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MLOps – Machine Learning Operations

Registration Now Open!

From Theory to Application: Mastering MLOps for Robust Machine Learning Solutions!

Course Description

Are you ready to take your machine learning expertise to the next level? Join our dynamic MLOps course and discover how machine learning has been transformed from a research tool into a key component of modern applications used by millions.

In this hands-on course, you’ll master essential topics like MLflow, Data Pipelines, RestAPI development, and containerization. Our expert instructors will guide you through every step, ensuring you gain a deep understanding of how to build, deploy, and manage machine learning models in production environments. By the end of the course, you’ll not only be proficient in modern MLOps tools and techniques but also confident in your ability to deploy and maintain robust machine-learning solutions.

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:

Prerequisites

  • 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 MLOps and create a basic pipeline for machine learning in production.

  • Learning Outcomes
  • Assessments
  • Course Outline

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

  • Apply set of DataOps for real-world datasets.
  • Complete a full cycle of Machine Learning Training.
  • Employ different Model Deployment strategies.
  • 2 Quizzes to help debug code errors (there will be unlimited attempts)
  • 2 Coding exercise questions which would include implementing python codes based on hands-on activities. This would include coding a pipeline for DataOps, and pipeline to build and deploy model.
  • Module 1: Introduction to MLOPS
  • Module 2: Model Training with MLFlow
  • Module 3: Model Deployment

Course Procedures

The course starts on September 6, 2024. All coursework must be completed before the course ends on October 6, 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: September 9, 2024

Last Day to Register: September 13, 2024

Course End Date: October 6, 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

 

Aditya-BaluAditya Balu, Data Scientist

Aditya Balu is a data scientist in the Translational AI Center (TrAC) at Iowa State University. His research interests are in (i) Geometry-aware scientific machine learning (ii) Distributed and Decentralized Deep Learning (iii) Geometry-aware computational simulation tools.

Aditya also works on several topics in AI and its applications to diverse domains such as healthcare imaging, transportation, manufacturing, design, etc.

As part of TrAC, Aditya has organized several tutorials and workshops at reputed conferences such as CVPR, AAAI, and Supercomputing. He also has several publications in Neurips, ICML, CVPR and AAAI.

Learn more about this instructor