Introduction to Artificial Intelligence: Fundamentals of AI e-learning from Udacity
Artificial Intelligence (AI) is a constantly developing field regularly gaining relevance in our daily lives. While AI has a long theoretical history, modern AI pushes well beyond theory, with the total number of representative applications growing all the time. It is useful in a number of different industries, from complex professions like robotics, quantum science and medical diagnosis to broader applications like journalism, gaming, and finance.
This course introduces the basics and driving applications of AI, including:
- machine learning
- computer vision
- probabilistic reasoning
- computer vision
- natural language processing
Upcoming start dates
Free E-Learning: Start Anytime!
- Self-paced Online
Who should attend?
This Introduction to Artificial Intelligence course is designed for anyone hoping to gain a clear understanding of how AI works and experience working with a number of applications.
This course builds upon probability theory and linear algebra. As such, participants should have a solid understanding of probability theory, similar to that covered in the Udacity Intro to Statistics courses.
Find out if this course is right for you - request more information here!
Training topics for this Introduction to Artificial Intelligence course is divided into two main parts:
Part I: Fundamentals of AI
- Overview of AI
- Statistics, Uncertainty, and Bayes networks
- Machine Learning
- Logic and Planning
- Markov Decision Processes and Reinforcement Learning
- Hidden Markov Models and Filters
- Adversarial and Advanced Planning
Part II: Applications of AI
- Image Processing and Computer Vision
- Robotics and robot motion planning
- Natural Language Processing and Information Retrieval
It is free to start this Introduction to Artificial Intelligence course
Estimated time for completion assuming 6 hours per week: Approx. 2 months
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