llSourcell/Learn_Data_Science_in_3_Months

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

• EdX https://www.edx.org/course/introduction-python-data-science-2
• Siraj Raval https://www.youtube.com/watch?v=T5pRlIbr6gg&list=PL2-dafEMk2A6QKz1mrk1uIGfHkC1zZ6UU

Week 2 - Statistics & Probability

• KhanAcademy https://www.khanacademy.org/math/statistics-probability

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

• EdX https://www.edx.org/course/introduction-to-computing-for-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

• Statistics
• Probability
• Calculus
• Linear Algebra

Week 1-2 - Algorithms & Machine Learning

• Columbia https://courses.edx.org/courses/course-v1:ColumbiaX+DS102X+2T2018/course/

Week 3 - Deep Learning

• Part 1 and 2 of DL Book https://www.deeplearningbook.org/
• Siraj Raval https://www.youtube.com/watch?v=vOppzHpvTiQ&list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3

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)

• Udacity https://www.udacity.com/course/intro-to-relational-databases--ud197
• EdX https://www.edx.org/course/introduction-to-nosql-data-solutions-2

Week 2 Hadoop & Map Reduce + Spark

• Udacity https://www.udacity.com/course/intro-to-hadoop-and-mapreduce--ud617
• Spark Workshop https://stanford.edu/~rezab/sparkclass/slides/itas_workshop.pdf

Week 3 Data Storytelling

• Edx https://www.edx.org/course/analytics-storytelling-impact-1

Week 4 Kaggle Project #3

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