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Introduction to Computer Science and Programming [FS]
Introduction to Computer Science and Programming particularly MIT 2009
This guinea-pig is aimed at students with little or no programming experience. It aims to provide students with an understanding of the function computation can play in solving problems. It also aims to oppose be on the side of students, regardless of their major, to quality justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The grade will use the Pythonв„ў programming language. 01- Goals of the course; what is computation; introduction to data types, operators, and variables Download Links : http://www.fileserve.com/file/wQfY3Xe/introduction_to_computer_science.part1.rar No Password Introduction to Computer Science and Programming [FS]
English | MP4 | MPEG 304 kbps 15 fps | 480 x 360 | AAC 128 kbps 44 KHz Stereo | 2.53 GB
Genre: elearning
02- Operators and operands; statements; branching, conditionals, and iteration
03- Common code patterns: iterative programs
04- Decomposition and abstraction fully functions; introduction to recursion
05- Floating point numbers, continuous refinement, finding roots
06- Bisection methods, Newton/Raphson, introduction to lists
07- Lists and mutability, dictionaries, pseudocode, introduction to effectiveness
08- Complexity; log, linear, quadratic, exponential algorithms
09- Binary search, boil and selection sorts
10- Divide and conquer methods, pool sort, exceptions
11- Testing and debugging
12- More more debugging, knapsack problem, introduction to dynamic programming
13- Dynamic programming: overlapping subproblems, optimal substructure
14- Analysis of knapsack problem, introduction to object-oriented programming
15- Abstract data types, classes and methods
16- Encapsulation, inheritance, shadowing
17- Computational models: random strut 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; barbarism of statistics
23- Stock market simulation
24- Course overview; what do computer scientists do?
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