MITx's Introduction to Computer Science and Programming Using Python
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README.md
bestshigt_fish2.py
class_instance.py
edx_courseinfo.py
fable.txt
fatc1.py
feedparser.py
fibonachi1.py
final_exam_secret_number.py
findBestShift_fish.py
fish_cipher.py
fish_cipher2.py
fish_cipher3.py
gentest1.py
gentest2.py
grading_code.py
inset_class.py
object_1.py
object_2.py
p6_q1.py
p6_q2.py
problemset1_practice.py
project_util.py
ps4a.py
ps4a.pyc
ps4a2.py
ps4b.py
ps4b2.py
ps6_encryption.py
ps6_pseudo.txt
ps6_pseudo_fish.py
ps6_recursion.py
ps7.py
ps7_test.py
sort4.py
story.txt
test_ps4a.py
test_ps4a2.py
tmp.py
triggers.txt
wordgame.py
words.txt

README.md

6.00.1x

MITx's Introduction to Computer Science and Programming Using Python

ID verified certificate of achievement is available at https://s3.amazonaws.com/verify.edx.org/downloads/7acef5767cd74e28b07ec112638241d2/Certificate.pdf

List of Lecture Topics

Lecture 1 – Introduction: • What a computer does • Computational thinking • Aspects of programming languages • Basic machine architecture

Lecture 2 – Core elements of programs: • Kinds of languages • Objects, expressions, operators • Abstraction by naming • Strings • Scripts • Straightline programs • Branching programs

Lecture 3 – Simple algorithms: • Simple programs • Iteration • Input • Exhaustive enumeration • Guess and check • For and while loops • Approximate solutions • Bisection search • Newton-Raphson Lecture 4 – Functions: • Function syntax • Abstraction by specification • Functions and scoping • Floating point numbers • Specifications • Modules

Lecture 5 – Recursion: • Recursion • Inductive reasoning • Divide and conquer

Lecture 6 – Objects: • Structured types and mutability • Tuples • Lists and mutability • Functions as objects • Dictionaries

Lecture 7 – Debugging: • Testing and debugging • Black box testing • Glass box testing • Integration testing and unit testing • Debugging with binary search

Lecture 8 – Assertions and Exceptions • Assertions • Exceptions

Lecture 9 – Efficiency and orders of growth: • Complexity • How to measure complexity • Asymptotic notation

Lecture 10 – Memory and search: • Memory storage • Indirection • Searching and sorting methods • Hashing

Lecture 11 – Classes: • Definition of classes • Classes versus instances • Methods • Bindings of values • Exceptions

Lecture 12 – Object Oriented Programming and Inheritance: • Inheritance • Object oriented programming

Lecture 13 – Trees: • Decision trees • Depth-first search • Breadth-first search

Lecture 14 – Summary

Lecture 15 – Research videos