Skill up this spring and SAVE! Use code SPRINGSKILLS to save 15%. Exclusions apply

Professional Certificate in Data Science and Analytics

Delivered in collaboration with Emeritus.

  • START DATE May 7, 2025 More Dates
  • TIME COMMITMENT 15-20 hours/week
  • DURATION 24 weeks
  • FORMAT Online
  • CEUs 36
  • PRICE $7,550
The Professional Certificate in Data Science and Analytics from MIT xPRO equips you with the expertise needed for this in-demand field. You'll explore data science fundamentals and advanced AI/ML concepts relevant to data professionals. Expand your skill set by learning to use cutting-edge tools like Python and Google Colab, enhancing decision-making and translating technical results into actionable insights.

What You Will Learn

Organizations are increasingly relying on data scientists and analysts to provide insights from big data for business success. Skilled data professionals are in high demand for their ability to uncover opportunities for growth and profit. In fact, data science is ranked as the third-best profession in the United States with 13,500 annual job openings projected through 2031. The Professional Certificate in Data Science and Analytics program from MIT xPRO will help you develop the skills needed for data-driven decision making and career advancement in this thriving field.

  • Leverage data to optimize or improve decision making within an organization
  • Train, organize, run, and analyze datasets and models that yield meaningful results using Python and Google Colab
  • Analyze and decipher technical results into actionable business insights for executives

Who Should Enroll

  • The program is ideal for:

    • Data professionals in engineering, finance, insurance, IT, or operations with coding experience who are looking to develop an advanced data analysis skill set that can be applied at work to make informative business decisions
    • Business professionals in sales, marketing, IT, or operations aiming to sharpen their decision-making skills by learning to model and execute data and analyze inferences to advance their career
    • Recent graduates with a STEM background who wish to build practical experience in data science in anticipation of a career in data analytics

    Prerequisites: Recommended to be familiar with Excel data sets and data visualization and a basic knowledge of Python.

MCPO-800x500.jpg

How You Will Learn

  • Learning technique

    LEARN BY DOING

    Practice processes and methods through simulations, assessments, case studies, and tools.

  • Learning technique

    LEARN FROM OTHERS

    Connect with an international community of professionals while working on projects based on real-world examples.

  • Learning technique

    LEARN ON DEMAND

    Access all of the content online and watch videos on the go.

  • Learning technique

    REFLECT AND APPLY

    Bring your new skills to your organization, through examples from technical work environments and ample prompts for reflection.

  • Learning technique

    DEMONSTRATE YOUR SUCCESS

    Earn a Professional Certificate and CEUs from MIT xPRO.

  • Learning technique

    LEARN FROM THE BEST

    Gain insights from leading MIT faculty and industry experts.

MIT Faculty

Vivek Farias

Vivek Farias

Professor of Operations Management, MIT Sloan School of Management

Robert Freund

Robert Freund

Professor of Operations Research, MIT Sloan School of Management

Retsef Levi

Retsef Levi

Professor of Operations Management, MIT Sloan School of Management

Rama Ramakrishnan

Rama Ramakrishnan

Professor of the Practice, MIT Sloan School of Management

Curriculum

Part 1: Fundamentals of Data Science

Gain a foundational understanding of data science and its capabilities. Discover how data science can provide insights into your customer base and master essential analytical frameworks.

Part 2: Foundations of Optimization

Explore the significance of optimization in promoting the welfare of humanity. Delve into the intricacies of model design and acquire the skills necessary to construct, interpret, and evaluate models.

Part 3: Foundations of Machine Learning

Take an in-depth look at regression and classification, ensemble learning, and bias in model-based, data-driven decision-making.

Part 4: Advanced Machine Learning

Explore advanced applications of data science, including deep learning, neural networks, and natural language processing.

Part 5: Deployment

Discover real-world applications of AI and ML and new applications of digital transformation.

MIT xPRO is collaborating with online education provider Emeritus to deliver this online program. By clicking LEARN MORE or VIEW UPCOMING COHORT DATES, you will be taken to a page where you can download the brochure and apply to the program via Emeritus.

View upcoming cohort dates
For Teams