以前本站推薦過麻省理工的C/C++的課程，今天在他們的網(wǎng)站看到上有一組關(guān)于計算機(jī)科學(xué)和編程導(dǎo)論的免費公開課（視頻是Youtube的），我看了幾個課程，我覺得講得很系統(tǒng)啊，而且有一點一通百通的感覺。雖然是理論課，但是可以感到我國的教育還是有很大差距的。這個組課程推薦給大家（需要翻墻），視頻都有字幕，計算機(jī)科學(xué)系畢業(yè)的同學(xué)應(yīng)該會很容易聽懂。強(qiáng)烈推薦。（網(wǎng)友Aslan指出已經(jīng)有人搬運到優(yōu)酷上了，鏈接在這里，遺憾的是沒有字幕，另外，不知道為什么會說是Python學(xué)習(xí)）
1: Introduction and Goals; Data Types, Operators, and Variables |
2: Branching, Conditionals, and Iteration |
3: Common Code Patterns: Iterative Programs |
4: Abstraction through Functions; Introduction to Recursion |
5: Floating Point Numbers, Successive Refinement, Finding Roots |
6: Bisection Methods, Newton/Raphson, Introduction to Lists |
7: Lists and Mutability, Dictionaries, Introduction to Efficiency |
8: Complexity: Log, Linear, Quadratic, Exponential Algorithms |
9: Binary Search, Bubble and Selection Sorts |
10: Divide and Conquer Methods, Merge Sort, Exceptions |
11: Testing and Debugging |
12: Debugging, Knapsack Problem, Introduction to Dynamic Programming |
13: Dynamic Programming: Overlapping Subproblems, Optimal Substructure |
14: Introduction to Object-oriented Programming |
15: Abstract Data Types, Classes and Methods |
16: Encapsulation, Inheritance, Shadowing |
17: Computational Models: Random Walk Simulation |
18: Presenting Simulation Results, Pylab, Plotting |
19: Biased Random Walks, Distributions |
20: Monte Carlo Simulations, Estimating pi |
21: Validating Simulation Results, Curve Fitting, Linear Regression |
22: Normal, Uniform, and Exponential Distributions |
23: Stock Market Simulation |
24: Course Overview; What Do Computer Scientists Do? |
