Professional Certificate in Data Science for Business

Unlock the solutions hidden in data to take on business challenges with a Data Science certificate at UChicago.

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Data Science

At a Glance

Open Enrollment
10 months
Total CEUs:
25.7 CEUs
$12,500 for certificate

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.

Designed For

Designed for professionals with backgrounds in computer science, data analysis, mathematics, programming, or statistics who want to sharpen their skills for today’s data-driven industries.

Learning Objectives

Gain the skills you need to solve real-world problems with data. Upon completing the program, you will be equipped with the tools to put your interdisciplinary knowledge into practice in any industry that uses data to make better business decisions.

After completing the certificate program, you will be able to: 

  • Build and extract insights from document databases.
  • Design code that runs in parallel using multiprocessing and multithreading functionality.
  • Understand RStudio and its application.
  • Use scripting languages, including Python, to process, visualize, and analyze large data sets and implement machine learning solutions.
The Data Science Certificate at the University of Chicago

Drive Informed Decisions by Analyzing and Extracting Data

Discover how this data science certificate program can help you gain the tools and knowledge you need to enhance your decision-making process in a data-driven world. 

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The Certificate Explores the Following Topics:

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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.

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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.

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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.

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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.

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Strategic Data Storytelling

Learn the techniques and tools you need to turn insights into compelling narratives. Students will master the art of conveying data in a meaningful way to support stakeholder decision-making and drive action.

View the full data science curriculum

Career Outlook for Data Science Professionals

Propelled by rising data volume and the growing adoption of sophisticated data management tools, the data science market platform is expected to grow by 26.9 percent 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 thirty-three percent 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 percent year-over-year.

$ 97 k

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

# 1

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

26.9 %

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

Potential job titles for data scientists

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

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