MIT 6.00 Introduction to Computer Science and Programming - Fall 2008

MIT 6.00 Introduction to Computer Science and Programming - Fall 2008

24 Videos · Sep 3, 2008

About

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.

Course Homepage: 16.00 Introduction to Computer Science and Programming

Course features at MIT OpenCourseWare page: *Exams *Assignments

Videos

video-img
50:59

Lecture 3: Common code patterns: iterative programs

Eric Grimson

Apr 17, 2010

 · 

11395 views

video-img
50:02

Lecture 8: Complexity; log, linear, quadratic, exponential algorithms

Eric Grimson

Apr 17, 2010

 · 

7876 views

video-img
53:29

Lecture 1: Goals of the course; what is computation; introduction to data types,...

Eric Grimson

Apr 17, 2010

 · 

51970 views

video-img
48:55

Lecture 13: Dynamic programming: overlapping subproblems, optimal substructure

John Guttag

Apr 17, 2010

 · 

6965 views

video-img
50:22

Lecture 16: Encapsulation, inheritance, shadowing

Eric Grimson

Apr 17, 2010

 · 

4510 views

video-img
48:58

Lecture 11: Testing and debugging

John Guttag

Apr 17, 2010

 · 

5974 views

video-img
46:18

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

Eric Grimson

Apr 17, 2010

 · 

6434 views

video-img
49:22

Lecture 17: Computational models: random walk simulation

John Guttag

Apr 17, 2010

 · 

5825 views

video-img
46:21

Lecture 7: Lists and mutability, dictionaries, pseudocode, introduction to effic...

Eric Grimson

Apr 17, 2010

 · 

6815 views

video-img
50:33

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

John Guttag

Apr 17, 2010

 · 

7212 views

video-img
50:49

Lecture 2: Operators and operands; statements; branching, conditionals, and iter...

Eric Grimson

Apr 17, 2010

 · 

18508 views

video-img
49:46

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

John Guttag

Apr 17, 2010

 · 

6718 views

video-img
51:09

Lecture 23: Stock market simulation

John Guttag

Apr 17, 2010

 · 

13273 views

video-img
50:24

Lecture 15: Abstract data types, classes and methods

Eric Grimson

Apr 17, 2010

 · 

5000 views

video-img
53:47

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

John Guttag

Apr 17, 2010

 · 

5714 views

video-img
47:29

Lecture 9: Binary search, bubble and selection sorts

Eric Grimson

Apr 17, 2010

 · 

5776 views

video-img
52:53

Lecture 18: Presenting simulation results, Pylab, plotting

John Guttag

Apr 17, 2010

 · 

4266 views

video-img
50:48

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

John Guttag

Apr 17, 2010

 · 

4645 views

video-img
47:54

Lecture 20: Monte Carlo simulations, estimating

John Guttag

Apr 17, 2010

 · 

8141 views

video-img
42:47

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

John Guttag

Apr 17, 2010

 · 

4761 views

video-img
49:52

Lecture 19: Biased random walks, distributions

John Guttag

Apr 17, 2010

 · 

4038 views

video-img
51:26

Lecture 4: Decomposition and abstraction through functions; introduction to recu...

Eric Grimson

Apr 17, 2010

 · 

9681 views

video-img
44:12

Lecture 5: Floating point numbers, successive refinement, finding roots

John Guttag

Apr 17, 2010

 · 

7494 views

video-img
50:10

Lecture 6: Bisection methods, Newton/Raphson, introduction to lists

John Guttag

Apr 17, 2010

 · 

7426 views