At 12-15 hrs/week
Get access to classroom immediately on enrollment
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
from industry experts
Personal career coach and
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.
As the founder and president of Udacity, Sebastian’s mission is to democratize education. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass, and more.
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.
I do wish that the test cases used in submission were built into the unit testing. I understand to an extent why it's protected in the remote, but it would have been handy to help debug an issue that I was running into. Based on the instructions, it wasn't clear that I needed to replace the code in my previous work in the classroom with assign_value to get the full history to work with, and it also wasn't clear that the naked_twins was meant to be used in conjunction with the depth first search and not as a replacement. The original puzzle provided in the solution.py file is solvable just by reduce_puzzle and naked_twins... no depth first search required, so that threw me for a bit of a loop.
The Nanodegree is a high-quality class I've wished for. The most significant difference to other courses is that Udacity Nanodegrees will motivate you really strong! It's such a fantastic community with great inspiring mentors. I personally will use Udacity as long as it exists, maybe one time, I will complete every possible Nanodegree! Udacity is an investment in yourself, do it! If you can also study perfectly with only a book and have fun, go for it, but I think this is a super rare skill. If you want to have fun and get curious about the topic, go with Udacity!
High quality video content, well presented. Comparable to Andrew NG's Deep Learning Specialization or the MITx Pro Quantum Computing Fundamentals course. Technical unit tests using an IDE feel better than editing half written functions in Jupyter notebook (with an autograder), or random example code. Quizzes have explanations videos, which is improvement over the Coursera quiz model. I like how you include textbook readings, extracurricular submodules and content links to other courses. Overall, this feels very much like an online university course. Impressed!
This was an excellent program, that covered many aspects of the field with clear concepts and great exercises and projects. The project evaluation was good and detailed, from the concepts to the code review. Thanks for a great NanoDegree!.
I have no AI background. I am a programmer. I think I will be able to keep going. I also thought once we subscribed to the program it would no start before the "enroll date" but the deadlines started as soon as I paid for the course.
This program is matching my expectations so far. The Sudoku Solver has helped me build an initial intuition about how to structure AI projects and how to apply search and constraints in order to maximize algorithm efficiency.
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.
If you are new to Python programming, we suggest our AI Programming with Python Nanodegree program. You must have completed a course in computer science algorithms equivalent to the Data Structures & Algorithms 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 content and curriculum to support four (4) projects. We estimate that students can complete the program in three (3) months working 10 hours per week.
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 Program FAQs 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.