ND111 - Data Science II - Notebook
Course Info
Tags
- Author : AH Uyekita
- Dedication : 10 hours/week (suggested)
- Start : 14/12/2018
- End (Planned): 28/12/2018
- Title : Data Science II - Foundations Nanodegree Program
- COD : ND111
Related Courses
Bookdown and Projects
Objectives
I want to finish this course in two weeks. It includes the Optional videos and chapters.
Syllabus
- Chapter 01 - Welcome
- Lesson 01 - Instructions
- Lesson 02 - Tips
- Chapter 02 - SQL for Data Analysis
- Lesson 01 - Basic SQL
- Lesson 02 - SQL Joins
- Lesson 03 - SQL Aggregations
- Lesson 04 - (Optional) SQL Subqueries & Temporary Tables (Advanced)
- Lesson 05 - (Optional) SQL Data Cleaning (Advanced)
- Project 01 - Query a Digital Music Store Database
- Chapter 03 - Data Wrangling
- Lesson 01 - Introduction to Data Wrangling
- Lesson 02 - Gathering
- Lesson 03 - Assessing Data
- Lesson 04 - Cleaning Data
- Project 02 - Wrangle and Analyze Data
- Chapter 04 - Advanced Statistics
- Lesson 01 - Descriptive Statistics - Part 1
- Lesson 02 - Descriptive Statistics - Part 2
- Lesson 03 - Admissions Case Study
- Lesson 04 - Probability
- Lesson 05 - Binomial Distribution
- Lesson 06 - Conditional Probability
- Lesson 07 - Bayes Rule
- Lesson 08 - Python Probability Practice
- Lesson 09 - Normal Distribution Theory
- Lesson 10 - Sampling Distributions and the Central Limit Theorem
- Lesson 11 - Confidence Intervals
- Lesson 12 - Hypothesis Testing
- Lesson 13 - Case Study: A/B Tests
- Lesson 14 - Regression
- Lesson 15 - Multiple Linear Regression
- Lesson 16 - Logistic Regression
- Project 03 - Analyze A/B Test Results
- Chapter 05 - Intro to Machine Learning
- Lesson 01 - Welcome to Machine Learning
- Lesson 02 - Naive Bayes
- Lesson 03 - SVM
- Lesson 04 - Decision Trees
- Lesson 05 - Choose Your Own Algorithm
- Lesson 06 - Datasets and Questions
- Lesson 07 - Regressions
- Lesson 08 - Outliers
- Lesson 09 - Clustering
- Lesson 10 - Feature Scaling
- Lesson 11 - Text Learning
- Lesson 12 - Feature Selection
- Lesson 13 - PCA
- Lesson 14 - Validation
- Lesson 15 - Evaluation Metrics
- Lesson 16 - Tying It All Together
- Project 04 - Identify Fraud from Enron Email
- Chapter 06 - (Optional) Data Visualization
- Lesson 01 - Introduction to Data Visualization
- Lesson 02 - Design
- Lesson 03 - Data Visualization in Tableau
- Lesson 04 - Making Dashboard & Stories in Tableau
Repository Structure
This is the structure of this repository, each course’s chapters (or parts) will be stored in different folders.
ND111_data_science_foundation_02
|
+-- 01-Chapter_01
| |
| +-- README.md # General information
|
+-- 02-Chapter_02
| |
| +-- README.md # General information
| +-- 00-Project_01 # Project 01
| +-- 01-Lesson_01 # Files from Lesson 01
| | +-- README.md # Notes from Lesson 01 from Chapter 02
| +-- 02-Lesson_02 # Files from Lesson 02
| | +-- README.md # Notes from Lesson 02 from Chapter 02
| .
|
+-- 03-Chapter_03
| |
| +-- README.md # General information
| +-- 00-Project_02 # Project 02
| +-- 01-Lesson_01 # Files from Lesson 01
| | +-- README.md # Notes from Lesson 01 from Chapter 02
| +-- 02-Lesson_02 # Files from Lesson 02
| | +-- README.md # Notes from Lesson 02 from Chapter 02
| .
Best practice
- Add all deliverables in the
GitKraken Glo
; - Take notes using the
Markdown
.
A work by AH Uyekita
anderson.uyekita[at]gmail.com