The list below is a small selection from Open Culture. We picked up classes relevant to data scientists, and removed links that no longer work at the time of writing. If you know of any other interesting courses, email me and we will include them if they are relevant.

The 78-video playlist above comes from a course called Neural Networks for Machine Learning, taught by Geoffrey Hinton, a computer science professor at the University of Toronto. The videos were created for a larger course taught on Coursera, which gets re-offered on a fairly regularly basis.

Neural Networks for Machine Learning will teach you about “artificial neural networks and how they’re being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc.” The courses emphasizes ” both the basic algorithms and the practical tricks needed to get them to work well.” It’s geared for an intermediate level learner – comfortable with calculus and with experience programming (Python).

You can find the video playlist on YouTube. For more free courses about computer science, click here. Below is a small selection.

Other Free Courses

• Advanced Algorithms – Free Online Video – Jelani Nelson, Harvard

• Advanced Data Structures – Free Online Video – Free Course Info & Video – Erik Demaine, MIT

• Algorithm Design and Analysis – Free iTunes Video – Free Online Video – Dan Gusfield, UC Davis

• Algorithms for Big Data – Free Online Video – Multiple professors, Harvard

• Artificial Intelligence – Free iTunes Video – Free Online Video & Course Info – Patrick Winston, MIT

• Artificial Intelligence – Free Online Video – Pieter Abbeel, UC Berkeley

• Artificial Intelligence – Natural Language Processing – Free Course in Multiple formats – Christopher Manning, Stanford

• Artificial Intelligence – Machine Learning – Free Online Video – Andrew Ng, Stanford

• Computational Discrete Mathematics – Free Web Course – Carnegie Mellon

• Computer Science: Foundations of Computer & Information Security – Free iTunes Video – Matt Bishop, UC Davis

• CS50, Harvard’s Introductory Computer Science Course (2016) – Free Online Course – David Malan, Harvard

• Discrete Mathematical Structures – Free Online Video – Kamala Krithivasan, IIT

• Discrete Mathematics and Probability Theory – Free Online Video – Umesh Vazirani, UC Berkeley

• Discrete Stochastic Processes –  Free Online Video – Free iTunes Video – Free Course Materials & Video – Robert Gallagher, MIT

• Discrete Structures – Free iTunes Video – Sergio Dibiasi, Rutgers

• Discrete Structures – Free iTunes Video – Stan Warford, Pepperdine

• Efficient Algorithms and Intractable Problems – Free iTunes Video – Free Online Video – Christos Papadimitriou & Satish Rao, UC Berkeley

• Foundations of Computer Graphics – Free Online Video – Ravi Ramamoorthi, UC Berkeley

• Introduction to Computer Science and Programming (Using Python) – Free Online Course – John Guttag, MIT

• Machine Learning – Free iTunes Video – Yaser S. Abu-Mostafa, CalTech

• Massively Parallel Computing – Free iTunes Video – Harvard

• Mathematics for Computer Science – Free Online Course Materials & Video – Tom Leighton, MIT

• Neural Networks for Machine Learning – Free Online Video – Geoffrey Hinton, University of Toronto

• Principles of Computing – Free Web Course – Carnegie Mellon

• Probabilistic Systems Analysis and Applied Probability – Free Online Video – Free Video & Course Info – John Tsitsiklis, MIT

• Python – Free Online Course – Nick Parlante, Google

• Quantum Computing for the Determined – Free Online Video – Michael Nielsen, The University of Queensland

• Search Engines: Technology, Society and Business – Free Online Video – Marti Hearst, UC Berkeley

• Signal Processing on Databases – Free iTunes Video – Jeremy Kepner, MIT

• Theory of Computation – Free iTunes Video – Free Online Video – UC Davis, David Gusfield

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  Reference

   https://www.datasciencecentral.com/profiles/blogs/neural-networks-for-machine-learning