At 10 hrs/week
Get access to classroom immediately on enrollment
Formal prerequisites include basic knowledge of algebra, and basic programming in any language.See detailed requirements.
Start coding with Python, drawing upon libraries and automation scripts to solve complex problems quickly.Use a Pre-trained Image Classifier to Identify Dog Breeds
Learn how to use all the key tools for working with data in Python: Jupyter Notebooks, NumPy, Anaconda, Pandas, and Matplotlib.
Learn the foundational linear algebra you need for AI success: vectors, linear transformations, and matrices—as well as the linear algebra behind neural networks.
Learn the foundations of calculus to understand how to train a neural network: plotting, derivatives, the chain rule, and more. See how these mathematical skills visually come to life with a neural network example.
Gain a solid foundation in the hottest fields in AI: neural networks, deep learning, and PyTorch.Create Your Own Image Classifier
from industry experts
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Ortal Arel has a PhD in Computer Engineering, and has been a professor and researcher in the field of applied cryptography. She has worked on design and analysis of intelligent algorithms for high-speed custom digital architectures.
Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Jennifer has a PhD in Computer Science and a Masters in Biostatistics; she was a professor at Florida Polytechnic University. She previously worked at RTI International and United Therapeutics as a statistician and computer scientist.
Juan is a computational physicist with a Masters in Astronomy. He is finishing his PhD in Biophysics. He previously worked at NASA developing space instruments and writing software to analyze large amounts of scientific data using machine learning techniques.
Grant Sanderson is the creator of the YouTube channel 3Blue1Brown, which is devoted to teaching math visually, using a custom-built animation tool. He was previously a content creator for Khan Academy.
Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
Mike is a Content Developer with a BS in Mathematics and Statistics. He received his PhD in Cognitive Science from the University of Irvine. Previously, he worked on Udacity's Data Analyst Nanodegree program as a support lead.
As a data scientist at Looplist, Juno built neural networks to analyze and categorize product images, a recommendation system to personalize shopping experiences for each user, and tools to generate insight into user behavior.
Andrew has an engineering degree from Yale, and has used his data science skills to build a jewelry business from the ground up. He has additionally created courses for Udacity’s Self-Driving Car Engineer Nanodegree program.
I'm very grateful for this opportunity! I enjoyed having a mentor who encouraged me and was patient. The program was detailed enough to learn online and I felt supported. Thanks!
The program is great and I am really happy with the quality of the content and projects.
I love the design of the course so far and the step by step guidance of the project.
The program is going good.
This helped me to understand the basic concepts for AI
Numbers don't lie. See what difference it makes in career searches.*
Career-seeking and job-ready graduates found a new, better job within six months of graduation.
Average salary increase for graduates who found a new, better job within six months of graduation.
AI-powered increases in safety, productivity, and efficiency are already improving our world, and the best is yet to come! As it becomes increasingly evident how impactful AI can be, demand for employees with AI skills increases—demand is in fact already skyrocketing.
The AI Programming with Python Nanodegree program makes it easy to learn the in-demand skills employers are looking for. You’ll learn foundational AI programming tools (Python, NumPy, PyTorch) and the essential math skills (linear algebra and calculus) that will enable you to start building your own AI applications in just three months.
Whether you’re seeking a full-time role in an AI-related field, want to start applying AI solutions in your current role, or simply want to start learning the defining technology of our time, this is the perfect place to get started.
While this is an introductory course that is not designed to prepare you for a specific job, after completing this program, you should be proficient in the skills used in the AI Industry, including but not limited to Python, machine learning, etc. If you wish to prepare for a full-time AI-related career, we recommend enrolling in our Machine Learning Engineer Nanodegree program next.
Learning to program with Python, one of the most widely used languages in Artificial Intelligence, is the core of this program. You’ll also focus on neural networks—AI’s main building blocks. By learning foundational AI and math skills, you lay the groundwork for advancing your career—whether you’re just starting out, or readying for a full-time role.
Formal prerequisites include basic knowledge of algebra and basic programming in any language. You will also need to be able to communicate fluently and professionally in written and spoken English.
No. This Nanodegree program accepts all applicants regardless of experience and specific background.
The AI Programming with Python Nanodegree program is comprised of content and curriculum to support two (2) 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 Nanodegree program FAQs for policies on enrollment in our programs.
We’ll teach you how to install all the software required. Virtually any 64-bit operating system with at least 8GB of RAM will be suitable. Udacity does not provide any hardware.