/treenamu

Learn_Data_Science_in_3_Months

Course Objective

This is the Curriculum for Learn Data Science in 3 Months by Siraj Raval on Youtube. After completing this course, start applying for jobs, doing contract work, start your own data science consulting group, or just keep on learning. Remember to believe in your ability to learn. You can learn data science, you will learn data science, and if you stick to it, eventually you will master it.

Find a study buddy

Join the #DataSciencein3Months channel in our Slack channel to find one.

Components

  • 3 Projects
  • 1 Weekly assignment. Pick 1 from the course for each week, do it in a weekend.

Course Length

  • 12 Weeks
  • 2-3 Hours of Study per Day

Tools Used

  • Python, SQL, R, Tensorflow, Hadoop, MapReduce, Spark, GitHub,

Accelerated Learning Techniques

  • Watch videos at 2x or 3x speed using a browser extension
  • Handwrite notes as you watch for memory retention
  • Immerse yourself in the community

Month 1 - Data Analysis

Week 1 - Learn Python

Week 2 - Statistics & Probability

Week 3 Data Pre-processing, Data Visualization, Exploratory Data Analysis

Week 4 Kaggle Project #1

  • Try your best at a competition of your choice from Kaggle.
  • Use Kaggle Learn as a helpful guide

Month 2 - Machine Learning

Math of Machine Learning Cheat Sheets

Week 1-2 - Algorithms & Machine Learning

Week 3 - Deep Learning

Week 4 - Kaggle Project #2

  • Try your best at a competition of your choice from Kaggle. Make sure to add great documentation to your github repository! Github is the new resume.

Month 3 - Real-World Tools

Week 1 Databases (SQL + NoSQL)

Week 2 Hadoop & Map Reduce + Spark

Week 3 Data Storytelling

Week 4 Kaggle Project #3

  • Try your best at a competition of your choice from Kaggle.