Study 10 hrs/week and complete in 3 months
Learning material and communication in English
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 two 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.
Learn with the support of mentors from the very beginning of the program, and connect with thousands of fellow students on dedicated Udacity-moderated platforms.
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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: Jupyter Notebooks, 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
“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
Ortal Arel has a PhD in Computer Engineering, and has been 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.
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