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End-to-End Computer Vision

Registration Now Open!

Transform your AI projects with our hands-on ‘End-to-End Computer Vision’ course

Course Description

Are you ready to dive into the fascinating world of computer vision? Join our dynamic End-to-End Computer Vision course and discover how this cutting-edge technology is revolutionizing industries and applications worldwide.

In this hands-on course, you’ll master essential topics like image classification, object detection, and segmentation. Our expert instructors will guide you through every step, ensuring you gain a deep understanding of how to build, train, and deploy computer vision models using PyTorch. By the end of the course, you’ll not only be proficient in modern computer vision techniques but also confident in your ability to create and implement robust solutions for real-world challenges in AI and machine learning.

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.

Foundations in AI Pathway Courses:

Prerequisite

  • Python programming
  • Basic understanding of deep learning

Intended Audience

This course is aimed at software engineers, data scientists, data engineers, data analysts, research scientists, and developers who wish to gain a foundational understanding of computer vision and its real-world applications. Previous participants have included professionals from leading technology and AgriTech companies.

  • Learning Outcomes
  • Assessments
  • Course Outline

By the end of the course, you should be able to:

  • Recognize the fundamentals of computer vision, including its applications, challenges, and common tasks.
  • Develop computer vision models using PyTorch for various tasks such as image classification, object detection, and segmentation.
  • Apply data preprocessing, augmentation, and annotation techniques for computer vision datasets.
  • Apply transfer learning and fine-tuning techniques to leverage pre-trained models for computer vision tasks.
  • Evaluate computer vision models for performance and efficiency.
  • 3 Quizzes: Test comprehension of fundamental computer vision concepts.
  • 1 Coding Assignment: Implement solutions for image classification, object detection, and segmentation using PyTorch. Tasks include fine-tuning models, data preprocessing, and deployment.
  • Module 1: Introduction to Computer Vision
  • Module 2: Computer Vision Data Handling
  • Module 3: Computer Vision Model Architectures
  • Module 4: Model Training and Optimization

Course Procedures

The course starts on October 7, 2024. All coursework must be completed before the course ends on November 3, 2024. The approximate time to complete this course is 16 hours. You can complete the modules 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 a micro-credential badge upon completing the assessments at the end.

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

Translational_AI Center

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

 

Registration Cost: $750.00 $500 USD
(Initial Promo)
*$300 Student & Government Employee

Course Hours: 16 hours

Course Start Date: October 7, 2024

Last Day to Register: October 11, 2024

Course End Date: November 3, 2024

Course Access Time: 27 Days

*At the time of registration, you’ll be asked to create an account for this course. Use an email address ending in “.edu” or “.gov” to receive a discount. $200.00 will be immediately credit back after purchase.

Instructor

 

Zaki Jubery Profile PictureZaki 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.