Resources for the 22-week plan:

(This course is planned considering 20 hours/week of commitment)

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Foundational

 

Week 1-3

• Data Analysis in Excel​​

  • https://www.youtube.com/watch?v=OOWAk2aLEfk

  • https://www.educba.com/data-analysis-tool-in-excel/

  • ​https://www.excel-easy.com/data-analysis.html

• Statistical Analysis​

  • https://www.youtube.com/watch?v=xxpc-HPKN28

  • ​https://www.kdnuggets.com/2020/06/8-basic-statistics-concepts.html

• Probability Theory​

  • ​https://www.youtube.com/playlist?list=PLaFfQroTgZnxtnfht3BzBHVfxodX9AR9F

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Week 4-6

• Data Structures

  • ​https://www.geeksforgeeks.org/data-structures/

• Algorithms and analysis​

  • ​https://www.geeksforgeeks.org/fundamentals-of-algorithms/

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Intermediate

 

Week 7-12

• Programming​​

  • Python: https://www.coursera.org/learn/python-crash-course (Audit for free)

  • R: https://www.coursera.org/learn/r-programming Audit for free)

• Open source libraries​

  • NumPy: https://www.w3schools.com/python/numpy/numpy_intro.asp​

  • Pandas: https://www.w3schools.com/python/pandas/default.asp

• Databases​

  • SQL: https://www.w3schools.com/python/python_mysql_getstarted.asp

  • MongoDB: https://www.w3schools.com/python/python_mongodb_getstarted.asp

• Data Vizualization

  • All libraries - Python: https://mode.com/blog/python-data-visualization-libraries/ (Choose 2-3 libraries)

  • Data viz in R: https://rkabacoff.github.io/datavis/

 

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​ Advanced

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Week 13-17

• Machine Learning: 

  • Course: https://www.udacity.com/course/intro-to-machine-learning--ud120

• Deep Learning:

  • Course 1,2 and 4: https://www.coursera.org/specializations/deep-learning​

 

Week 18-22

• Advanced Machine Learning

  • Computer Vision: https://vision.soe.ucsc.edu/projects

  • Human-computer interaction: https://hcii.cmu.edu/summer-research-program/projects 

  • Reinforcement learning: https://neptune.ai/blog/best-reinforcement-learning-tutorials-examples-projects-and-courses

  • Speech/Text Processing: 

    • ​https://analyticsindiamag.com/8-different-nlp-scenarios-one-can-take-up-for-a-project/

    • https://www.upgrad.com/blog/speech-processing-projects-topics-for-beginners-experienced/

 

 

For projects, please choose from Kaggle and practice.

 

Your feedback and suggestion is much appreciated. Please send it to contact.illuminate.ai@gmail.com​​​​

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