Learn-Data-Science-in-3-months
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Course Curriculum and Resources for Learning Data Science in 3 Months
Learn Data Science in 3 Months
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
- Youtube (Freecodecamp) https://www.youtube.com/watch?v=LHBE6Q9XlzI
- Youtube (Data Analysis) https://www.youtube.com/watch?v=GPVsHOlRBBI
Week 2 - Statistics & Probability
- Krish Naik https://www.youtube.com/watch?v=zRUliXuwJCQ&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO
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
Week 1-2 - Algorithms & Machine Learning
- Krish Naik https://www.youtube.com/watch?v=bPrmA1SEN2k&list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe
Week 3 - Deep Learning
- Read Part 1 and 2 of DL Book https://www.deeplearningbook.org/
- Intro to Deep Learning https://www.youtube.com/watch?v=VyWAvY2CF9c
- Tensorflow For Deep Learning https://www.youtube.com/watch?v=qFJeN9V1ZsI
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
- NoSQL https://www.youtube.com/watch?v=E-1xI85Zog8
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 Big Data
- Edx https://www.edx.org/course/big-data-analytics-using-spark
Week 4 Kaggle Project #3
- Try your best at a competition of your choice from Kaggle.