Learn AI theory and follow hands-on exercises with Intel free courses from the Intel® AI Academy for software developers, data scientists, and students. These lessons cover AI topics and explore tools and optimized libraries that take advantage of Intel® processors in personal computers and server workstations.
After completing this course, participants may receive a certificate.
• AI From the Data Center to the Edge
This AI course covers a data science workflow that starts with exploring a dataset and training a model and ends with deploying an application.
From the basics of AI to graduate-level topics in technical AI theory, these courses explain the intuition and mathematics behind AI.
Get an overview of the fundamentals of machine learning on modern Intel® architecture. (12 weeks)
• Deep Learning
Learn the basic techniques and foundations of deep learning on modern Intel architecture. (12 weeks)
• Introduction to AI
Explore the fundamentals of AI in this introductory course—without the math. (8 weeks)
• Natural Language Processing
Get an overview of how machines process and classify textual information. (8 weeks)
• Time-Series Analysis
Study the techniques used to analyze and process sequential data to predict future data. (8 weeks)
• Deep Learning for Robotics
Find out how to use deep learning instead of traditional robotics algorithms in this course from Arizona State University. (4 weeks)
• Anomaly Detection
Combine machine learning and statistics to solve this vital component of many industrial applications. (8 weeks)
Learn how to use Intel® hardware from high-performance data center processors and accelerators to fast edge inference devices.
• Deep Learning Inference with Intel® FPGAs
Master how to engineer high-speed machine learning inference applications on powerful Intel® FPGAs. (5 weeks)
• AI on PC
Overcome the challenges of AI on edge devices using Windows* Machine Learning, ONNX*, and OpenVINO™ toolkit on Intel hardware. (8 weeks)
• AI on the Edge with Computer Vision
Learn how to use the Intel® Movidius™ Neural Compute Stick (NCS) for deep learning inference on edge devices.
Use the best software frameworks to quickly develop AI applications that can run anywhere from edge devices to across an entire data center.
• Deep Learning with BigDL
Combine the power of AI and big data using BigDL, a distributed deep learning framework for Apache Spark*. (10 weeks)
• Distributed AI with the Ray Framework
Use Ray, a Python* framework from UC Berkeley’s RISELab, to distribute AI training across many processors. (5 weeks)
• Applied Deep Learning with TensorFlow*
Master the basics of using TensorFlow* with Intel architecture. (8 weeks)