Deep Learning and AI Online Courses You Should Be Taking Right Now

Deep learning and AI is the next big thing. Microsoft, Apple, Google, Facebook, and other tech giants of Silicon Valley are conducting research, developing systems, improving existing systems (Siri, Google Assistant, Facebook Algorithm) to connect on an almost human level with humans. This means that for the next few decades, people with deep learning and AI programming skills, analysis and testing skills will be in huge demand. Already there are hundreds of courses out there on the Internet focusing on the two subjects, so if you’re looking for something new to learn in tech, this is the best time. If you’re already a part of deep learning or AI projects, this is also a great time to equip yourself with the best info out there.

Ready? Enroll yourself in these online courses and get the best of new age learning.

Neural Networks for Machine Learning by The University of Toronto in Coursera

Artificial neural networks refer to a computational model that is based on the structures and functions of a biological neural network. A neural network attempts to learn and adapt based on the input it receives which means that it tries to come at par with human level of intelligence. The ANN is currently being used for machine learning and is being applied to speech and object recognition as well as for modeling human motion. The Neural Networks for Machine Learning course is taught by Geoffrey Hinton who was one of the most influential AI researchers and neural networks of his time.

Deep Learning Specialization by Coursera

Coursera was amongst the first online institutes to offer an in-depth course on AI knowledge and deep learning. The site has five deep learning courses and is taught by some of the most famous names in the world of ANN. You will be familiarized with model networks as Convolutional networks, RNNs, LSTM, BatchNorm and a lot more. The best part? The course covers the use of AI in all major industries; from medical to music, driving to sign language and natural language processing. This is a great course to dive into if you have the bucks!

Deep Learning by Google in Collaboration with Udacity

Google has its own course on deep learning and attempts to familiarize the learner with the very foundations of deep learning – why we need it and what we can achieve with massive datasets of human behavior. With the help of AI, numerous problems could be resolved, and more ease can be brought into human life. The course is designed to help anyone new to machine learning to get a more philosophical aspect of it and perhaps come to appreciate human intelligence as well as machine intelligence.

Deep Learning A-Z: Hands on Artificial Neural Networks with Udemy

Where Google deals with the philosophical side, Udemy takes it a step further with the technical aspects of neural networks. This Deep Learning A-Z: Hands on Artificial Neural Networks course helps programmers and coders develop deep learning algorithms in Python from two machine learning and data science experts. It is a highly recommended course for people with skills or exposure in algorithm development.

Practical Deep Learning for Coders

The course is designed specifically for coders with at least a year of experience. An intensive 7-hours course, Practical Deep Learning for Coders provides learners with the basics of key mathematical and modeling tools. After the course, you become equipped to identify exciting AI opportunities and how you can use the knowledge obtained to provide relevant solutions. Once you complete part-1, you can move onto part-2 where you’re taught about the latest development, practices, and achievements of AI programming.

If you haven’t already got any learning goal lined up for this year (or the next), we’d say this is high time you got started with the next big revolution in the world of tech.

Farah tries to keep up with the fast-paced tech world by writing about it. She covers latest tech news and writes informative pieces to help her readers make informed decisions about their tech preferences.