Introduction to Computational Thinking with Data 📊
UC Berkeley, Summer 2021
Instructors: Isaac Merritt (isaacmerritt@berkeley.edu), Ian Castro (castro.ian@berkeley.edu)
Lecture: MW 10-11AM, TuTh 10AM-12PM, Lab: MW 11AM-12PM, Discussion: F 10AM-12PM, Office Hours: See Ed
The following breakdown is tentative. All assignments are available for public consumption on our GitHub.
1. Welcome to Data 6!
- Jul 6
1 Introduction + Course Overview; Jupyter and Arithmetic
1 slides • lec1 code • lec1 code HTML • lec2 code • lec2 code HTML
- Jul 7
2 Variables and Types
Lab 0 Using Jupyter Notebooks
- Jul 8
3 Comparison; Functions
3 slides • QC • lec1 code • lec1 code HTML • lec2 code • lec2 code HTML
Homework 1 Introduction to Python (due July 12th)
Survey 1 Weekly Survey (due July 12th)
- Jul 9
Discussion 1 Data in Education
2. Python Fundamentals
- Jul 12
4 Control (if/else)
Lab 1 Functions
- Jul 13
5 Control & Functions Review; Lists and Strings
5 slides • QC • lec1 practice problems • lec2 code • lec2 code HTML
- Jul 14
6 Iteration I (For Loops)
6 optional readings: SPR 19
Lab 2 Python Fundamentals
Homework 2 Python Fundamentals (due July 19th)
Survey 2 Weekly Survey (due July 19th)
- Jul 15
7 Iteration II (For Loops & Algorithms); Iteration III (While Loops)
7 slides • QC • lec1 code • lec1 code HTML • lec2 code • lec2 code HTML
7 optional readings: SPR 10, 14; TCS 8.2, 10.18, Luhn’s,TCS 10.24
- Jul 16
Discussion 2 Human Contexts & Ethics
3. Data and Tables
- Jul 19
8 Quiz 1 Review
Lab 3 For Loops
- Jul 20
Quiz 1 Quiz 1 (in lecture)
9 File Formats + Dictionaries
9 optional readings: CSV vs. JSON, Imports, SPR 21, TCS 12
- Jul 21
10 Dictionaries and NumPy
10 optional readings: SPR 21, TCS 12, CIT 5, Data 8 Python ref
Lab 4 Dictionaries and NumPy
Homework 3 Dictionaries and NumPy (due July 26th)
Survey 3 Weekly Survey (due July 26th)
- Jul 22
11 Table Fundamentals; Row Manipulation
11 slides • QC • lec1 code • lec1 code HTML • lec2 code • lec2 code HTML
11 optional readings: CIT 6.0, CIT 6.1-6.4,
are.
docs- Jul 23
Discussion 3 Algorithmic Bias
4. Table Methods
- Jul 26
12 Applying
12 optional readings: CIT 8.1
Lab 5 Tables
- Jul 27
13 Grouping; Pivoting
13 slides • QC • lec1 code • lec1 code HTML • lec2 code • lec2 code HTML
13 optional readings: CIT 8.2, 8.3; Table Visualizer
- Jul 28
14 Joining and Row Methods
14 optional readings: CIT 8.4, Join animation
Lab 6 More Table Methods
Homework 4 Table Methods (due August 2nd)
Survey 4 Weekly Survey (due August 2nd)
- Jul 29
15 Case Study: University Rankings; Quiz 2 Review
15 case study slides • QC • code • code HTML
- Jul 30
Discussion 4 Data in Elections (Cambridge Analytica)
5. Data Visualization
- Aug 2
Quiz 2 Quiz 2 (in lecture)
16 Introduction to Visualization
16 optional readings: History of Viz
- Aug 3
17 Visualizing Categorical & Numerical Variables
17 slides • QC • lec1 code • lec1 code HTML • lec2 code • lec2 code HTML
- Aug 4
18 Visualizing Two Numerical Variables
18 optional readings: CIT 7.0
Homework 5 Data Visualization (due August 10th)
Survey 5 Weekly Survey (due August 10th)
- Aug 5
19 Maps; Fun with Plotly
19 slides • QC • lec1 code • lec1 code HTML • lec2 code • lec2 code HTML
19 optional readings: CIT 8.5
- Aug 6
Discussion 5 Privacy (Carpenter v. US)
6. Simulations with Data + Conclusion
- Aug 9
20 Case Study: Perception
20 optional readings: Basic Principles
Lab 8 More Visualization
- Aug 10
21 Randomness + Simulations; Finding and Using Data
21 optional readings: Randomness; CIT 9.3, 10.1
- Aug 11
22 Conclusion + Next Steps
Lab Next Steps (no notebook)
Survey 6 Final Survey (due August 14th)
- Aug 12
23 Final Review
23 slides • Final Exam Solutions
- Aug 13
Final Exam Final Exam (in lecture 10AM-12PM)