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RESOURCES

Use the following resources to spply yourself and for additional help in the STEM field. These resources will help you learn more about STEM and will allow you to spark your interest in different topics.

Resources: Image

STEM in the Media:

Sign up for these great newsletters to keep up to date on recent development in scientific research and technology!

Wall Street Journal: The Future of Everything

Wall Street Journal: Tech Weekly

Newsletter: https://www.wsj.com/newsletters

New York Times: Tech Bits

Newsletter: https://www.nytimes.com/newsletters/bits

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STEM Education:

Need help with your homework in Science or Math class? Check out Khan Academy to find great video tutorials on any subject!

https://www.khanacademy.org/

Want free online classes to learn how to code? Check out these websites below!

https://www.codecademy.com/

https://scratch.mit.edu/

https://www.coursera.org/

https://edx.org/

https://udacity.com/

https://udemy.com/

https://freecodecamp.org

ttps://ocw.mit.edu â€“ online library of educational material from subjects taught at MIT – including CS

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Artificial Intelligence/Machine Learning:
https://www.tensorflow.org/ â€“ open-source software library for machine learning
http://scikit-learn.org/stable/index.html â€“ machine learning in Python
https://www.edx.org/…/artificial-intelligence-ai-columbiax-… â€“ edX course on artificial intelligence by Columbia University
https://www.edx.org/…/machine-learning-columbiax-csmm-102x-0 â€“ free edX course on machine learning by Columbia
https://www.coursera.org/learn/machine-learning â€“ free coursera course on machine learning by Stanford
https://www.coursera.org/learn/neural-networks â€“ free coursera course on neural networks by the UToronto
https://www.coursera.org/specializations/machine-learning â€“ coursera 4-part specialization – 7-day free trial, $49/mo to continue after trial – part 1: foundations, part 2: regression, part 3: classification, part 4: clustering/retrieval
http://www.work.caltech.edu/telecourse.html â€“ free online course taught by Caltech professor, includes lectures, homework sets & final exam
https://www.cs.ox.ac.uk/pe…/nando.defreitas/machinelearning/ â€“ course materials from Oxford machine learning course, includes slides & problem sets

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