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