Udacity Data Analyst Nanodegree

This repository has all Jupyter Notebooks that summarize important techniques I've learned throughout the program.

Details about the program can be found HERE.

Table of contents

1. Introduction to Data Analysis

• Anaconda
• Jupyter Notebooks
• The Data Analysis Process
• Case Study 1
• Case Study 2

2. Practical Statistics

• Descriptive Statistics
• Admission Case Study (Simpson's Paradox)
• Probability
• Binomial Distribution
• Conditional Probability
• Bayes Rule
• Python Probability Practice
• Normal Distribution Theory
• Sampling distributions and Central Limit Theorem
• Confidence Interval
• Hypothesis Testing
• Case study: A/B Tests
• Regression
• Multiple Linear Regression
• Logistic Regression

3. Data Wrangling

• Gathering Data
• Assessing Data
• Cleaning Data

4. Data Visualization

• Design of Visualizations
• Unvariate Exploration of Data
• Bivarate Exploration of Data
• Multivariate Exploration of Data
• Explanatory of Visualizations
• Visualization Case Study

5. Course projects

• Project 1 - Explore Weather Trends
• Project 2 - Investigate the Movie Database (TMDB)
• Project 3 - Analyze A/B Test Results
• Project 4 - Wrangle and Analyze WeRateDogs Twitter datasets
• Project 5 - Visualize the PISA 2012 dataset