Difference between revisions of "Courses & Certifications"
| Line 2: | Line 2: | ||
* [[Reading Material]] | * [[Reading Material]] | ||
| − | === YouTube Courses === | + | ==== YouTube Courses ==== |
* [https://www.youtube.com/watch?v=sRy26qWejOI&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN Application of Deep Neural Networks | Washington University in St. Louis] | * [https://www.youtube.com/watch?v=sRy26qWejOI&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN Application of Deep Neural Networks | Washington University in St. Louis] | ||
* [http://www.youtube.com/watch?v=J7LqgglEfQw&list=PL9zFgBale5fug7z_YlD9M0x8gdZ7ziXen Introduction to AI | Well Academy ] | * [http://www.youtube.com/watch?v=J7LqgglEfQw&list=PL9zFgBale5fug7z_YlD9M0x8gdZ7ziXen Introduction to AI | Well Academy ] | ||
Revision as of 04:55, 26 August 2018
Contents
YouTube Courses
- Application of Deep Neural Networks | Washington University in St. Louis
- Introduction to AI | Well Academy
- Introduction to Artificial Intelligence | Edureka
Pluralsight
Udemy
- Complete Guide to TensorFlow for Deep Learning with Python | Jose Portilla - Udemy
- Data Science and Machine Learning Bootcamp with R | Jose Portilla - Udemy
- Scala and Spark for Big Data and Machine Learning | Jose Portilla - Udemy
- Python for Data Science and Machine Learning Bootcamp | Jose Portilla - Udemy
- Deep Learning A-Z™: Hands-On Artificial Neural Networks | Kirill Eremenko, Hadelin de Ponteves - Udemy
- Machine Learning A-Z™: Hands-On Python & R In Data Science | Kirill Eremenko, Hadelin de Ponteves - Udemy
- Data Science, Deep Learning, & Machine Learning with Python | Frank Kane - Udemy
Coursera =
- Deep Learning Specialization | Andrew Ng - Coursera
- Machine Learning | Stanford- Coursera
- Machine Learning Specialization | University of Washington - Coursera
- Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization | Stanford - Coursera
- Structuring Machine Learning Projects | Stanford - Coursera
- Sequence Models | Stanford - Coursera
- Convolutional Neural Networks | Stanford - Coursera
Stanford
- Natural Language Processing with Deep Learning | Stanford
- Convolutional Neural Networks for Visual Recognition | Stanford
MIT =
- Introduction to Deep Learning | MIT
- Artificial Intelligence | MIT
- Deep Learning for Self-Driving Cars | MIT
- Learn with Google AI
- Machine Learning Crash Course with TensorFlow APIs | Google
- Learn TensorFlow and deep learning, without a Ph.D. | Google
- Deep Learning | Google
Microsoft
Amazon
IBM
Other Courses
- NVIDIA Deep Learning Institute (DLI)
- Intel AI Academy
- Kaggle Hands-On Data Science Education
- Creative Applications of Deep Learning with TensorFlow | Kadenze
- Artificial Intelligence (AI) | Columbia University
- CS188 Intro to AI | UC Berkeley
- Deep Learning for Natural Language Processing | Oxford - Phil Blunsom
- Intro to Artificial Intelligence | Udacity
- MOOC Training Course | PM.org
- Machine Learning | Georgia Institute of Technology
- Introduction to Deep Learning | Higher School of Economics
- Introduction to Reinforcement Learning | Higher School of Economics
- Natural Language Processing | Higher School of Economics
- Deep Learning in Computer Vision | Higher School of Economics
- Deep Learning for Business | Yonsei University
- Cutting Edge Deep Learning For Coders | fast.ai and University of San Francisco
- Deep Learning Fundamentals | Cognitive Class
- Deep Learning with TensorFlow | Cognitive Class
- Online Course on Neural Networks | Université de Sherbrooke - Hugo Larochelle
- Machine Learning: 2014-2015 | Oxford - Nando de Freitas
- Deep Learning Summer School 2015 | Yoshua Bengio, Roland Memisevic, Yann LeCun
- Neural Networks for Machine Learning 2013 | University of Toronto - Geoffrey Hinton the godfather of deep learning