Resource Index

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This resource index gives users access to most of the course resources in a single location.

Unit 1

TITLES	LECTURE VIDEOS	LECTURE SLIDES	LECTURE RESOURCES	RECITATION VIDEOS	PROBLEM SETS	FURTHER STUDY LINKS
Introduction to 6.00	Lecture 1: Introduction to 6.00	Lecture slides (PDF)	None	None	Instructions (PDF) Solutions (ZIP)	Readings The Python Standard Library 6.01SC Introduction to Electrical Engineering and Computer Science I
Core Elements of a Program	Lecture 2: Core Elements of a Program	None	Lecture code handout (PDF) Lecture code (PY)	Recitation 1: Introduction to Coding Concepts	Instructions (PDF) Code Files (ZIP) Solutions (ZIP)	None
Problem Solving	Lecture 3: Problem Solving	None	Lecture code handout (PDF) Lecture code (PY)	None	Instructions (PDF) Code Files (ZIP) Solutions (ZIP)	Readings Loops. An Introduction to Python.
Machine Interpretation of a Program	Lecture 4: Machine Interpretation of a Program	None	Lecture code handout (PDF) Lecture code (PY)	Recitation 2: Loops, Tuples, Strings and Functions	Instructions (PDF) Pseudocode (PDF) Code Files (ZIP) Solutions (ZIP)	None
Objects in Python	Lecture 5: Objects in Python	None	Lecture code handout (PDF) Lecture code (PY)	None	Instructions (PDF) Code Files (ZIP) Solutions (ZIP)	Readings 8. Lists. How to Think Like a Computer Scientist. 9. Tuples. How to Think Like a Computer Scientist. 10. Dictionaries. How to Think Like a Computer Scientist. 5.1 More on Lists. Python Tutorial. 5.3 Tuples as Sequences. Python Tutorial. 5.5 Dictionaries. Python Tutorial.
Recursion	Lecture 6: Recursion	None	Lecture code handout (PDF) Lecture code (PY)	Recitation 3: Lists and their Elements, Sorting, and Recursion	Instructions (PDF) Code Files (ZIP) Solutions (ZIP)	Readings 4.9 Recursion. How to Think Like a Computer Scientist. Recursion. An Introduction to Python. Comparing Recursion and Looping. An Introduction to Python. Related Lectures 6.006 Introduction to Algorithms. 6.006 lectures assume a greater level of mathematical sophistication than does 6.00SC. Read the lecture notes on: Dynamic programming I: memoization, Fibonacci, Crazy Eights, guessing
Debugging	Lecture 7: Debugging	Lecture slides (PDF)	Lecture code handout (PDF) Lecture code (PY)	Recitation 4: Recursion, Pseudo code and Debugging	Instructions (PDF) Code File (PY) Solutions (ZIP)	Readings 8. Errors and Exceptions. Python Tutorial. Appendix A: Debugging. How to Think Like a Computer Scientist.
Efficiency and Order of Growth	Lecture 8: Efficiency and Order of Growth	None	Lecture code handout (PDF) Lecture code (PY) showGrowth code (PY)	Optional Recitation: Algorithm Complexity and Class Review	Instructions (PDF) Code Files (ZIP) Solutions (ZIP)	None
Memory and Search Methods	Lecture 9: Memory and Search Methods	None	Lecture code handout (PDF) Lecture code (PY)	None	Instructions (PDF) Code Files (ZIP) Note: Solutions are not available for this assignment.	Readings 8.7. Sets—Unordered collections of unique elements. Python Standard Library. Related Lectures 6.01SC Introduction to Electrical Engineering and Computer Science I. Search Algorithms Optimizing a search 6.006 Introduction to Algorithms. 6.006 lectures assume a greater level of mathematical sophistication than does 6.00SC. Read the lecture notes on: Binary search trees Sorting Searching

Quiz I

QUIZ SCOPE	PREPARATION AND CONTENT REVIEW	QUIZ PROBLEMS AND SOLUTIONS
Quiz 1	Quiz 1 Topics List (PDF) Practice Quiz 1 (PDF)	Quiz 1 Problems (PDF) Quiz 1 Solutions (PDF)

Unit 2

TITLES	LECTURE VIDEOS	LECTURE SLIDES	LECTURE RESOURCES	RECITATION VIDEOS	PROBLEM SETS	FURTHER STUDY LINKS
Hashing and Classes	Lecture 10: Hashing and Classes	None	Lecture code handout (PDF) Lecture code (PY)	None	Instructions (PDF) Code Files (ZIP) Note: Solutions are not available for this assignment.	Readings 12. Classes and objects. How to Think Like a Computer Scientist. Related Lectures 6.006 Introduction to Algorithms. 6.006 lectures assume a greater level of mathematical sophistication than does 6.00SC. Read the lecture notes on: Hashing I: Chaining, hash functions Hashing II: Table doubling, Karp-Rabin Hashing III: Open addressing
OOP and Inheritance	Lecture 11: OOP and Inheritance	None	Lecture code handout (PDF) Lecture code (PY)	Recitation 5: Quiz 1 Answers and Object-Oriented Programming	Instructions (PDF) Code Files (ZIP) Note: Solutions are not available for this assignment.	None
Introduction to Simulation and Random Walks	Lecture 12: Introduction to Simulation and Random Walks	None	Lecture code handout (PDF) Lecture code (PY)	None	None	None
Some Basic Probability and Plotting Data	Lecture 13: Some Basic Probability and Plotting Data	None	Lecture code handout (PDF) Lecture code (PY)	None	None	None
Sampling and Monte Carlo Simulation	Lecture 14: Sampling and Monte Carlo Simulation	None	Lecture code handout (PDF) Lecture code (PY)	None	None	Readings Monte Carlo method. Wikipedia.
Statistical Thinking	Lecture 15: Statistical Thinking	None	Lecture code handout (PDF) Lecture code (PY)	Recitation 6: Probability and Statistics	None	None
Using Randomness to Solve Non-random Problems	Lecture 16: Using Randomness to Solve Non-random Problems	None	Lecture code handout (PDF) Lecture code (PY)	None	None	Monte Carlo method. Wikipedia. Matplotlib
Curve Fitting	Lecture 17: Curve Fitting	Lecture slides (PDF)	Lecture code handout (PDF) Lecture code (PY) Lecture data files (ZIP)	Recitation 7: Distributions, Monte Carlo, and Regressions	None	None
Optimization Problems and Algorithms	Lecture 18: Optimization Problems and Algorithms	Lecture slides (PDF)	Lecture code handout (PDF) Lecture code (PY) Launcher data file (TXT)	None	None	None
More Optimization and Clustering	Lecture 19: More Optimization and Clustering	Lecture slides (PDF)	Lecture code handout (PDF) Lecture code (PY)	None	None	None

Quiz 2

QUIZ SCOPE	PREPARATION AND CONTENT REVIEW	QUIZ AND SOLUTIONS
Quiz 2	Quiz 2 Topics List (PDF) Practice Quiz 2 (PDF)	Quiz 2 Problems (PDF) Quiz 2 Solutions (PDF)

Unit III

TITLES	LECTURE VIDEOs	LECTURE SLIDES	LECTURE RESOURCES	RECITATION VIDEOS	PROBLEM SETS	FURTHER STUDY LINKS
More Clustering	Lecture 20: More Clustering	Lecture slides (PDF)	Lecture code handout (PDF) Lecture code (PY) Lecture data files (ZIP)	Recitation 8: Hierarchical and k-means Clustering	None	None
Using Graphs to Model Problems, Part 1	Lecture 21: Using Graphs to Model Problems, Part 1	Lecture slides (PDF)	Lecture code handout (PDF) Lecture code (PY)	None	None	None
Using Graphs to Model Problems, Part 2	Lecture 22: Using Graphs to Model Problems, Part 2	None	Lecture code handout (PDF) Lecture code (PY)	Recitation 9: Directed and Undirected Node Graphs	None	None
Dynamic Programming	Lecture 23: Dynamic Programming	None	Lecture code handout (PDF) Lecture code (PY)	None	None	None
Avoiding Statistical Fallacies	Lecture 24: Avoiding Statistical Fallacies	Lecture slides (PDF)	Lecture code handout (PDF) Lecture code (PY)	Recitation 10: Introduction to Dynamic Programming	None	7.2 Reading and Writing Files. Python Tutorial.
Queuing Network Models	Lecture 25: Queuing Network Models	None	Lecture code handout (PDF) Lecture code (PY) Bus code (PY)	None	None	None
What Do Computer Scientists Do?	Lecture 26: What Do Computer Scientists Do?	Lecture slides (PDF)	None	None	None	None

Final Exam

FINAL EXAM	PREPARATION AND CONTENT REVIEW	QUIZ PROBLEMS AND SOLUTIONS
Final Exam	Quiz 3 Topics List (PDF) Practice Quiz 3 (PDF) Quiz 3 Code (PY)	Final Exam Problems (PDF) Final Exam Solutions (PDF)

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