University of Colorado Boulder via Coursera Learning path or series
This specialization is intended for computer scientists and engineers wishing to expand their technical expertise to the realm of Computing Security, with a broad skill-set and understanding of offensive Cybersecurity. Regardless of what area of Computing you may want to specialize in – from networking and systems to algorithms in machine learning and AI – a deep understanding of how the underlying technologies work, and how they can be abused, is essential to a robustly functioning, secure computing environment. One thing we have learned from the remarkable history of Computing is that staying ahead of attackers requires adopting the adversarial mindset. We aim to develop this mindset through a series of three courses, each exploring a different realm of technology. Throughout the series, expect an in-depth technical treatment with little reliance on pre-made tooling, as we seek to create exploits from scratch. By completing the specialization, you will have gained exposure to modern attacks on computer networks, web applications, binary programs, and cutting-edge areas of research in subverting AI systems.
Some points apply to every course of this kind; see how we rank.
University of Colorado Boulder is in Tier 3: good universities, respected companies, nonprofits and well-known teachers of our institution ranking (76/100). Large online catalogue, good quality.
MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: http://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathe…
A curated collection of videos featuring top experts in artificial intelligence.
-Learn more and enroll in the program: https://online.stanford.edu/programs/generative-ai-technology-business-and-society-program Recent advancements in generative AI are reshaping industries, pushing technological boundaries, and revolutionizing creative processes. In this fast-changing landscape…
For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai Delve into the exciting world of Artificial Intelligence with insights and research from the world's top experts. This playlist offers a comprehensive journey, from foundational machine learning con…
Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (cluster…
View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In these lectures, Prof. Patrick Winston introduces the 6.034 material from a conceptual, big-picture perspective. Topics include reasoning, search, constraints, learning, representations, architectures, and probabili…
