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.
Join the #DataSciencein3Months channel in our Slack channel to find one.
- 3 Projects
- 1 Weekly assignment. Pick 1 from the course for each week, do it in a weekend.
- 12 Weeks
- 2-3 Hours of Study per Day
- Python, SQL, R, Tensorflow, Hadoop, MapReduce, Spark, GitHub,
- Watch videos at 2x or 3x speed using a browser extension
- Handwrite notes as you watch for memory retention
- Immerse yourself in the community
- EdX https://www.edx.org/course/introduction-python-data-science-2
- Siraj Raval https://www.youtube.com/watch?v=T5pRlIbr6gg&list=PL2-dafEMk2A6QKz1mrk1uIGfHkC1zZ6UU
- Try your best at a competition of your choice from Kaggle.
- Use Kaggle Learn as a helpful guide
- Part 1 and 2 of DL Book https://www.deeplearningbook.org/
- Siraj Raval https://www.youtube.com/watch?v=vOppzHpvTiQ&list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3
- 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.
- Udacity https://www.udacity.com/course/intro-to-relational-databases--ud197
- EdX https://www.edx.org/course/introduction-to-nosql-data-solutions-2
- Udacity https://www.udacity.com/course/intro-to-hadoop-and-mapreduce--ud617
- Spark Workshop https://stanford.edu/~rezab/sparkclass/slides/itas_workshop.pdf
- Try your best at a competition of your choice from Kaggle.