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Computer Science and Programming
- Lecture 24 - Course overview: What do computer scientists do?
- Lecture 23 - Stock market simulation
- Lecture 22 - Normal, uniform, and exponential distributions
- Lecture 21 - Validating simulation results
- Lecture 20 - Monte Carlo simulations
- Lecture 19 - Biased random walks
- Lecture 18 - Presenting simulation results
- Lecture 17 - Computational models
- Lecture 16 - Encapsulation
- Lecture 15 - Abstract data types
- Lecture 14 - Introduction to object-oriented programming
- Lecture 13 - Dynamic programming
- Lecture 12 - Knapsack problem
- Lecture 11 - Testing and debugging
- Lecture 10 - Divide and conquer methods
- Lecture 9 - Binary search
- Lecture 8 - Complexity
- Lecture 7 - Lists and mutability
- Lecture 6 - Bisection methods
- Lecture 5 - Floating point numbers
- Lecture 4 - Decomposition and abstraction through functions
- Lecture 3 - Common code patterns
- Lecture 2 - Operators and operands