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 MIT Public Course: Introduction to Computer Science and Programming

MIT Public Course: Introduction to Computer Science and Programming

Welcome to the 24 episodes of this course

Lecturer: Prof Eric Grimson Prof. John Guttag -Professor in the Department of Computer Science and Engineering at MIT - Bachelor of Science in Mathematics and Physics at Regina University, Doctor of Science in Mathematics at MIT

College introduction: West Carolina State University was founded in 1889 to provide higher education and career opportunities for the western region of North Carolina. Since its establishment, WCU has mainly focused on culture, science and education.

Course introduction: This course is suitable for students with little or no programming experience. It is committed to making students understand the role of computers in solving problems, and helping students, regardless of their major, to be confident about the goal of completing useful small programs.

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【 Episode 1 】 Course objectives, data types, operations, variables

MIT Open Class: Introduction to Computer Science and Programming - Course Objectives, Data Types, Operations, Variables

[Episode 2] Branches, conditions and loops

MIT Open Class: Introduction to Computer Science and Programming - Branches, Conditions and Cycles

[Episode 3] General code style, circular program

MIT Open Class: Introduction to Computer Science and Programming - General Code Styles, Cyclic Programming

【 Episode 4 】 Introduction to Function Abstraction and Recursion

MIT Public Course: Introduction to Computer Science and Programming Introduction to Function Abstraction and Recursion

[Episode 5] Floating point numbers and dichotomy (successive approximation)

MIT Public Course: Introduction to Computer Science and Programming - Floating Point and Dichotomy (Successive Approximation)

[Episode 6] Dichotomy, Newton, Lagrangian method, introduction to arrays

MIT Public Course: Introduction to Computer Science and Programming - Dichotomy, Newton, Lagrangian Method, Introduction to Arrays

[Episode 7] Array and variability, dictionary, pseudo code, introduction to code operation efficiency

MIT Public Course: Introduction to Computer Science and Programming - Array and Variability, Dictionary, Pseudocode, Introduction to Code Operating Efficiency

[Set 8] Algorithm complexity: logarithmic, linear, square, exponential

MIT Public Course: Introduction to Computer Science and Programming Algorithm Complexity: Logarithmic, Linear, Square, Exponential

[Episode 9] Dichotomy search, bubble sorting and selection sorting

MIT Public Course: Introduction to Computer Science and Programming Dichotomy Search, Bubble Sorting and Selective Sorting

[Episode 10] Divide and conquer, merge and sort, exception

MIT Open Class: Introduction to Computer Science and Programming - divide and conquer, merge and sort, anomaly

[Episode 11] Testing and Commissioning

MIT Public Course: Introduction to Computer Science and Programming - Testing and Debugging

[Episode 12] More about debugging: knapsack problem, introduction to dynamic programming

MIT Public Course: Introduction to Computer Science and Programming More about Debugging: Backpack Problems, Introduction to Dynamic Programming

[Episode 13] Dynamic programming, overlapping subproblems, optimal substructure

MIT Open Class: Introduction to Computer Science and Programming - Dynamic Programming, Overlapping Subproblems, Optimal Substructure

【 Episode 14 】 Analysis of knapsack problem, introduction to object-oriented programming

MIT Public Course: Introduction to Computer Science and Programming - Analysis of Backpack Problems, Introduction to Object Oriented Programming

【 Episode 15 】 Abstract data types, classes and methods

MIT Public Course: Introduction to Computer Science and Programming - Abstract Data Types, Classes and Methods

【 Episode 16 】 Encapsulation, inheritance, mapping

MIT Public Course: Introduction to Computer Science and Programming - Encapsulation, Inheritance, Mapping

[Episode 17] Calculation model: random walking simulation

MIT Public Course: Introduction to Computer Science and Programming - Computing Models - Random Walk Simulation

【 Episode 18 】 represents the simulation results Pylab and Drawing

MIT Open Class: Introduction to Computer Science and Programming - Representing Simulation Results Pylab and Drawing

【 Episode 19 】 Random walk with preference and probability distribution

MIT Public Course: Introduction to Computer Science and Programming - Random Walk with Preference and Probability Distribution

【 Episode 20 】 Statistical test simulation program predicts pi value

MIT Public Course: Introduction to Computer Science and Programming - Predicting pi Values by Statistical Experiment Simulation Program

【 Episode 21 】 Verification of simulation program results. Linear regression. Curve fitting

MIT Public Course: Introduction to Computer Science and Programming - Verification of Simulation Program Results, Linear Regression, Curve Fitting

【 Episode 22 】 Normal distribution Uniform distribution and exponential distribution

MIT Public Course: Introduction to Computer Science and Programming - Normal Distribution Uniform Distribution and Exponential Distribution

【 Episode 23 】 Stock Market Simulation

MIT Public Course: Introduction to Computer Science and Programming Stock Market Simulation

[Episode 24] What Computer Scientists Do

MIT Open Class: Introduction to Computer Science and Programming - What Computer Scientists Do

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