Lead A.I., Machine Learning, and Data Science Projects With Confidence

This popular immersive course from the University of Georgia is now available fully online.

Built for business executives and mid-level managers leading or involved in digital transformations, this class teaches the basics of cutting-edge data science and machine learning technologies, and how to implement them in their businesses. Designed for people with little to no coding experience, Practical Machine Learning and Data Science for Managers provides hands-on experience building and implementing data science projects. Upon course completion, you will earn a Digital Badge that signifies your new skillset and expands your career opportunities.

Snapshot

Format: Live-Online

Hours: 25

Credits: 2.5 CEUs

Cost: $2,399
  • The basics of data science and data analytics using machine learning
  • The basics of developing use cases for business impact and the resources required
  • How a data science project is executed, and its results are interpreted
  • About data sources, data creation, data pre-processing, and the data analytics model building process based on machine learning
  • How to implement data science and machine learning in your company projects
  • How to use non-programming type machine learning tools and software for the non-practitioner
  • How to use data to build predictive analytics models and to measure their performance
  • About cutting-edge technologies like Deep Learning and their applications
  • Data generation, data pre-processing, building a model, predicting, inferencing, and telling a story
  • Key terminology of AI, machine learning, and data science

For a complete listing of Learning Objectives, please download the file.

Successful enrollees earn a Digital Badge, Certificate of Program Completion, and University of Georgia Continuing Education Units (CEUs).

Who Should Attend?

  • Mid to senior-level employee who are involved in a data science project or who want to start one for their current business
  • Business managers and plant managers engaged with their company’s digital transformation programs
  • Small and large business owners who need to understand the basics of cutting-edge data science technologies and how and where to apply them
  • Product management professionals who are involved in the development of data-driven products (IoT, wearables, etc.)
  • Business executives and mangers seeking to expand their basic skill set in the space of data science

Course Information

Course Fee(s): 

$2,399 (U.S. Funds)

Refund and Program Cancellation Policies
The Georgia Center will gladly issue refunds (minus a $250 processing fee) for cancellations made on or before September 10, 2021. No refunds will be made for cancellations after September 10, 2021. Substitutions are welcomed with advance written notice to the Georgia Center.

Learn from the best!

Taught by UGA Professor of Practice, College of Engineering, Jagannath Rao, a 33-year veteran of international manufacturer Siemens, was involved in developing and executing IoT business and customer use cases. With his decades of experience in this area, there is nobody better to teach this course.

Jagannath Rao, Professor of Practice, School of Engineering – University of Georgia

Jagannath Rao, Professor of Practice, School of Engineering at UGAJagannath Rao runs a complete course on Machine Learning and Data Science as part of the Georgia Informatics institute in the engineering school. He retired in 2018, working for 33 years at the global conglomerate Siemens and brings rich industry experience in areas ranging from Industrial Automation to the Internet of Things. Apart from an education in AI, he has also spent many years in the practical application of these technologies in the business world, and that includes the widespread application of “Big Data” technologies in the realm of manufacturing, including plant analytics, asset analytics, and digital services. In addition to his role at UGA, he also consults with industry clients in the space of AI & Machine Learning in the context of generating use cases and applying / implementing those technologies.

Professor Rao is an Electrical engineer with a graduate degree in Knowledge Engineering (AI) and an MBA. He has worked around the globe in India, Germany, Singapore, and the USA. With more than 30 years’ experience, including practical hands-on implementation, he brings a large body of expertise to the young engineers and industry professionals graduating today.

He has also served as the Chair of the Advisory Board, the University of Georgia – Athens, College of Engineering, and on the advisory boards of Arizona State University W.P. Carey School of Business, Center for Services Leadership, and the Georgia Institute of Technology, School of Biomedical Engineering, Advisory Board.