Mastering PyTorch

Course Description

Master PyTorch, an open-source deep learning framework for AI. This course covers everything from the Tensors computations, custom architectures, and advanced functions in PyTorch. It also covers how to debug PyTorch codes to gain confidence in debugging codes.

The course is packed with plenty of hands-on activities, homework, and instructor consulting to make learning PyTorch enjoyable and rewarding. Tackle real-world problems, from image recognition to natural language processing. By the end of this course, you’ll have the skills and confidence to tackle any machine-learning challenge with PyTorch.

This course is one of 6 courses in the Foundations in AI pilot Micro-Credential pathway offered by the Translational AI Center at Iowa State University.

Complete any 3 courses listed below to earn the Foundations in AI badge:

• Machine Learning Operations (MLOps)
• End-to-End Computer Vision
• Generative Models
• Mastering PyTorch
• End-to-End Natural Language Processing
• Interpretability in AI

Learn more about Micro-Credentials at Iowa State University!

Prerequisites

• Basic python programming
• Basic understanding of deep learning

Intended Audience

The course is intended for a broad audience within the spectrum of the software and technology industry, including software engineers, data scientists, data engineers, data analysts, research scientists, and software developers. The course is designed to provide a basic understanding of AI and how to use PyTorch for a broad range of audiences.

Course Procedures

The course starts on February 3, 2025. All coursework must be completed by March 31, 2025, in order to earn the micro-credential badge. You will continue to have access to the course materials until January 1, 2026. The approximate time to complete this course is 16 hours. 

This course has an instructional period from February 3 to March 2, 2025. During this instructional period, course materials will be released weekly and live synchronous sessions will be held. You may complete the course materials at your own pace. Live Zoom meetings will be conducted for interactive coding sessions. A suitable time for these live sessions will be determined through a group poll. The recordings of those sessions will be available soon after each meeting.

You will receive the Mastering PyTorch micro-credential badge upon successful completion of the course assessments.

Course Materials

Course materials are provided within the course. No additional purchase is required.

Contact Information

Contact isopd@iastate.edu for more information.

Course Developer

The Translational AI Center breaks down disciplinary silos to bring together core Iowa State artificial intelligence researchers and subject matter experts interested in applying new technologies to their work. For more information, visit Translational AI Center at Iowa State University

Instructor

Zaki Jubery, Research Scientist

Zaki Jubery is a research scientist in the Translational AI Center (TrAC) at Iowa State University. His research interests are in (i) High-throughput phenotyping (ii) Crop modeling (iii) Image processing (iv) Applied machine learning in agriculture.

Zaki works on integrating engineering tools into various agricultural applications. He has been dedicated to pioneering research in this field since September 2013.

Zaki earned his Ph.D. in Mechanical Engineering from Washington State University and completed a postdoctoral fellowship at the University of Illinois Urbana-Champaign. Before transitioning to agriculture, his background includes designing, simulating, and manufacturing point-of-care microfluidics sensors for biomedical and industrial applications.