YData: An Introduction to Data Science
YData is an introduction to the fundamental ideas and skills of data science.
Based on Berkeley’s popular Data 8 course, YData is an introduction to data science that emphasizes
computational and programming skills along with inferential thinking.
Calendar Spring 2022
Instructors: Ethan Meyers
Note: This class schedule is provisional and will be updated as the course progresses.
Here link to the MyBinder for running class demonstrations
Date
Topic
Lecture
Reading
Practice
Assignment
Wed 1/26
Introduction
Slides Chapter 1.1 , 1.2 , 1.3
Assignment 00 : Not due.
Fri 1/28
Cause and Effect
Slides Chapter 2
Mon 1/31
Intro to Python
demos/lec03 , MyBinder , Slides Chapter 3 Practice 01: Expressions Assignment 01: due 2/6
Wed 2/2
Data Types
demos/lec04 , MyBinder , slides Chapters 4 , 5
Fri 2/4
Arrays and Tables
demos/lec05 , MyBinder , Slides Chapter 6.1 , 6.2 Practice 02: Types & Sequences
Mon 2/7
Census
demos/lec06 , MyBinder , Slides Chapter 6.3 , 6.4
Assignment 02: due 2/13
Wed 2/9
Charts
demos/lec07 , MyBinder ,Slides Chapter 7 , 7.1 Practice 03: Arrays & Tables
Fri 2/11
Histograms
demos/lec08 , MyBinder , Slides Chapter 7.2 , 7.3
Mon 2/14
Functions
demos/lec09 , Slides Chapter 8 , 8.1
Assignment 03: due 2/20
Wed 2/16
Groups
demos/lec10 , Slides Chapter 8.2 , 8.3 Practice 04: Histograms & Functions
Fri 2/18
Joins
demos/lec11 , slides Chapter 8.4 , 8.5
Mon 2/21
Mapping and conditional statements
demos/lec12 , slides chapter 8.5
Assignment 04: due 2/27 Project 1: due Friday 3/4
Wed 2/23
Iteration
demos/lec13 , slides Chapter 9 , 9.1 , 9.2 , 9.3
Fri 2/25
Chance
demos/lec14 , slides Chapter 9.4 , 9.5
Mon 2/28
Sampling
demos/lec15 , slides Chapter 9.4 10 , 10.1 , 10.2
Assignment 05: practice only, not turned in
Wed 3/2
Models
demos/lec16 , slides Chapter 10.3 , 11.1
Fri 3/4
Comparing Distributions
demos/lec17 , slides Chapter 11.1 , 11.2 Practice 05: Simulations
Mon 3/7
Decisions and Uncertainty
demos/lec18 , slides Chapter 11.3
Assignment 06: due 3/13
Wed 3/9
A/B Testing
demos/lec19 , slides Chapter 12.1 , 12.3 Practice 06: Assessing Models
Fri 3/11
Causality
demos/lec20 , slides Chapter 12.2
Mon 3/14
Confidence Intervals
demos/lec23 , slides chapter 13 , 13.1 13.2
Wed 3/16
Examples
demos/lec22 , slides
Fri 3/18
Midterm
3/19-3/27
Spring Break
Mon 3/28
Interpreting Confidence
demos/lec24 , slides Chapter 13.3 , 13.4
Assignment 07: practice only, not turned in Project 2: due Friday 4/8
Wed 3/30
Center and Spread
demos/lec25 , slides Chapter 14 , 14.1 , 14.2 Practice 07: Bootstrap
Fri 4/1
The Normal Distribution
demos/lec26 , slides Chapter 14.3 , 14.4
Mon 4/4
Sample Means
demos/lec27 , slides Chapter 14.5
Assignment 08: due 4/10
Wed 4/6
Designing Experiments
demos/lec28 , slides Chapter 14.6
Fri 4/8
Correlation
demos/lec29 , slides Chapter 15 , 15.1 Practice 08: Correlation
Mon 4/11
Linear Regression
demos/lec30 , slides Chapter 15.2
Assignment 09: due 4/17
Wed 4/13
Least Squares
demos/lec31 , slides Chapter 15.3 , 15.4
Project 3: due Wednesday 4/27
Fri 4/15
Residuals
demos/lec32 , slides Chapter 15.5 , 15.6 Practice 09: Regression
Mon 4/18
Regression Inference
demos/lec33 , slides Chapter 16
Assignment 10: due 4/24
Wed 4/20
Classification
<demos/lec34 , slides
Chapter 17 , 17.1 , 17.2 , 17.3 Practice 10: Inference for Regression
Fri 4/22
Classifiers
demos/lec35 , slides Chapter 17.4
Mon 4/25
Classification continued
demos/lec36 , slides Chapter 17.6
Assignment 11: due 5/1
Wed 4/27
Multiple Regression
demos/lec37 , slides Chapter 18
Fri 4/29
pandas
demos/lec38 , slides
Mon 5/9
Final exam
2pm
