This course is also listed in my guide to the best free data science courses. There are so many courses, tutorials, and guides available online that it is perfectly possible to gain a thorough grounding in these subjects without paying a penny. Today, with the wealth of freely available educational content online, it may not be necessary. This is another course focused on the open-source TensorFlow framework originally created by Google for use in Deep Learning, and is one that has received good reviews for giving an easy-to-follow guide to a complex technical subject. Find materials for this course in the pages linked along the left. Introduction to Artificial Intelligence - Intelligent Agents - State Space Search - Uninformed Search - Informed Search - Two Players Games - Constraint Satisfaction Problems - Knowledge Representation and Logic - Interface in Propositional Logics - First Order Logic - Reasoning Using First Order Logic - Resolution in FOPL - Rule Based System - Semantic Net - Reasoning in Semantic Net Frames - Planning - Rule Based Expart System-Reasoning with Uncertainty-Fuzzy Reasoning - Introduction to Learning - Rule Induction and Decision Trees - Learning Using neural Networks - Probabilistic Learning - Natural Language Processing. Often cited by AI experts as the single most important online resource for anyone wanting to learn AI, this course is led by Andrew Ng, who founded Google’s pioneering Google Brain deep learning program. All Rights Reserved, This is a BETA experience. This all helps to build a broad understanding of the many factors – technological or otherwise – that are important to consider when considering how AI could work for you. Home; Browse Lectures; People; Conferences; Academic Organisations With more than 2,400 courses available, OCW is delivering on the promise of open sharing of knowledge. Spring 2014 Lecture Videos Knowledge is your reward. Another course that takes a slightly different approach, here you are taken through the practical steps necessary to build machines that solve a number of real-world AI problems, such as driving a car or playing a game. Lecture 20, which focuses on the AI business, is not available. Deep learning is one of the most advanced fields of AI, and one that is pushing the boundaries of creating machines that can think and learn like humans. He helps organisations improve their business performance, use data more intelligently, and understand the implications of new technologies such as artificial intelligence, big data, blockchains, and the Internet of Things. These courses are aimed at a range of different audiences – maybe you want to actually learn how to design and code AI algorithms, maybe you want to bolt together the increasing range of “DIY” AI tools and services that are available, or maybe you need to manage AI projects in your organization. Lecture 2: Reasoning: Goal Trees and Problem Solving, Lecture 3: Reasoning: Goal Trees and Rule-Based Expert Systems, Lecture 4: Search: Depth-First, Hill Climbing, Beam, Lecture 5: Search: Optimal, Branch and Bound, A*, Lecture 6: Search: Games, Minimax, and Alpha-Beta, Lecture 7: Constraints: Interpreting Line Drawings, Lecture 8: Constraints: Search, Domain Reduction, Lecture 9: Constraints: Visual Object Recognition, Lecture 10: Introduction to Learning, Nearest Neighbors, Lecture 11: Learning: Identification Trees, Disorder, Lecture 14: Learning: Sparse Spaces, Phonology, Lecture 15: Learning: Near Misses, Felicity Conditions, Lecture 16: Learning: Support Vector Machines, Lecture 18: Representations: Classes, Trajectories, Transitions, Lecture 19: Architectures: GPS, SOAR, Subsumption, Society of Mind, Lecture 23: Model Merging, Cross-Modal Coupling, Course Summary. Like many of the courses covered here, all of the materials are freely available, but you can pay $50 for official certification at the end. Freely browse and use OCW materials at your own pace. Machine Learning and Blockchain: Mi... 43 Lectures 03:29:03. Excellent course helped me understand topic that i couldn't while attendinfg my college. Add to Cart. MIT OpenCourseWare is a free & open publication of material from thousands of MIT courses, covering the entire MIT curriculum. Below are full-length lecture videos that cover the content in this course. Another course from Andrew Ng – this one explicitly aimed at those who don’t need an in-depth technical understanding of the subject but who may want to begin leveraging AI in their organizations or working to roll out AI initiatives while working with non-technical teams. Adobe Stock. » It covers the workflow of running AI projects as well as how to develop a strategy around AI deployments in business. Contents: Introduction to Artificial Intelligence - Intelligent Agents - State Space Search - Uninformed Search - Informed Search - Two Players Games - Constraint Satisfaction Problems - … Description: In this lecture, Prof. Winston introduces artificial intelligence and provides a brief history of the field. Starting with theoretical principles such as "what is learning?" FreeVideoLectures aim to help millions of students across the world acquire knowledge, gain good grades, get jobs. The 10 Best Free Artificial Intelligence And Machine Learning Courses for 2020. The demand for people with knowledge and skills in artificial intelligence (AI) and machine learning (ML) hugely outstrips the supply. The last ten … Creative Applications of Deep Learning With Tensorflow – Kadenze (Class Central). Fall 2013 Lecture Videos This section provides full-length lecture videos that cover the content of the course. GATE Computer Science; NTA UGC NET Computer Science; ISRO SC – Computer Science This course gives a thorough grounding in the mathematical, statistical, and computer science fundamentals that go into developing and deploying automated learning machines. Send to friends and colleagues. Made for sharing. Artificial Intelligence A-Z: Learn How To Build An AI - Udemy. This Course is designed for the Students who are preparing for the Following Examinations. Fall 2012 Lecture Videos, Decision Diagrams / Value of Perfect Information, Advanced Applications: NLP, Games, and Robotic Cars, Advanced Applications: Computer Vision and Robotics, Machine Learning: Decision Trees and Neural Nets, Advanced Applications: NLP and Robotic Cars, Recording is a bit flaky, see Fall 2013 Lecture 4 for alternative, Recording is a bit flaky, see Fall 2013 Lecture 18 for alternative.