Introduction to Computational Thinking with Data 📊

UC Berkeley, Spring 2021

Instructor: Suraj Rampure (rampure@berkeley.edu)

Lecture: MWF 11AM-12PM, Lab: F 12-1PM, Office Hours: See Ed

Zoom links Lecture recordings

The following breakdown is tentative. All assignments are available for public consumption on our GitHub.

1. Welcome to Data 94!

Jan 20

1 Introduction, Course Overview

1 slides • code • code HTML

Jan 22

2 Jupyter Notebooks and Arithmetic

2 slides • code • code HTML • example QC • readings: CIT 3.1, 4.1; SPR 8

Lab 0 Using Jupyter Notebooks

2. Python Fundamentals

Jan 25

3 Variables and Types

3 slides • code • code HTML • QC • readings: CIT 3.2, 4.2; SPR 7

Jan 27

4 Comparisons

4 slides • code • code HTML • QC • readings: CIT 4.3

Jan 28

Homework 1 Python Fundamentals (due Feb. 3)

Survey 1 Weekly Survey (due Feb. 3)

Jan 29

5 Functions

5 slides • code • code HTML • QC • readings: CIT 8.0, SPR 9

Lab 1 Functions

3. Iteration

Feb 1

6 Control

6 slides • code • code HTML • QC • readings: CIT 9.1; SPR 12, 13

Feb 3

7 Iteration 1 (While loops)

7 slides • code • code HTML • QC • readings: SPR 11

Feb 4

Homework 2 Control, Iteration, Lists, and Strings (due Feb. 17)

Survey 2 Weekly Survey (due Feb. 11)

Feb 5

8 Lists and Strings

8 slides • code • code HTML • QC • readings: SPR 19

Lab 2 More Python Fundamentals

4. Review, Quiz 1

Feb 8

9 Review

9 slides • code • code HTML • QC

Feb 10

10 More Review

10 slides • code • code HTML • QC

Feb 12

QUIZ 1 Quiz 1 (in lecture)

Lab Quiz Review

5. More Iteration

Feb 15

N/A (Presidents Day)

Feb 17

11 Iteration 2 (For loops)

11 slides • code • code HTML • QC • readings: SPR 10, 14; TCS 8.2, 10.18

Feb 18

Homework 3 Review and For Loops (due Feb. 24)

Survey 3 Weekly Survey (due Feb. 24)

Feb 19

12 More Iteration

12 slides • code • code HTML • QC • readings: Luhn’s, TCS 10.24

Lab 3 For Loops

6. Programming in Data Science

Feb 22

13 Dictionaries

13 slides • code • code HTML • QC • readings: SPR 21, TCS 12

Feb 24

14 File Formats and Modules

14 slides • code • code HTML • QC • readings: CSV vs. JSON, Imports

Feb 25

Homework 4 Dictionaries and NumPy (due Mar. 4)

Survey 4 Weekly Survey (due Mar. 4)

Feb 26

15 NumPy

15 slides • code • code HTML • QC • readings: CIT 5, Data 8 Python reference

Lab 4 Dictionaries and NumPy

7. Table Fundamentals

Mar 1

16 Table Fundamentals

16 slides • code • code HTML • QC • readings: CIT 6.0

Mar 3

17 Guest Lecture: Disinformation and Data

17 slides • no QC

Mar 4

Homework 5 Table Fundamentals (due Mar. 11)

Survey 5 Weekly Survey (due Mar. 11)

Mar 5

18 Row Manipulation

16 slides • code • code HTML • QC • readings: CIT 6.1-6.4, are. docs

Lab 5 Tables

8. More Table Methods

Mar 8

19 Applying

Mar 10

20 Grouping and Pivoting

Mar 12

21 Joins

9. Quiz 2, Special Topics

Mar 15

22 Case Studies

Mar 17

23 Review

Mar 19

QUIZ 2 Quiz 2 (in lecture)

10. Spring Break 🏄

Mar 22

N/A (Spring Break)

Mar 24

N/A (Spring Break)

Mar 26

N/A (Spring Break)

11. Visualization

Mar 29

24 Variable Types and Distributions

Mar 31

25 Visualizing and Describing Single Variables

Apr 2

26 Visualizing Pairs of Variables

12. Visualization and Graphics

Apr 5

27 Cartography

Apr 7

28 Visualization Principles

Apr 9

29 Visualization Libraries

13. Quiz 3, Statistics

Apr 12

30 TBD

Apr 14

31 Review

Apr 16

Quiz 3 Quiz 3 (in lecture)

14. Statistics and Special Topics

Apr 19

32 Sampling with Simulations

Apr 21

33 Applications of Simulations

Apr 23

34 Future Studies in Statistics

15. Special Topics and Review

Apr 26

35 Drawing

Apr 28

36 APIs and File I/O

Apr 30

37 Conclusion