For beginners to advanced developers, the Intel® AI Developer Program teaches about AI, how to make deep learning faster on Intel® hardware, and how to advance research. Learn from courses, connect with experts, and use the latest tools.
Step 1: Learn AI
Start with this large collection of courses, special resources for students and professors, and a library of research papers, webinars, and tutorials.
Written by experts, these courses cover the basics of machine learning and extend to advanced theory. Each course includes homework and example code to teach you how to build AI applications.
Gain practical knowledge of supervised learning algorithms, key machine learning concepts, and more. (12 weeks)
Learn the basics of deep learning, the fundamentals of neural, convolutional, and recurrent network architectures, and more. (12 weeks)
Ready-to-use courses, hands-on exercises, cloud compute, and faculty support for creating curriculum or teaching AI in the classroom.
Learn from free courses, sign up for the Intel® AI DevCloud compute space, join the student ambassadors for more resources, and learn about Intel's latest innovations in AI.
Get free software and tools to enhance your research development, obtain extended access to the Intel AI DevCloud, and find out early about new hardware from Intel.
Access this extensive library of content written by developers, industry experts, and student ambassadors.
Topics include machine learning, developing AI software with Intel® hardware and tools, and the latest frameworks and libraries.
Read about AI innovations that use Intel® technology and how the technology is used to advance research and application development.
Step 2: Explore Frameworks
Use the most popular software frameworks to develop machine learning applications now optimized for Intel® hardware to provide greater speed and accuracy.
This open-source software library from Google* is equipped with optimizations for Intel® CPUs to increase speed.
Create powerful applications and reduce development time with this framework for machine learning.