Study 12-15 hrs/week and complete in 3 months.
Learn from the world’s foremost AI experts, and develop a deep understanding of algorithms being applied to real-world problems in natural language processing, computer vision, bioinformatics, and more. Practice a structured approach for applying these techniques to new challenges, and emerge fully prepared to advance in the field.
Learn AI algorithms that have been successfully applied to real world problems in NLP, computer vision, bioinformatics, and more. Learn how to solve problems with these tools so that you can apply them in the real world.
Explore probabilistic models for pattern recognition with Sebastian Thrun, founder of Google’s self-driving car team. Discover how to implement key AI algorithms with Peter Norvig, co-author of the leading AI textbook. Learn how to frame and solve modern AI problems, and gain real-world experience.
Work on specially-designed projects, and receive detailed feedback on each from our mentors.
Work on career-caliber projects that will populate and enhance your professional profile, and benefit from detailed and actionable feedback from project reviewers who will help ensure you're doing your best work.
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This program requires experience with linear algebra, statistics, and Python (including object-oriented programming).See detailed requirements.
Use constraint propagation and search to build an agent that reasons like a human would to efficiently solve any Sudoku puzzle.Build a Sudoku Solver
Build agents that can reason to achieve their goals using search and symbolic logic—like the NASA Mars rovers.Build a Forward Planning Agent
Extend classical search to adversarial domains, to build agents that make good decisions without any human intervention—such as the DeepMind AlphaGo agent.Build an Adversarial Game Playing Agent
Model real-world uncertainty through probability to perform pattern recognition.Part of Speech Tagging
“AI is going to create all sorts of new jobs. I think it's nothing but upside and exciting for those who know what to do with it.”— Jordan Bitterman, CMO, IBM Watson Content & IoT Platform
Research Director, Google
Peter Norvig is a Director of Research at Google and is co-author of Artificial Intelligence: A Modern Approach, the leading textbook in the field.
Sebastian Thrun is a scientist, educator, inventor, and entrepreneur. Prior to founding Udacity, he launched Google’s self-driving car project.
Professor of Computer Science, Georgia Tech
Thad Starner is the director of the Contextual Computing Group (CCG) at Georgia Tech and is also the longest-serving Technical Lead/Manager on Google's Glass project.
The program was great, but it would be better for me if more advanced lectures were provided. I love the way that the projects were going, which helped me a lot!
EPIC!. I have learnt so many things along the way. Most importantly, How to deal with python dictionaries :P (They are everywhere!). Thanks for this experience!
This has been fantastic experience, I get to learn more about AI and AI algorithms and continue to build application on this platform.
Difficult but worth taking!
To make it even easier to learn, you can finance your Nanodegree through Affirm.
As low as $84 per month at 0% APR.
Pay your monthly bill using a bank transfer, check, or debit card.
Learn everything you need to start building your own AI applications
The Artificial Intelligence Nanodegree program features expert instructors, and world-class curriculum built in collaboration with top companies in the field. The program offers a broad introduction to the field of artificial intelligence, and can help you maximize your potential as an artificial intelligence or machine learning engineer. If you’re ready for an efficient and effective immersion in the world of AI, with the goal of pursuing new opportunities in the field, this is an excellent program for you.
This Nanodegree program is designed to build on your existing skills as an engineer or developer. As such, it doesn't prepare you for a specific job, but instead expands your skills with artificial intelligence algorithms. These skills can be applied to various applications such as video game AI, pathfinding for robots, and recognizing patterns over time like handwriting and sign language.
In this Nanodegree program, you will learn from the world’s foremost AI experts, and develop a deep understanding of algorithms being applied to real-world problems in Natural Language Processing, Computer Vision, Bioinformatics and more. If your goal is to become an AI expert, then this program is ideal, because it teaches you some of the most important algorithms in AI. You’ll benefit from a structured approach for applying these techniques to new challenges, and emerge from the program fully prepared to advance in the field.
You must have completed a course in Deep Learning equivalent to the Deep Learning Nanodegree program prior to entering the program. Additionally, you should have the following knowledge: Intermediate Python programming knowledge, including:
Basic shell scripting:
Basic statistical knowledge, including:
Intermediate differential calculus and linear algebra, including:
Additionally, you should be able to follow and interpret pseudocode for algorithms like the example below and implement them in Python. You should also be able to informally evaluate the time or space complexity of an algorithm. For example, you should be able to explain that a for loop that does constant O(1) work on each iteration over an array of length n has a complexity of O(n).
function Hill-Climbing(problem) returns a State current <- Make-Node(problem.Initial-State) loop do neighbor <- a highest-valued successor of current if neighbor.value ≤ current.value then return current.state current <- neighbor
We have a number of courses and programs we can recommend that will help prepare you for the program, depending on the areas you need to address. For example:
No. This Nanodegree program accepts all applicants regardless of experience and specific background.
The Artificial Intelligence Nanodegree program is comprised of one (1) three (3)- month Term. The Terms have fixed start and end dates.
To graduate, students must successfully complete four (4) projects, each of which affords you the opportunity to apply and demonstrate new skills that you learn in the lessons. Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
Please see the Udacity Nanodegree program FAQs found here for policies on enrollment in our programs.
You will need a computer running a 64-bit operating system (most modern Windows, OS X, and Linux versions will work) with at least 8GB of RAM, along with administrator account permissions sufficient to install programs including Anaconda with Python 3.5 and supporting packages. Your network should allow secure connections to remote hosts (like SSH). We will provide you with instructions to install the required software packages. Udacity does not provide any hardware.