Data Science for Business

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Upskilling into the Latest Data Science Trends

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 a Professional Looking to Take Advantage of Emerging Opportunities in the Field of Data Science?

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.

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About the Certificate Program:

Our ten-month Data Science certificate is designed to provide solid theoretical frameworks in key areas of expertise within the field. Taught by seasoned industry experts, the program will guide participants through core principles, tools, and industry trends, culminating in a deep dive into artificial intelligence and machine learning.

This certificate includes the following courses:

data engineering Icon representing a laptop

Data Engineering

This course provides you with a technical overview of how to interpret, manage, and report data. You will learn about the history and principles of database systems and be able to source, prepare, and leverage historical data.

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

Python for Data Science

At its core, this course is project-based and integrates practical application as well as the opportunity to create and run your own Python projects.


Statistics for Data Science

Our Statistics for Data Science online program will provide you with the essential tools and analytical methods to manage data sets and extract meaningful insights from them.


Artificial Intelligence and Machine Learning

Acquire breadth of knowledge in predictive analytics, the Python programming language, and machine learning to confidently consider and resolve issues through the use of big data.

Strategic Data Storytelling

This online program will provide you with the techniques and tools you need to turn insights into compelling narratives. Over eight weeks, you will learn the art of conveying data in a meaningful way to support stakeholder decision-making and drive action.

Methodologies and Techniques Covered:

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 RStudio and its application
  4. Use scripting languages, including Python, to process, visualize, and analyze large data sets and implement machine learning solutions

Meet Your Instructors

Ashish Pujari, MSc
Ashish Pujari, MScData Engineering
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Ashish Pujari is a leader in data and analytics, IT strategy, and technology consulting. As a Director of Analytics at GLG, Pujari leads the design and implementation of business intelligence, predictive analytics, and visualization. Before joining GLG, Pujari served as an AVP of Analytics Architecture for CNA Insurance, where he was responsible for insurance analytics platforms and data strategy. Pujari specializes in big-data analytics, cloud computing, algorithm development, application and database design, decision management, and visualization technologies. He has been involved in technology consulting in finance, banking, insurance, and communications domains for clients in Europe, North America, and Asia.

Brian Craft, MSc
Brian Craft, MScPython for Data Science
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Brian Craft is a seasoned data scientist with years of industry experience. In his role as a data scientist at Conagra Brands, he focuses on scaling their machine learning capabilities and develops models to understand consumer purchase behavior and identify emerging ingredient and flavor trends.

Gregory Bernstein, MSc
Gregory Bernstein, MScStatistics for Data Science
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Gregory Bernstein works as a data scientist for Kinexon Sports and Media, a small branch of a German based company working with teams in the NBA, NFL and other professional leagues to monitor athletes’ movement and exertion, provide consultation regarding load management, and optimize in-game performance. Bernstein enjoys working in the startup environment and engages in analytical modeling, reporting and visualization, and product development. He earned a BA from Lafayette College in creative writing and economics in 2012 and graduated from the University of Chicago Master of Science in Analytics program in 2019. In addition to sports, Bernstein has a passion for teaching and education and has previously worked with the Princeton Review and as a TA for both the MS Analytics program and the Booth School of Business.

Shree Bharadwaj, MSc
Shree Bharadwaj, MScData Engineering and Strategic Data Storytelling
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Shree Bharadwaj works at West Monroe, a management consulting company. As a M&A Data and AI Practice Lead, he advises private equity and venture capital firms and C-level executives on value creation, post-close synergies, and data and analytics (BI/AI) strategies focused on business outcomes. In his previous executive leadership role at Syndigo, he led the data strategy, data science, next-gen platform and M&A integrations. His expertise revolves around driving innovation, standardization, development and operationalization of machine learning models, data engineering at scale using on-premise and cloud platforms, effective data visualizations, model-driven design, and algorithmic thinking. Bharadwaj was elected to the Global Standards Architecture Board at GS1, where he worked with global industry leaders to develop standards, road maps, and governance and compliance requirements relating to food services, healthcare, retail, supply chain, and CPG/FMCG verticals. His experience spans across multiple industries that include AdTech, EdTech, Fintech, healthcare, MarTech, public safety, retail, and telecom in organizations that range from startups to Fortune 100 companies.

Utku Pamuksuz, PhD
Utku Pamuksuz, PhDCorporate Financial Strategy and Decision-Making and Risk Management
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Dr. Pamuksuz is an AI researcher with expertise in data science, business analytics, applied mathematics, and machine/deep learning. He has been an invited speaker, delivering keynote sessions in academic and professional seminars in Europe, Asia, and the US, for application and development of data analytics in the areas of management, finance, strategy, healthcare, e-commerce, and quantitative marketing. Pamuksuz has served as a senior data scientist at State Farm as well as W.W. Grainger. He co-founded Inference Analytics in 2018.

Bridget Sheahan, MBA, CFA
Bridget Sheahan, MBA, CFAStrategic Data Storytelling
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Bridget Sheahan works as the VP of Analytics and Insights at Vericast (formerly Valassis Marketing Solutions), a global media and marketing services company. She leads the analytics services, data innovation, and data science teams. Prior to her current role at the company, Sheahan held various analytics-related positions, including serving as executive director of Client Analytics. Before joining Vericast, she was the director of Pricing and Marketing Analytics at the Learning Care Group.

Sheahan earned her bachelor’s degree from Colgate University and an MBA from the University of Pittsburgh’s Katz Graduate School of Business.

Career Outlook

Propelled by rising data volume and the growing adoption of sophisticated data management tools, the data science market platform is expected to grow 26.9% by 2027. Data engineering, statistics, AI and machine learning (ML), and Python coding are each fast-growing fields with an increased demand for qualified professionals. The World Economic Forum has ranked AI and ML roles as today’s most in-demand jobs. Statisticians will be 33% more employable by 2031. Python, one of the most popular programming languages, has seen an increase in the number of job openings for those who know it—from 70,242 positions in September 2019 to 79,942 in February 2021. Positions in data engineering are expected to grow 50% year-over-year.





Is the Python’s rank among programming languages that developers want to learn


Is the expected CAGR of the global data science platform size from 2020 to 2027

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

Admissions Process


Candidacy Fee:

Pay the candidacy fee (non-refundable) and fill out the application form.



Receive a call for an interview with our admissions team.​



Our Admission Committee will inform you of the final decision*.

*(2 business days max)

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.

Certificate participants will receive a certificate of completion.

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