AlignAI and The University of Cincinnati Team Up to Offer a ML OPS Course

Learn how to free-up Data Science time for more model building and less model support.

This course is for teams looking to scale their Data Science functions  while increasing the number and performance of models in production.  MLOps is the best practices and standards to deploy, monitor, and  improve A.I. models. Students learn an overview of MLOps and how to  apply best practices for your team.

This course does not require prerequisite knowledge.

4 online sessions with live instructors

This Course Addresses:

• Scaling Data Science - How do you shift data science teams to building more models?
• Increasing R.O.I. - How do you deploy more models in production to increase R.O.I. and adoption?
• Performance - How do teams quantify and improve model performance?

Learning Outcomes:

• Understand  and utilize the terminology, best practices, and critical concepts for  deploying, monitoring, and governing A.I. models.
• Automate the training, deployment, and monitoring of a model.
• Measure and monitor the performance of A.I. models.
• Govern A.I. models to increase R.O.I. and trust.

Learning Path:

Overview
Learn the terminology and concepts of enterprise MLOps, including process, roles, and best practices.

A.I. Architecture
Learn to design, architect, and deploy deep learning applications.

A.I. Pipelines
Build automated model pipelines for continuous training, integration, and deployment.

A.I. Monitoring
Measure, monitor, and improve model performance to maximize impact and R.O.I. throughout the model’s life cycle.

DATES AND TIMES

This class will be delivered on-line in four, 3.5-hour sessions over two weeks through Zoom with a live instructor.  Dates and times for this class are:

• Tuesday Sept 20- 12:45 PM - 4:15PM
• Thursday Sept 22 - 12:45 PM - 4:15PM
• Tuesday Sept 27- 12:45 PM - 4:15PM
• Thursday Sept 29 - 12:45 PM - 4:15PM

A good internet connection and dual screens are recommended to maximize the learning experience.  Links to the Zoom Training and class materials will be sent to registered attendees approximately 3-5 days before the class.

Certificate of Completion

A Certificate of Completion is provided with this course showing number of contact hours (instruction), and field of study as "Information Technology" for continuing education purposes. This course provides 12 contact hours and is equivalent to 1.2 CEU's.

The term CEU is not a trademarked term; therefore, any educational institution may use it to describe their courses. Professions and industries usually regulate their approved continuing education within their bylaws and not one institute or accrediting body has become a standard to accept in this regard. Professionals should always consult their Association or regulating body prior to embarking on continuing education and not assume a CEU will be accepted as part of their professional development.

Instructors

Brendan Kelly

Brendan focuses on helping teams align their processes, tools, and architecture to their product and business strategy. Brendan enjoys helping teams solve complex problems in technology adoption and innovation to change how people work. He brings hands-on experience helping enterprise organizations to design, deploy, and optimize ML and AI models. He also has helped teams utilize Agile, DevOps, ITSM, and ModelOps methodologies to drive organizational change. He also loves teaching and training on a variety of subjects including Analytics, Product, and Entrepreneurship

Steve Avsec

Steve Avsec is currently the Lead Data Scientist at DefenseStorm. He holds a Ph.D. in mathematics from the University of Illinois. After a career as a research mathematician, Steve transitioned to data science. He first led the data science practice at ModelOp, where he helped to develop industry standards for the development and monitoring of production machine learning models. At DefenseStorm, he has been developing best-in-class models for anomaly detection in the cybersecurity and fraud industries.

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