Modern ML systems sometimes undergo qualitative shifts in behavior simply by “scaling up” the number of parameters and training examples. Given this, how can we extrapolate the behavior of...

Understand Artificial Intelligence, its principles and techniques with this Standford engineering course. The course would cover Machine Learning, Search Algorithms, Markov's decision processes,...

This course aims to teach learners about the REX Neo Architecture, an energy-efficient processor design. By the end of the course, students will understand the inefficiencies of current...

This course aims to explore the quest for low storage latency and its impact on changing storage technologies. By the end of the course, learners will understand the need for lower latency in...

This course aims to teach learners about synchronized, multi-sensory integrated learning environments. The learning outcomes include understanding the OHIO principle, time accuracy...

This course covers the learning outcomes and goals of understanding security in Software Defined Networks (SDN). Students will learn about classic network perimeter defense, network threat...

The next stage of human-computer evolution, Scalable Intelligent Systems, integrates people, communications, and computers into a unified cooperative environment. Think of it as moving beyond...

The course will take you through the essentials of nonprofit and philanthropy strategy. You will apply the basic elements of strategic planning―from defining the problem through designing a...

This course teaches learners how to create safe and easy-to-use passwords. The learning outcomes include understanding authentication methods, comparing passwords vs passphrases, and learning...

Autonomous robots need to be efficient and agile, and be able to handle a wide range of tasks and environmental conditions. This requires the ability to learn good representations of domains...

This course covers practical applications of blockchain technology, exploring its implications and limitations in real-world scenarios. Students will learn about track responsibility, key...

This course teaches how to create persistent and unforgeable watermarks for Deep Neural Networks. The learning outcomes include understanding the importance of IP protection for model...

This course covers the evolution of computer architecture from the early days of IBM's incompatible computer lines to the current era of Domain Specific Architectures (DSAs). The learning...

To apply neural networks to different applications, various customized hardware architectures are proposed in the past a few years to boost the energy efficiency of deep learning...

This course covers the basics of R: a free programming language and software environment used for statistical computing and graphics. R is widely used by data analysts, statisticians, and...

This course covers the TimeSeries AggregatoR (TSAR) tool, focusing on its design principles, data schema coordination, and operational simplicity. Students will learn about time series aggregation...

Conversational applications often are over-hyped and under perform. While there's been significant progress in Natural Language Understanding (NLU) in academia and a huge growing market for...