BitTiger Data Scientist Mastery Program

This is the repository for BitTiger Data Scientist Mastery Program (DS501). This page covers what we are going to teach you and the resource you will need throughout the course.

The course videos are linked here: DS501 数据科学家直通车.

• Day: Day of the Week
• Readings: Readings for the day.
• Lecture Notes: The folder contains lecture notes and slides.

Teaching Team

• Lead Instructor

  • Ella - ella.bittiger@gmail.com
  • Stone - stone.bittiger@gmail.com
  • Miao - miao.peng@bittiger.io

• Teaching Assitant

  • Ye
  • Qirui
  • Yiqing

• Course Coordinator

  • Chloe
  • Joy

Syllabus

• Week 1: Statistical Foundations
• Week 2: Statistical Inference
• Week 3: Linear Regression
• Week 4: Tree Based Models
• Week 5: Logistic Regression
• Week 6: Natural Language Processing
• Week 7: Clustering
• Week 8: Recommendation System

Week 1: Statistical Foundations

	Day (US)	Readings	Lecture Notes	Instructor
Knowledge	Friday	To be posted	To be posted	Ella
Practice	Saturday	To be posted	To be posted	Ella
Code Lab	Tuesday	To be posted	To be posted	Ella

---

Week 2: Statistical Inference

	Day (US)	Readings	Lecture Notes	Instructor
Knowledge	Friday	To be posted	To be posted	Ella
Practice	Saturday	To be posted	To be posted	Ella
Code Lab	Tuesday	To be posted	To be posted	Ella

---

Week 3: Linear Regression

	Day (US)	Readings	Lecture Notes	Instructor
Knowledge	Friday	To be posted	To be posted	Ella
Practice	Saturday	To be posted	To be posted	Ella
Code Lab	Tuesday	To be posted	To be posted	Ella

---

Week 4: Tree Based Models

	Day (US)	Readings	Lecture Notes	Instructor
Knowledge	Friday	To be posted	To be posted	Ella
Practice	Saturday	To be posted	To be posted	Ella
Code Lab	Tuesday	To be posted	To be posted	Ella

---

Week 5: Logistic Regression

	Day (US)	Readings	Lecture Notes	Instructor
Knowledge	Friday	To be posted	To be posted	Stone
Practice	Saturday	1. Python environment setup	To be posted	Stone
Code Lab	Tuesday	To be posted	To be posted	Stone

---

Week 6: Natural Language Processing

	Day (US)	Readings	Lecture Notes	Instructor
Knowledge	Friday	To be posted	To be posted	Stone
Practice	Saturday	To be posted	To be posted	Stone
Code Lab	Tuesday	To be posted	To be posted	Stone

---

Week 7: Clustering

	Day (US)	Readings	Lecture Notes	Instructor
Knowledge	Friday	To be posted	To be posted	Stone
Practice	Saturday	To be posted	To be posted	Stone
Code Lab	Tuesday	To be posted	To be posted	Stone

---

Week 8: Recommendation System

	Day (US)	Readings	Lecture Notes	Instructor
Knowledge	Friday	To be posted	To be posted	Stone
Practice	Saturday	To be posted	To be posted	Stone
Code Lab	Tuesday	To be posted	To be posted	Stone

---

Notes

• Git and Github

  • Set up git
  • Git and Github learning resource
  • Github overall guides

• Python and Python tools

  • Required: Python environment setup
  • Scipy lectures
  • Scikit-Learn Tutorial

Textbooks

• Statistics

  • The Elements of Statistical Learning Data Mining, Inference, and Prediction
  • An Introduction to Statistical Learning with Applications in R

• Data Science and Machine Learning in Python

  • Introduction to Machine Learning with Python
  • Machine Learning In Action
  • Python Data Science Handbook

• Python Language

  • Introductory: Learn Python the Hard Way
  • Advanced: Effective Python

• Business and Data Science

  • Data Science For Business

• Natural Language Processing

  • Natural Language Processing with Python

• More...

  • 23 Free Data Science Books

Getting Help

• Data Science Stack Exchange
• Stats Stack Exchange
• MetaOptimize: ML and Datascience forum

Data Science Interview

• y-hat: What We Learned Analyzing Hundreds of Data Science Interviews
• Quora: How Do I Prepare for a Data Scientist Interview

Data Science Blogs

• Airbnb
• Uber
• StitchFix
• Facebook
• y-hat
• Machine Learning Mastery
• Data Science 101
• The Data Incubator: good examples of data science projects