Introduction to Python
(Spring 2020)

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Lecture Material

(Videos in Calendar below)

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Live broadcasts here
during lecture time

Lecture 10: Notes
Lecture 11: Notes
Lecture 12: Notes

Office Hours

Monday: 11am-11pm
Tuesday - Thursday: 11am-9pm
Friday 11am-5pm
How? Help Queue using Zoom

This Week's Pset

Problem Set 0: Warm Up.
Due: Feb 07 at 05:00PM

Recitation Schedule

Cancelled

Calendar and Materials 6.0002 - Spring 2020

Monday

Tuesday

Wednesday

Thursday

Friday

3/30: Lecture 1
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files

Introduction, optimization, knapsack problems

MITx Ex. 1 out
Pset 1 out

3/31

4/1: Lecture 2
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files

Dynamic programming (incl. tabular method), Pseudo polynomial complexity
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<b><a href="COURSE/MQ0">Trial Microquiz 0</a> (to test YOUR and our system)</b>
</div>

4/2

4/3: Last day we are accepting 6.0002 adds

4/6: Lecture 3
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files

Graphs, shortest path problems, DFS and BFS, all paths, and efficient algorithms including Dijkstra.

MITx Ex. 1 due
Pset 1 due at 11pm
MITx Ex. 2 out
Pset 2 out

4/7

4/8: Lecture 4
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files
Stochastic thinking, probability, simulation

Microquiz 1 (30 minutes within a 12 hour time period)

4/9

4/10

4/13: Lecture 5
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files (updated with slides hidden pre-lecture)

Random Walks

MITx Ex. 2 due
Pset 2 due at 11pm
MITx Ex. 3 out
Pset 3 out

4/14

4/15: Lecture 6
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files

Monte Carlo Methods, variance, confidence intervals, roulette, pi

4/16

Pset 4 out

4/17

4/20: Patriot's Day

4/21

Pset 3 due at 11pm

4/22: Lecture 7
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO and Slides and .py files (for virus sim, now updated with annotations and extra content)

Recorded Video and Slides and .py files (for stocks sim)

Stock market simulation / virus simulation (both lectures cover the same ideas just on a different topic)

MITx Ex. 3 due
MITx Ex. 4 out

Microquiz 2 (30 minutes within a 12 hour time period)

4/23

4/24

4/27: Lecture 8
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files

Distributions, CLT, sampling, standard error

Pset 4 due at 11pm
Pset 5 out

4/28

4/29: Lecture 9
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files

Curve fitting, linear regression, R**2, overfitting, choosing a degree, training and test sets

MITx Ex. 4 due
MITx Ex. 5 out

Microquiz 3 (30 minutes within a 12 hour time period)

4/30

5/1

5/4: Lecture 10
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files

Intro to ML, distance metrics, scaling of features, K-means clustering, classification, KNN classification

5/5

5/6: Lecture 11
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files (updated with annotations)

Classification, KNN, logistic regression

MITx Ex. 5 due

Microquiz 4 (30 minutes within a 12 hour time period)

5/7

5/8

5/11: Lecture 12
YOU MUST LOG AND BE REGISTERED AS A STUDENT IN TO SEE LECTURE VIDEO

Slides and .py files (updated with annotations)

Last lecture - statistical fallacies, wrap up

Pset 5 due at 11pm

5/12
Last day of classes

5/13

5/14

5/15

Calendar and Materials 6.0001 - Spring 2020

Monday

Tuesday

Wednesday

Thursday

Friday

2/3: Lecture 1
Admin & overview , what is computation, intro to programming languages and Python, assignment, types (int, float, str), objects, branching, indentation

L1 FE out
PS 0 out

2/4
PS 1 out

2/5: Lecture 2 (updated with class annotations)
Iteration (while loops, basic for loops with range), guess and check algorithms, Strings (insertion, deletion).

L2 FE out
L1 FE due

2/6

2/7
Recitation 1
PS 0 due at 5pm

2/10: Lecture 3
Binary numbers, floating point, approximate solutions, bisection methods

L3 FE out
L2 FE due
6.0001 add deadline

2/11
PS 2 out

2/12: Lecture 4
Decomposition, abstraction, functions, scope, recursion

L4 FE out
L3 FE due
PS 1 due at 9pm

2/13
PS 1 checkoffs start

2/14
Recitation 2

2/17
No school - President's Day holiday

2/18: Lecture 5
Tuples, lists, mutability, for loops over sequences

Microquiz 1
L5 FE out
PS 3 out
L4 FE due

2/19: Lecture 6
Dictionaries, debugging

L6 FE out
L5 FE due
PS 2 due at 9pm

2/20
PS 2 checkoffs start

2/21
Recitation 3

2/24: Lecture 7 (updated with class annotations)
Data abstraction, start classes, subtyping, substitution rule

Microquiz 2
No L7 FE
L6 FE due
PS 1 checkoff due

2/25
PS 4 out

2/26: Lecture 8 (updated with class annotations)
Inheritance, extended example using classes, class attributes

L8 FE out
PS 3 due at 9pm
PS3 checkoffs start

2/27

2/28
Recitation 4

3/2: Lecture 9 (updated with class annotations)
Introduce algorithm analysis

Microquiz 3
No L9 FE
L8 FE due
PS 2 checkoff due

3/3
PS 5 out
PS 5 checkoffs start (after code submitted)

3/4: Lecture 10
Continue analysis of algorithms, implementing lists using indirection

No L10 FE
PS 4 due at 9pm
PS4 checkoffs cancelled

3/5

3/6
6.0001 drop deadline

3/9: Lecture 11
Binary search, selection sort, merge sort, amortized analysis

L11 FE out
PS 3 checkoff due

3/10

3/11: Lecture 12
Hashing, plotting

No L12 FE
L11 FE due
PS 5 cancelled

3/12

3/13

3/16: No Lecture

Quiz review (cancelled)

3/17

3/18:
6.0001 Final Exam (cancelled)

PS 4 checkoff cancelled

3/19

3/20
PS 5 checkoff cancelled

Introduction to Python (Spring 2020)