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Explore advanced algorithms for autonomous aerial and ground vehicles, enabling aggressive navigation in unknown environments through rapid decision-making and obstacle avoidance techniques.
Explore gaze mechanisms for embodied agents and social robots, covering design, implementation, and evaluation of interactive gaze behaviors to enhance human-robot communication and collaboration.
Uncovering hidden dependencies in software to improve testing efficiency and effectiveness. Explores techniques for reducing testing time, detecting dependencies, and specifying data-related test oracles.
Explore goal-directed dynamics in robotics, featuring a novel control framework with built-in optimization. Learn about soft-constraint physics models and their applications in various robotic control scenarios.
Explore automated techniques for verifying and improving numerical software accuracy, addressing challenges in finite-precision arithmetic and error estimation for scientific computing applications.
Explore P, a framework for designing and validating event-driven asynchronous systems. Learn key concepts, real-world applications, and open research problems in this innovative programming approach.
Explore assistive robotics and human intent recognition through nonverbal behavior. Learn how robots can provide social and physical assistance by understanding human goals and intentions.
Explore the Lean theorem prover's architecture, features, and goals. Learn how it bridges interactive and automated theorem proving, and its applications in various mathematical domains.
Explore integrated strategies for planning, perception, and action in complex mobile manipulation domains using belief space planning and hierarchical goal regression.
Explore the evolution of computer vision and AI with Ali Farhadi, covering deep neural networks, object detection, visual reasoning, and future predictions in this insightful seminar.
Probabilistic models for learning semantic parser lexicons from question/answer pairs, improving accuracy and efficiency without extensive human input or dataset-specific engineering.
Explores decision-theoretic planning for optimizing crowdsourced workflows, covering POMDPs, dynamic workflow switching, taxonomy construction, and data annotation optimization for machine learning applications.
Exploring analytical gradients in physics simulation for computational design of dynamic systems, with applications in robotics, biomechanics, and computer graphics.
Explore dynamic robot manipulation through integrated planning, deep learning, and cloud computing for high-speed, reliable motions in unstructured environments.
Explore innovative approaches to robot perception and planning for manipulating diverse objects, enhancing capabilities in cloth handling, articulated objects, and transparent materials.
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