Learn all the essentials for AI programming with Python
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Study 10 hrs/week and complete in 3 months
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.
Start building deep learning applications in just three months. Learn foundational AI skills as you work through a world-class curriculum. Learn from experts in the field, and amass core skills that will make your next career steps possible.
Master every key tool needed for AI success: Python, NumPy, Jupyter Notebooks, Pandas, Matplotlib, and PyTorch—all in one program.
Receive personalized feedback from AI experts when you submit your first neural network project. They’ll provide detailed and actionable insight, and challenge you to do your best work.
Engage with a Udacity mentor throughout your program experience. Learn faster and more confidently with 1:1 support from an AI expert.
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Formal prerequisites include basic knowledge of algebra and calculus. Basic programming knowledge will help to quickly pick up AI’s essential coding concepts. See detailed requirements.
Start coding with Python, drawing upon libraries and automation scripts to solve complex problems quickly.
Learn how to use all the key tools for working with data in Python: Anaconda, NumPy, Pandas, and Matplotlib.
Learn the foundational math you need for AI success: vectors, linear transformations, and matrices—as well as the linear algebra behind neural networks.
Gain a solid foundation in the hottest fields in AI: neural networks, deep learning, and PyTorch.Build Your Own Neural Network
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, Masters in Biostatistics, and 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.
This was a very good program, I learned a lot from it. Now I have a good understanding of AI network and how they are trained and used. and I'm ready to dive a bit deeper, and go to tthe next level All material presented was sufficient to complete the project. But with many personal interruptions, I felt that I had to do a treasure hunt to find the info to put together the final projects; we had bits and pieces of all the info, but with variation on implementation, and probably with some confusion on Pytorch usage (reading from files, or directory structure, or going from numpy to pytorch, etc). This was compounded by the inability to train torchvision VGG16 model with CUDA on my own NVidia 780 GTX TI with 3GB of ram (I was running out of memory, but I was able to do “prediction”). And the fact that I was getting disconnected every so often when running on Udacity server with CUDA (repeat, restart, etc), and not getting convergence, while trying to debug the code, and trying to internalize the transform and other factors, made it a bit difficult to complete some tasks in one sitting. I wish there were some hints, and more indication on what to look for; e.g. it would have been nice to about trying different lower value “LearnRate”, I would have saved a week. And there are many gotchas too: like saving the model parameters ( which ones), and if you save in CUDA, the model would not run on my desktop ( which has no CUDA). Also, it was nice to have classmate comments and solution column, but the web-format was painful to use (hard to read, and follow)… But I ’m very thankful for the few hints I got from other classmates.
Good program. Liked it very much. Recommend
Challenging and fun. I'll recommended
In depth coverage of Python if you need it then jumps into Linear Algebra, and then into some topical programming.
Great program. It's clear, meaningful and cuts out a lot of noise when compared to other training programs. Also, I'm studying at one of the most elite tech universities in the world, and I can say that these modules are a far better source of knowledge (better structures, better content and far more practical in terms of delivery methods). The only thing I'd recommend is to have the option to be able to download a digital PDF of all the content for future references. I'm very grateful for Udacity and it's brilliant Nanodegrees!
Learn everything you need to start building your own AI applications.
AI is changing how entire industries operate—retail, education, healthcare, and almost every other field out there. 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 learning 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) 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.