    • Lecture 03 – Problem Solving Unlimited
    • Lecture 04 – Machine Interpretation of a Program Unlimited
    • Lecture 05 – Objects in Python Unlimited
    • Lecture 06 – Recursion Unlimited
    • Lecture 07 – Debugging Unlimited
    • Lecture 08 – Efficiency and Order of Growth Unlimited
    • Lecture 09 – Memory and Search Methods Unlimited
    • Lecture 10 – Hashing and Classes Unlimited
    • Lecture 11 – OOP and Inheritance Unlimited
    • Lecture 12 – Introduction to Simulation and Random Walks Unlimited
    • Lecture 13 – Some Basic Probability and Plotting Data Unlimited
    • Lecture 14 – Sampling and Monte Carlo Simulation Unlimited
    • Lecture 15 – Statistical Thinking Unlimited
    • Lecture 16 – Using Randomness to Solve Non-random Problems Unlimited
    • Lecture 17 – Curve Fitting Unlimited
    • Lecture 18 – Optimization Problems and Algorithms Unlimited
    • Lecture 19 – More Optimization and Clustering Unlimited
    • Lecture 20 – More Clustering Unlimited
    • Lecture 21 – Using Graphs to Model Problems, Part 1 Unlimited
    • Lecture 22 – Using Graphs to Model Problems, Part 2 Unlimited
    • Lecture 23 – Dynamic Programming Unlimited
    • Lecture 24 – Avoiding Statistical Fallacies Unlimited
    • Lecture 25 – Queuing Network Models Unlimited
    • Lecture 26 – What Do Computer Scientists Do? Unlimited

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