course schedule

Week 1

Date Event
June 28
  1. Lecture #1: Welcome to Digital Scholars Data Science!
  2. Content:
June 29
  1. Lecture #2: Experimental Design, Blocking and pandas
  2. Content:
  3. Lab #1: Introduction
June 30
  1. Lecture #3: Observational Studies, Confounders, and Stratification
  2. Content:
  3. Lab #2: Pandas
July 1
  1. Lecture #4: Measures of Center and Spread, Boolean Logic, and Conditionals
  2. Content:
  3. Project: Introduction

Week 2

Date Event
July 5
  1. Holiday - No Class! :)
July 6
  1. Lecture #5: EDA: Summary Statistics and Grouping Data
  2. Content:
July 7
  1. Lecture #6: EDA: Plots
  2. Content:
  3. Lab #3: Simpson's Paradox & Grouping Data
July 8
  1. Lecture #7: Algorithms and Introduction to Probability
  2. Content:
  3. Project: Analysis Question & Exploring your Dataset

Week 3

Date Event
July 12
  1. Lecture #8: Probability, Control Flow and Simulation in Python
  2. Content:
July 13
  1. Lecture #9: Functions in Python, Conditional Probability and Bayes Rule
  2. Content:
  3. Lab 4: Plots & Simulations
July 14
  1. Lecture #10: Simulation Analysis, Errors and Ethics in Data Science
  2. Content:
  3. Lab 5: Birthday
July 15
  1. Lecture #11: Object-oriented Programming, Random Variables and Distributions
  2. Content:
  3. Project Demo

Week 4

Date Event
July 19
  1. Lecture #12: Discrete Random Variables, Distributions and Normal Approximation
  2. Content:
  3. Lab #6: Random Variables
July 20
  1. Lecture #13: Normal Approximation, Central Limit Theorem, and Sampling
  2. Content:
  3. Data Science CREATIVITY Workshop
July 21
  1. Lecture #14: Confidence Intervals, Data Types, and Linear Regression
  2. Content:
July 22
  1. #15: Linear Regression: Scatter Plots, Correlation, and Residuals
  2. Content:

Week 5

Date Event
July 26
  1. Lecture #16: Logistic Regression, K-Means Clustering, and Hypothesis Testing
  2. Content:
July 27
  1. Lecture #17: Hypothesis Testing and A/B Testing
July 28
  1. Lecture #18: TBD
  2. Project Presentations! :)
July 29
  1. Lecture #19: YOUR Future in Data Science
  2. Project Presentations! :)