A plethora of online courses have emerged in recent years, offering everything from basic introductions to advanced implementations to boost familiarity with the complexities of AI technology. Whether one is a coding enthusiast or someone interested in applying AI to real-world problems, there’s a programme out there for everyone. Here is a line-up of some of the best free courses available:
Making Friends with Machine Learning: Taught by Cassie Kozyrkov, a data scientist, this course delves deeper into the technical aspects of AI and machine learning. You’ll explore different algorithms, their applications, and how they generate outputs with relatable examples.
Google Generative AI Learning Path: Focused specifically on generative AI, this is a crash course in machine learning offered by Google, using its machine learning library, TensorFlow. It covers everything from a basic introduction to designing and training neural nets.
Google’s Machine Learning: Offered through Udacity, this course is not for beginners. It assumes some previous experience with machine learning and focuses on deep-learning techniques. Meant for data analysts, scientists and engineers, it teaches how to apply machine learning and neural network technology effectively.
Stanford University’s Machine Learning: Taught by Andrew Ng, an industry expert, this comprehensive course on Coursera covers a wide range of real-world machine learning applications, including speech recognition and web search enhancement. It delves into technical depth, covering topics such as linear regression, back propagation and MATLAB tutorials. Certification is available for those seeking career prospects.
Columbia University’s Machine Learning: This course, available on edX, teaches models, methods and applications of machine learning for solving real-world problems using probabilistic and non-probabilistic methods, as well as supervised and unsupervised learning. Expect to dedicate eight-10 hours per week for three months to complete it.
Nvidia’s Fundamentals of Deep Learning for Computer Vision: The course explores the technical fundamentals of computer vision and natural language processing. It helps one identify situations where machines capable of object recognition and image classification can be applied, and emphasises the role of GPUs (Graphic Processing Unit), manufactured by Nvidia. Expect to spend around eight hours on the material.
MIT’s Deep Learning for Self Driving Cars: The course uses self-driving cars as a real-world application to explore AI. It covers interpreting sensor data and teaching machines to navigate roads. Incorporating the use of the MIT DeepTraffic simulator, it challenges students to teach a simulated car to drive safely in a busy environment. All lecture videos and exercises are accessible online.
