++

noisy Y

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 2019

Instructors: Jessi Cisewski-Kehe and John Lafferty
Lecture: MWF 10:30-11:20, LUCE 101

Date Topic Lecture Reading Assignment
Mon 1/14 Introduction Demos, Slides Chapter 1.1, 1.2, 1.3  
Wed 1/16 Cause and Effect Slides Chapter 2 Practice 01: Expressions
Fri 1/18 Tables Demos (Binder verison), Slides Chapter 3 Homework 01 (Due Thu 1/24)
Mon 1/21 No class (MLK day)
Wed 1/23 Data Types Demos, Slides Chapters 4, 5 Practice 02: Types & Sequences
Fri 1/25 Building Tables Demos (Binder verison), Slides 6.1, 6.2 Homework 02 (Due Thu 1/31)
Mon 1/28 Census Demos, Slides 6.3, 6.4  
Wed 1/30 Charts Demos, Slides 7, 7.1 Practice 03: Arrays & Tables
Fri 2/1 Histograms Demos, Slides 7.2, 7.3 Homework 03 (Due Thu 2/7)
Mon 2/4 Functions Demos, Slides 8, 8.1  
Wed 2/6 Groups Demos, Slides 8.2, 8.3 Practice 04: Histograms & Functions
Fri 2/8 Joins Demos (Binder version), Slides 8.4, 8.5 Homework 04 (Due Thu 2/14)
Project 1: World Progress
(Checkpoint Fri 2/15; Due Fri 2/22)
Mon 2/11 Table Examples Demos (Binder version), Slides 8.5  
Wed 2/13 Iteration Demos, Slides 9, 9.1, 9.2, 9.3  
Fri 2/15 Chance Demos, Slides 9.4, 9.5 Homework 05 (Due Thu 2/21)
Mon 2/18 Sampling Demos, Slides 10, 10.1, 10.2  
Wed 2/20 Models Demos, Slides 10.3, 11.1 Practice 05: Sampling
Fri 2/22 Comparing Distributions Demos, Slides 11.1, 11.2 Homework 06 (Due Thu 2/27)
Project 1
Mon 2/25 Decisions and Uncertainty Demos, Slides 11.3  
Wed 2/27 A/B Testing Demos, Slides 12.1, 12.2 Practice 06: Assessing Models
Fri 3/1 Causality Demos, Slides 12.3 Homework 07 (Due Thu 3/28)
Practice midterm (sample solution)
Study sheet
Midterm solution
Mon 3/4 Examples Slides   Midterm Review
Wed 3/6 Midterm Exam      
Fri 3/8 Confidence Intervals Demos, Slides 13, 13.1, 13.2  
3/8 – 3/24 Spring Recess      
Mon 3/25 Interpreting Confidence Demos, Slides 13.3, 13.4  
Wed 3/27 Center and Spread Demos, Slides 14, 14.1, 14.2 Practice 07: Bootstrap
Fri 3/29 The Normal Distribution Demos, Slides 14.3, 14.4 Homework 08 (Due Thu 4/4)
Project 2: Diet & Disease
(Checkpoint Fri 4/5; Due Fri 4/12)
Mon 4/1 Sample Means Demos, Slides 14.5  
Wed 4/3 Designing Experiments Demos, Slides 14.6  
Fri 4/5 Correlation Demos, Slides 15, 15.1 Homework 09 (Due Thu 4/11)
Project 2 checkpoint
Mon 4/8 Linear Regression Demos, Slides 15.2  
Wed 4/10 Least Squares Demos, Slides 15.3, 15.4 Practice 08: Correlation
Fri 4/12 Residuals Demos, Slides 15.5, 15.6 Homework 10 (Due Thu 4/18)
Project 2 due
Project 3: Classifying Movies
(Optional; Due Fri 4/26)
Mon 4/15 Regression Inference Demos, Slides Chapter 16  
Wed 4/17 Classification Demos, Slides 17, 17.1, 17.2, 17.3  
Fri 4/19 Classifiers Demos, Slides 17.4 Homework 11 (Due Thu 4/25)
Mon 4/22 Classifiers Demos, Slides    
Wed 4/24 Decisions Demos, Slides   Chapter 18
Practice 09: Regression
Fri 4/26 Conclusion Demos, Slides   Project 3 due
Sun 5/5 Final Exam     Sunday 2pm