Want to attend a full MIT course on Computer Science and Programming?

This is professor Eric Grimson. He teaches "Introduction to Computer Science and Programming". https://i.imgur.com/0AMXsTp.jpg Lecture 1: What is computation; introduction to data types, operators, and variables. https://www.youtube.com/watch?v=k6U-i4gXkLM Lecture 2: Operators and operands; statements; branching, conditionals, and iteration https://www.youtube.com/watch?v=Pij6J0HsYFA Lecture 3: Common code patterns: iterative programs https://www.youtube.com/watch?v=X6ilT3uUOBo Lecture 4: Decomposition and abstraction through functions; introduction to recursion https://www.youtube.com/watch?v=SXR9CDof7qw Lecture 5: Floating point numbers, successive refinement, finding roots https://www.youtube.com/watch?v=Pfo7r6bjSqI Lecture 6: Bisection methods, Newton/Raphson, introduction to lists https://www.youtube.com/watch?v=hVHqs38fPe8 Lecture 7: Lists and mutability, dictionaries, pseudocode, introduction to efficiency https://www.youtube.com/watch?v=tuRYbBvOMRo Lecture 8: Complexity; log, linear, quadratic, exponential algorithms https://www.youtube.com/watch?v=ewd7Lf2dr5Q Lecture 9: Binary search, bubble and selection sorts https://www.youtube.com/watch?v=UNHQ7CRsEtU Lecture 10: Divide and conquer methods, merge sort, exceptions https://www.youtube.com/watch?v=kDhR4Zm53zc Lecture 11: Testing and debugging https://www.youtube.com/watch?v=DkPsD58nUIE Lecture 12: More about debugging, knapsack problem, introduction to dynamic programming https://www.youtube.com/watch?v=udnyuHzJsjM Lecture 13: Dynamic programming: overlapping subproblems, optimal substructure https://www.youtube.com/watch?v=ZKBUu_ahSR4 Lecture 14: Analysis of knapsack problem, introduction to object-oriented programming https://www.youtube.com/watch?v=le8tpXQyYcM Lecture 15: Abstract data types, classes and methods https://www.youtube.com/watch?v=y81AhLQN-NI Lecture 16: Encapsulation, inheritance, shadowing https://www.youtube.com/watch?v=Q8SoG1OIveU Lecture 17: Computational models: random walk simulation https://www.youtube.com/watch?v=ZbIpjf0QEPI Lecture 18: Presenting simulation results, Pylab, plotting https://www.youtube.com/watch?v=QJ_MPc0TobI Lecture 19: Biased random walks, distributions https://www.youtube.com/watch?v=IZaAUwW7OsU Lecture 20: Monte Carlo simulations, estimating pi https://www.youtube.com/watch?v=ENrAsRoR97I Lecture 21: Validating simulation results, curve fitting, linear regression https://www.youtube.com/watch?v=SuOIpJnn888 Lecture 22: Normal, uniform, and exponential distributions; misuse of statistics https://www.youtube.com/watch?v=WGDbIKtjmSs Lecture 23: Stock market simulation https://www.youtube.com/watch?v=raTzkzML31w Lecture 24: Course overview; what do computer scientists do? https://www.youtube.com/watch?v=2q--tAPkVXI