Advanced Artificial Intelligence | Cornell University

Cornell University

Explore cutting-edge topics in AI, including Watson, human computation, deep learning, and the future of self-driving cars. Ideal for students and professionals seeking the latest AI advancements.

University CoursesArtificial IntelligenceMachine Learning

Introduction

An advanced course on cutting-edge topics in artificial intelligence, including Watson, human computation, deep learning, self-driving cars, and the future of AI.

Highlights

  • Covers the latest developments in AI, such as Watson, human computation, and deep learning
  • Explores the potential of AI in areas like self-driving cars and creative applications
  • Examines the ongoing debate on the nature of AI and its future direction

Recommendation

This course is recommended for students and professionals interested in the latest advancements in artificial intelligence. It provides a deep dive into the cutting-edge research and applications in this rapidly evolving field, making it a valuable opportunity for those seeking to stay at the forefront of AI.

How GetVM Works

Learn by Doing from Your Browser Sidebar

Access from Browser Sidebar

Access from Browser Sidebar

Simply install the browser extension and click to launch GetVM directly from your sidebar.

Select Your Playground

Select Your Playground

Choose your OS, IDE, or app from our playground library and launch it instantly.

Learn and Practice Side-by-Side

Learn and Practice Side-by-Side

Practice within the VM while following tutorials or videos side-by-side. Save your work with Pro for easy continuity.

Explore Similar Hands-on Tutorials

Getting Started with Artificial Intelligence , 2nd Edition 25
Technical TutorialsData ScienceMachine Learning
Comprehensive introduction to AI, covering machine learning and data science. Practical guide to building enterprise applications with real-world examples.
Machine Learning For Dummies, IBM Limited Edition 19
Technical TutorialsData ScienceMachine Learning
Comprehensive guide to machine learning and data science, suitable for beginners and experienced professionals. Authored by experts Daniel Kirsch and Judith Hurwitz.
Data Mining Concepts and Techniques 25
Technical TutorialsData ScienceMachine Learning
Comprehensive coverage of data mining concepts and techniques, including data preprocessing, classification, clustering, and association rule mining. Essential resource for students, researchers, and professionals in data mining, machine learning, and data analysis.
A Brief Introduction to Machine Learning for Engineers 29
Technical TutorialsMachine Learning
Gain a solid understanding of machine learning concepts and techniques for engineers. Covers supervised, unsupervised, probabilistic models, and advanced topics.
A Comprehensive Guide to Machine Learning 24
Technical TutorialsData ScienceMachine Learning
Detailed resource on machine learning, data science, and artificial intelligence. Authored by experienced experts, suitable for beginners and experienced learners.
A First Encounter with Machine Learning 2
Technical TutorialsData ScienceMachine Learning
Explore fundamental machine learning concepts, algorithms, and applications in data science. Suitable for beginners interested in learning about this rapidly growing field.
A Selective Overview of Deep Learning 3
Technical TutorialsDeep LearningMachine LearningNeural Networks
Comprehensive overview of key concepts and recent advancements in deep learning, covering neural network models, training techniques, and theoretical foundations.
Algorithms for Reinforcement Learning 6
Technical TutorialsMachine LearningReinforcement Learning
Comprehensive guide to reinforcement learning algorithms, covering dynamic programming, temporal difference, Monte-Carlo methods, and more. Suitable for researchers, students, and practitioners in AI, ML, and control engineering.
Approaching Almost Any Machine Learning Problem 8
Technical TutorialsMachine LearningPython
Comprehensive guide to problem-solving approaches in machine learning, suitable for beginners and experienced practitioners. Covers a wide range of ML topics and techniques.