PROFESSIONAL CERTIFICATE IN

Data Science for Business

We know how valuable your time is. If you would rather schedule a call with our academic advisor at your convenience, you can do so here.

Request for Information

Empowering Business Success through Data Science Expertise

As the business world evolves, professionals in finance roles need to continuously reskill and upskill to stay on top of the latest industry tools, trends, and terminology. The constant flux of applications, programs, and technologies demands a diverse array of data science professionals with evolving knowledge and up-to-date toolkits.

Certificate Overview

Data science, an interdisciplinary field that includes mathematics, statistics, computer science, and other science skills, seeks to extract actionable insights from the large and ever-growing volumes of data that organizations currently generate. Data science practitioners prepare data for analysis and processing, perform advanced data analysis, and present results to reveal patterns and enable stakeholders to draw informed conclusions.

Are You Looking to Leverage Emerging Data Science Opportunities to Enhance Business Outcomes?

Professionals with backgrounds in computer science, data analysis, mathematics, programming, or statistics who want to sharpen their skills for today’s data-driven industries will highly benefit from this certificate program.

A man and a woman discussing a chart

About the Learning Journey

The Professional Certificate in Data Science for Business comprises the following eight-week courses:

This certificate includes the following courses:

data engineering Icon representing a laptop

Course 1: Data Engineering

This course provides a technical overview of data collection, storage, management, and usage to bolster business intelligence.

- Phyton-for-Data-ScienceIllustration of parallel data science images

Course 2: Python for Data Science

Project-based and application-oriented, the course will teach you how to design, write, and run high-performing Python code.

Statistics-for-Data-Scientists

Course 3: Statistics for Data Science

This course equips you with the core tools to manage datasets, extract meaningful insights, and enhance decision-making processes.

artificial-Intelligence-and-Machine-Learning

Course 4: Artificial Intelligence and Machine Learning

In this course, you will expand your Python skills and acquire the mathematical and theoretical frameworks to leverage machine learning.

Course 5: Strategic Data Storytelling

The course teaches you the art of conveying insights through compelling narratives to drive impactful, data-led decision-making.

Methodologies and Techniques

logos of the following methodologies and techniques: Python, Jupyter, MySQL, mongoDB, Neo4J, OpenRefine, Tableau, Google Cloud, and Anaconda

After completing the program, you will be able to:

  1. Build and extract insights from document databases.
  2. Design code that runs in parallel using multiprocessing and multithreading functionality.
  3. Understand R and RStudio and their applications.
  4. Use scripting languages, including Python, to process, visualize, and analyze large datasets and implement machine-learning solutions.
  5. Apply techniques and tools to turn data-driven insights into compelling narratives.

 

Earn a certificate of completion from the University of Chicago and become part of the UChicago network.

Meet Your Instructors

img instructor Abid-Ali

Abid Ali, PhD

Data Engineering Instructor 

Abid Ali has spent a large part of his career working in data and analytics at major consulting firms, designing and delivering large-scale transformations worldwide across industries. He leads internal initiatives and capabilities and works with C-suite executives to devise strategies for migration and transition to modern data platforms.   
 
A believer in lifelong learning, Ali has earned several advanced degrees, including two master’s degrees, an EMBA, and a PhD in Organizational Leadership, as well as certifications from Teradata, Celonis, SAFe Agile, Azure, and AWS.  

instructor Gregory Bernstein

Gregory Bernstein, MSc

Statistics for Data Science Instructor 

Gregory Bernstein works as a data scientist and product manager for Kinexon Sports and Media, a branch of a Germany-based company that works with teams in the NBA, NFL, and other professional leagues to monitor athletes’ movement and exertion, provide consultation on load management, and optimize in-game performance. Bernstein enjoys working in the start-up environment and engages in analytical modeling, content creation, and strategic decision-making for product development. He earned a BA from Lafayette College in 2012 and an MSc in Analytics from the University of Chicago in 2019.

img instructor Patrick-McQuillan

Patrick McQuillan, MBA

Python for Data Science Instructor 

Patrick McQuillan is passionate about data as a tool for change and decision-making. He has held leadership roles, most recently as the Global Head of Data Governance and Operational Effectiveness at Wayfair. Previously, he led international consulting teams to drive AI strategy and technology enablement for Fortune 100, government, and higher education clients. 
 
A sought-after subject matter expert in data governance, business intelligence, and AI strategy, McQuillan earned an MBA from the University of Oxford and a Bachelor of Economics and International Affairs from Northeastern University. 

instructor-Utku-Pamuksuz

Utku Pamuksuz, PhD

Artificial Intelligence and Machine Learning Instructor 

Utku Pamuksuz is an AI and analytics professor with expertise in data science, applied mathematics, and machine and deep learning. As a frequent guest speaker, he delivers academic and professional seminars. His published research involves AI algorithms in management, finance, strategy, healthcare, e-commerce, and quantitative marketing. He cofounded Inference Analytics, a Chicago-based healthcare analytics company, and serves as chief scientist. 
 
Dr. Pamuksuz has a PhD in IS/Analytics from the University of Illinois Urbana-Champaign and an MSc in Computer Science from Northwestern University. 

instructor-Rebeca-Pop

Rebeca Pop, MA

Strategic Data Storytelling Co-Instructor  

Rebeca Pop is the founder of Vizlogue and an expert in data storytelling and visualization. She has delivered presentations to over 3,500 participants worldwide. Her training approach is grounded in understanding adult learning strategies and combines hands-on exercises with feedback sessions and real-life examples.  
 
Pop has a decade of experience in marketing science and analytics at media agencies across industries. She has published thought leadership articles on Everviz.com, the Data Visualization Society’s Nightingale, and the UN blog. She earned her MA from the University of Oklahoma. 

Bridget Sheahan, MBA, CFA

Strategic Data Storytelling Co-Instructor  

Bridget Sheahan works as the VP of Analytics and Insights at Vericast, a global media and marketing services company. She leads teams that work with companies of all sizes and verticals to create, innovate, and consult on marketing strategy. Prior to her current role, Sheahan held a number of analytics-related and marketing positions at retail, automotive, and financial companies. 
 
She earned a BA from Colgate University and an MBA from the University of Pittsburgh’s Katz Graduate School of Business. 

Michael Colella, MS, MA, MS

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.

Career Outlook

In today’s rapidly evolving business landscape, data science has become a cornerstone of decision-making across industries. Given data’s exponential growth, businesses increasingly rely on data scientists to extract insights and drive strategic initiatives. As companies continue to invest in technology and analytics, the demand for skilled data scientists is expected to surge, offering lucrative career opportunities in finance, healthcare, retail, and beyond. With the potential to revolutionize operations, enhance customer experiences, and boost profitability, data science remains at the forefront of innovation, shaping the future of business.

$

108

k

The average annual base salary for a data scientist in the United States.

Source: U.S. Bureau of Labor Statistics

35

%

The projected growth in employment of data scientists to 2032.

Source: U.S. Bureau of Labor Statistics

26.9%

The expected CAGR of the global data science platform size to 2027.

Source: Cision

Potential Job Titles in Data Science
  • Analytics Consultant
  • AI Engineer
  • AI Specialist
  • Big Data Engineer
  • Business Intelligence Developer
  • Business Intelligence Engineer
  • Computer Vision Engineer
  • Data Architect
  • Data Insight Analyst
  • Data-Mining Analyst
  • Data Scientist
  • Database Administrator
  • Entry-Level Software Developer
  • GIS Analyst
  • Junior Python Developer
  • Machine Learning Engineer
  • Machine Learning Researcher
  • Machine Learning Specialist
  • Python Full-Stack Developer
  • Quality Assurance Engineer
  • Senior Python Developer
  • Statistician

Admission Process

1

Application

Complete the application form and pay the non-refundable fee.

2

Interview

Receive a call for an interview with our Admissions Team.

3

Results

Our Admissions Committee will inform you of their final decision within two business days.

The University of Chicago Approach to Online Learning-img-CEU

The University of Chicago Approach to Online Learning

Our online learning programs are crafted with your specific needs in mind.

Certificate programs combine e-learning with live, interactive sessions to strengthen your skill set while maximizing your time. We couple academic theory and business knowledge with practical real-world application.

Through online learning sessions, you will have an opportunity to grow your professional network and interact with University of Chicago instructors and your classmates.

Why the University of Chicago?

Becoming a member of the University of Chicago community means gaining access to world-class instructors and a cohort of curious, diverse individuals.

Through a firm grounding in core principles and a rigorous approach to problem-solving, our teaching method—the Chicago Approach—will give you the tools you need to make sense of complex data and turn ideas into impact.

Participants will receive a certificate of completion.

Why the University of Chicago?-Tower-img-