Artificial Intelligence and Data Science for Leaders

Learn the latest AI and data science technologies, tools, and best practices to become a better leader.

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At a Glance

Open Enrollment
6 Weeks
Total CEUs:
4.6 CEUs
Also offered in:

Upcoming Dates

July Start

Students may register up to 7 days after the course start.

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Learn about the current trends in data science and machine learning from industry insiders. 

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The six-week Artificial Intelligence (AI) and Data Science for Leaders course at the University of Chicago is designed to future-fit your business for the digital age. Learn about statistical inference, machine learning, and emerging technologies to smoothly integrate AI into your organization and optimize the way your employees work with machines.

Designed For

Designed for managers and leaders across different industries who want to increase their understanding of AI and those that work with technical teams, analytics groups, and others who leverage data science to create value. Managers seeking to build and lead an AI-driven organization will also benefit from this program.

Learning Objectives to Become a Leader in AI

More and more companies are making use of AI as a way of increasing productivity. But what exactly is AI and why is it so important for today’s organizations? Our course will teach you to distinguish between the myths and opportunities that data science presents for your business with statistical inference and machine learning, as well as emerging tools such as auto machine learning and AI.

After completing the course, you will be able to: 

  • Create a strategy for your organization that makes use of AI to accomplish business goals.
  • Build a team for success in an AI world.
  • Choose the best areas for early stage development, and understand how to scale AI solutions.
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Is Your Company Future-Fit?

Learn how the AI and Data Science for Leaders course can bring your company to the next level.

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Data Science Curriculum

Our courses are designed to introduce you to the range of new data science and artificial intelligence technologies and tools. You will learn to: 

  • Identify new skills necessary for your business.
  • Develop a strategic plan to manage change within your team, function, or organization.
  • Identify the risks and rewards of new data science projects.

Data Science for Leaders online course format

  • Six weeks in length.
  • Weekly, self-paced interactive learning modules and assignments are time-sensitive and should be completed by the set deadlines.
  • Synchronous sessions and live question and answer sessions.
  • Mentors to provide continuous support and encourage a dynamic and positive learning environment.

Weekly course schedule

Describe the general challenges and opportunities that data, data science, and AI present leaders across organizations and industries and identify where in your own organization there may be opportunities for strong data science leadership. Understand the diversity of roles required for data science teams to be effective and how they work together.

Learn the five key variables that determine a company's success. You will have the opportunity to hone your business and financial acumen by identifying and analyzing economic data from sample financial documents. To conclude, we will discuss how to estimate the economic value of a data science project.

Explore the economic drivers of a business, understand approaches in the continuous development of business acumen, and  learn how to conduct an economic value estimation.

Learn to distinguish among the major subdisciplines and trends in the machine learning landscape and to describe various techniques and use cases for supervised, unsupervised, and reinforcement learning. You will also learn to identify the ML approaches that would be most promising for your own business problems.

This module will focus on other key features of artificial intelligence, anomaly detection, and model interpretation and assessment. Every successful learning model is subject to replacement or improvement as data cycles through different states. Learning models become outmoded and must be improved upon or replaced; unlearning or relearning parameters is a crucial part of creating successful models.

This final module will further your understanding of AI as an end-to-end service by examining use cases. We will take a closer look at adopting AI in the healthcare industry and consider potential pitfalls in the deployment phase. We will also consider Amazon Web Services (AWS) as an end-to-end solution and review the services available through this system. The module will conclude with an assignment about data ethics and privacy.

Meet Your Instructors

Courageous thinkers and passionate teachers, our instructors are an active community of scholars. Propelled by rigorous debate and cross-disciplinary collaboration, they produce ideas that matter and enrich human life.

Michael Colella, MSc, MA

Michael Colella, MSc, MA

Senior Director of Global Data Strategy and Analytics, AXS

Michael Colella is the senior director of Global Data Strategy and Analytics at AXS, where he leads business intelligence, analytics engineering, and web analytics. He is passionate about helping organizations use advanced analytics and AI to thrive.

Learn more about Michael

Utku Pamuksuz, PhD

Utku Pamuksuz, PhD

Assistant Clinical Professor & Co-Founder Inference Analytics

Dr. Pamuksuz is an AI professor with expertise in applied mathematics and machine/deep learning. His work has been published in a variety of analytics journals including IEEE-Transactions on Artificial Intelligence. He has been invited to speak at the respective national and international...

Learn more about Utku

Career Outlook

The artificial intelligence and data science industries are booming, with an expected market value of 99.9 billion dollars by 2023 in the case of the former and 16 billion by 2025 for the latter. An increasingly wide range of industries—automotive, entertainment, healthcare, media, retail, and telecommunications—need professionals with the skills to leverage AI and data science.

$ 165 k

The average annual base pay for a CTO in the US

75 %

The number of C-Suite executives who believe scaling AI over the next five years is crucial to the survival of their business

$ 99.9 B

The projected market value of the artificial intelligence industry by 2023

Potential job titles for leaders with Artificial Intelligence and Data Science skills

  • Analytics Consultant  
  • Analytics Specialist 
  • Artificial Intelligence Specialist  
  • Big Data Developer 
  • Business Intelligence Developer 
  • Chief Information Officer 
  • Chief Technology Officer 
  • Digital Innovation Officer 
  • Digital Product Director 
  • Director of Strategy 
  • Insights Analyst 
  • Program Director 
  • Program Manager 

Offered by The University of Chicago's Professional Education

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