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
- Enrollment
- Open Enrollment
- Duration
- 8 Weeks
- Format
- Online
- Total CEUs
- 4.6 CEUs
- Investment
-
$2,500
Upcoming Dates
April Start
June Start
Learn about the current trends in data science and machine learning from industry insiders.
The eight-week Artificial Intelligence (AI) and Data Science for Leaders program 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.
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 program 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 program, 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
Is Your Company Future-Fit?
Learn how the AI and Data Science for Leaders certificate program can bring your company to the next level.
Learn moreCurriculum
The 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
Program structure
- Eight 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 to create a plan to grow in your own professional life as a data science leader and understand how data-driven decision-making creates value beyond buzzwords. Understand how business acumen enables data-driven decision-making, and why it is crucial in the success of data scientists and data science projects.
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.
Understand future projections and trends in the AI realm and discover the usage of various algorithms in a simple to advanced spectrum for a specific use case. You will grasp the concepts of anomaly detection using AI and model interpretation and assessment.
Discover AI as an end-to-end service using the healthcare context as an example and learn the importance of open-source developments and understand the process behind employing full stack scalable big data pipelines with AWS as a use case. You will also analyze and act on the ethical implications of data management and research.
Develop leadership competencies for planning and building a world-class team and learn about the tools needed to set up your organization for data science and long-term success. In this module you will apply your learning to the real-world with a case study.
Apply knowledge gained from previous modules to a real-life use case by addressing a fully-formed business problem typically faced by data science teams and develop a team made up of technical and non-technical workers and define the role of each team member in the context of a real-life use case.
Meet your instructors
Greg Green, PhD
Associate Senior Instructional Professor, Director MScA Program
As director of analytics programs at the University of Chicago, Greg Green architects and leads programs that strategically apply analytics to solve complex industry problems with greater speed and impact.
Throughout his professional career, Greg has used his expertise in digital strategies...
Nalini Polavarapu, PhD
Vice President, Enterprise Analytics and Data Science
Dr. Nalini Polavarapu has been with Bayer for over ten years and leads data science strategy for a global team of analytical and IT professionals, specialized in machine learning, operations research, and cloud analytics to deliver better products to market faster through data science. Nalini also...
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...
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.
The average annual base pay for a CTO in the US
The number of C-Suite executives who believe scaling AI over the next five years is crucial to the survival of their business
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
