ND025 - Data Scientist

Tags

• Author : AH Uyekita
• Dedication : 10 hours/week (suggested)
• Start : 12/02/2019
• End (Planned): 30/03/2019
• Title : Data Scientist Nanodegree Program
  • COD : ND025

Related Courses

• ND110 - Data Science I - Nanodegree Foundations
• ND111 - Data Science II - Nanodegree Foundations

Bookdown and Projects

• Bookdown 📖
• Project 01
• Project 02
• Project 03
• Project 04

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Objectives

Syllabus

This course is divided into 5 parts/chapters and has 5 projects.

Core Curriculum

• Chapter 01 - Introduction
  • Lesson 01 - Orientações Importantes para o Nanodegree
  • Lesson 02 - Dicas para o seu Nanodegree
  • Lesson 03 - Introduction
• Chapter 02 - Supervised Learning
  • Lesson 01 - Linear Regression
  • Lesson 02 - Perceptron Algorithm
  • Lesson 03 - Decision Tree
  • Lesson 04 - Naïve Bayes
  • Lesson 05 - Support Vector Machine
  • Lesson 06 - Ensemble Methods
  • Lesson 07 - Supervised Learning Assessment
  • Project 01 - Supervised Learning Project
• Chapter 03 - Unsupervised Learning
  • Lesson 01 - Clustering
  • Lesson 02 - Clustering Mini-project
  • Lesson 03 - Hierarchical and Density-based Clustering
  • Lesson 04 - Gaussian Mixture Models and Cluster Validation
  • Lesson 05 - Fature Scaling
  • Lesson 06 - PCA
  • Lesson 07 - PCA Mini-project
  • Lesson 08 - Random Projection and ICA
  • Lesson 09 - Unsupervised Learning Assessment
  • Project 02 - Unsupervised Learning Project
  • Project 02.1 - Strengthen Your Online Presence Using LikedIn
  • Project 02.2 - Optimize your Github Profile
• Chapter 04 - Big Data & Map Reduce
  • Lesson 01 - Big Data
  • Lesson 02 - Problem Set
  • Lesson 03 - HDFS and MapReduce
  • Lesson 04 - Problem Set
  • Lesson 05 - MapReduce Code
  • Lesson 06 - Project [Optional]
  • Lesson 07 - MapReduce Design Patterns
  • Project 03 - Analyzing NY Subway Data
• Chapter 05 - Data Analysis with R
  • Lesson 01 - What is EDA?
  • Lesson 02 - R Basics
  • Lesson 03 - Explore One Variable
  • Lesson 04 - Problem Set: Explore One Variable
  • Lesson 05 - Explore Two Variables
  • Lesson 06 - Problem Set: Explore Two Variables
  • Lesson 07 - Explore Many Variables
  • Lesson 08 - Problem Set: Explore Many Variables
  • Lesson 09 - Diamonds & Price Predictions
  • Project 04 - Explore and Summarize Data

Extracurricular

• Chapter 01 - Matrix and NumPy Refresher
• Chapter 02 - Basic Software Engineering Skils

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.