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Introduction to Computer Science and Programming
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Introduction to Computer Science and Programming

Author: Eric Grimson, John Guttag

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Description

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.
24 Episodes
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Lecture 10: Divide and conquer methods, merge sort, exceptions

Lecture 10: Divide and conquer methods, merge sort, exceptions

2016-08-0546:18

Lecture 03: Common code patterns: iterative programs

Lecture 03: Common code patterns: iterative programs

2016-08-0550:59

Lecture 23: Stock market simulation

Lecture 23: Stock market simulation

2015-04-0851:091

Lecture 24: Course overview; what do computer scientists do?

Lecture 24: Course overview; what do computer scientists do?

2015-04-0842:47

Lecture 22: Normal, uniform, and exponential distributions; misuse of statistics

Lecture 22: Normal, uniform, and exponential distributions; misuse of statistics

2015-04-0850:492

Lecture 21: Validating simulation results, curve fitting, linear regression

Lecture 21: Validating simulation results, curve fitting, linear regression

2015-04-0853:47

Lecture 19: Biased random walks, distributions

Lecture 19: Biased random walks, distributions

2015-04-0849:53

Lecture 20: Monte Carlo simulations, estimating pi

Lecture 20: Monte Carlo simulations, estimating pi

2015-04-0847:54

Lecture 18: Presenting simulation results, Pylab, plotting

Lecture 18: Presenting simulation results, Pylab, plotting

2015-04-0852:53

Lecture 17: Computational models: random walk simulation

Lecture 17: Computational models: random walk simulation

2015-04-0849:23

Lecture 16: Encapsulation, inheritance, shadowing

Lecture 16: Encapsulation, inheritance, shadowing

2015-04-0850:22

Lecture 15: Abstract data types, classes and methods

Lecture 15: Abstract data types, classes and methods

2015-04-0850:24

Lecture 13: Dynamic programming: overlapping subproblems, optimal substructure

Lecture 13: Dynamic programming: overlapping subproblems, optimal substructure

2015-04-0848:55

Lecture 09: Binary search, bubble and selection sorts

Lecture 09: Binary search, bubble and selection sorts

2015-04-0847:30

Lecture 08: Complexity; log, linear, quadratic, exponential algorithms

Lecture 08: Complexity; log, linear, quadratic, exponential algorithms

2015-04-0850:03

Lecture 14: Analysis of knapsack problem, introduction to object-oriented programming

Lecture 14: Analysis of knapsack problem, introduction to object-oriented programming

2015-04-0850:33

Lecture 12: More about debugging, knapsack problem, introduction to dynamic programming

Lecture 12: More about debugging, knapsack problem, introduction to dynamic programming

2015-04-0849:46

Lecture 07: Lists and mutability, dictionaries, pseudocode, introduction to efficiency

Lecture 07: Lists and mutability, dictionaries, pseudocode, introduction to efficiency

2015-04-0846:22

Lecture 11: Testing and debugging

Lecture 11: Testing and debugging

2015-04-0848:59

Lecture 02: Operators and operands; statements; branching, conditionals, and iteration

Lecture 02: Operators and operands; statements; branching, conditionals, and iteration

2015-04-0850:49

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