MITx's Introduction to Computer Science and Programming Using Python

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List of Lecture Topics

Lecture 1 – Introduction: • What a computer does • Computational thinking • Aspects of programming languages • Basic machine architecture

Lecture 2 – Core elements of programs: • Kinds of languages • Objects, expressions, operators • Abstraction by naming • Strings • Scripts • Straightline programs • Branching programs

Lecture 3 – Simple algorithms: • Simple programs • Iteration • Input • Exhaustive enumeration • Guess and check • For and while loops • Approximate solutions • Bisection search • Newton-Raphson Lecture 4 – Functions: • Function syntax • Abstraction by specification • Functions and scoping • Floating point numbers • Specifications • Modules

Lecture 5 – Recursion: • Recursion • Inductive reasoning • Divide and conquer

Lecture 6 – Objects: • Structured types and mutability • Tuples • Lists and mutability • Functions as objects • Dictionaries

Lecture 7 – Debugging: • Testing and debugging • Black box testing • Glass box testing • Integration testing and unit testing • Debugging with binary search

Lecture 8 – Assertions and Exceptions • Assertions • Exceptions

Lecture 9 – Efficiency and orders of growth: • Complexity • How to measure complexity • Asymptotic notation

Lecture 10 – Memory and search: • Memory storage • Indirection • Searching and sorting methods • Hashing

Lecture 11 – Classes: • Definition of classes • Classes versus instances • Methods • Bindings of values • Exceptions

Lecture 12 – Object Oriented Programming and Inheritance: • Inheritance • Object oriented programming

Lecture 13 – Trees: • Decision trees • Depth-first search • Breadth-first search

Lecture 14 – Summary

Lecture 15 – Research videos