Introduction
Beginning your data science exploration
()
1. Defining Data Science
What is data science?
()
Why data science?
()
2. Data Science Life Cycle
What is the data science life cycle?
()
3. Data Design
Probability sampling
()
4. Computational Tools
Python vs. R
()
Set up the environment: Jupyter
()
5. Tabular Data
What is tabular data?
()
Reading tabular data
()
Gathering insights
()
Answering specific questions
()
6. Exploratory Data Analysis
What is exploratory data analysis?
()
Statistical data types
()
Properties of data
()
7. Data Cleaning
What is data cleaning?
()
Questions to ask before cleaning
()
8. Data Visualization
Visualize qualitative data
()
Visualize quantitative data
()
What is data visualization?
()
9. Inference
Design a hypothesis test
()
Conduct a permutation test
()
Bootstrap a confidence interval
()
What is inference?
()
10. Classification
What is classification?
()
Intro to k-Nearest Neighbor algorithm
()
Ex_Files_Intro_Data_Science.zip
(57.9 MB)