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ONLINE COURSE

Data Leadership: AI, Cloud & Governance

Lead with Data. Deliver Impact.

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Overview

This 8-week online program from MIT Professional Education equips professionals with practical tools to turn data into strategic action across industries. Designed for business leaders, managers, and technical professionals, it blends data strategy, modern technologies, and leadership skills for impactful results. 

Why Enroll in This Course?

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Drive digital transformation in your organization by connecting business strategy with data capabilities. 

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Architect data-driven solutions to improve operational efficiency and competitive edge. 

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Build a culture of data-driven decision-making across teams and business functions. 

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Explore cloud data platforms, AI integrations, and modern data architectures for business success. 

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Join two live sessions with MIT instructors, plus up to eight interactive sessions with industry experts, learning facilitators, and global peers. 

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Gain access to curated supplementary resources that deepen your understanding and extend your learning beyond the core modules. 

What Will You Learn?

  • Data governance and its application in organizations to maximize the value of data assets.

  • To build an organizational culture that incorporates the use of technology

  • To extract information and insights from various sources of raw data

  • Successful data-based decision-making skills to drive strategic growth and operational efficiency

  • To apply DevOps to optimize data systems for organizational advancement

  • To use current tools to leverage the data overseen by the organization

  • To understand how cloud, machine learning, and data storage technologies enhance the speed and scalability of contemporary data systems.

Course Outline

The overarching goal of data leadership is to make relevant data accessible to decision-makers at every level of the organization. Data leadership serves to recognize and anticipate market changes, and therefore respond quickly to trends and changes in customer preferences.

  • Big Data and AI for Leaders

  • Parsing Our Physical World

  • ChatGPT and No-Code Models

  • AI Applications

  • Reinforcement Learning 101

  • Data Pipeline Automation

  • Frameworks for System Design and Operation

  • Data-First Companies

  • Decision-Making Frameworks

  • Agile Software Development Methodology

  • Organizing Around Modern Pipelines

  • Axiomatic Design

  • Design of Organizations

  • Internet and The World Wide Web

  • Client-Server Architecture

  • Structured Query Language (SQL) and Database Architecture

  • Architect Simplicity

  • Legacy Microsoft 365 With No-Code Power Platform

  • The API Problem and Apollo Graph

  • Data

  • Transforming the Organization

  • The First Data Company

  • Data Explosion

  • Artisan vs. Factory

  • What is a Data Platform?

  • Database Design

  • SQL for Leaders

  • Database Design Deep Dive

  • AI Factories

  • Data Platforms: Data Ingestion

  • Data Platforms: Data Reporting

  • The Modern Data Stack

  • Data Stacks Case Study: JetBlue

  • Modern Data Stack Patterns

  • Explore the history of the cloud

  • Cloud Journey: Understand the differences between the cloud and data centers

  • The Cloud and Data Leadership: Recognize the limitations to cloud interoperability

  • Ethics – AI Bias and Fairness, Part I

  • Ethics – AI Bias and Fairness, Part II

  • Data Governance and Compliance

  • Data Leadership

  • The Transformation of Data Technology

Gain Experience with Essential Data Leadership Tools

  • ChatGPT – Generate insights and automate text with conversational AI

  • Google Cloud – Scale data processing and storage in the cloud

  • Power Apps – Build custom business applications with low-code

  • Power BI – Create interactive dashboards and visual analytics

  • Tableau – Visualize and explore complex datasets intuitively

  • Snowflake – Manage and query data efficiently on the cloud

  • BigQuery – Perform fast SQL-based analytics on large datasets

  • Databricks – Accelerate machine learning and data engineering workflows

  • Apache Kafka – Stream and process real-time event data

  • GitHub Actions – Automate CI/CD workflows and data pipelines

Note: Tools listed are indicative and may be updated as per curriculum enhancements.

Who Is This Online Course For?

  • Management level professionals and executives looking to champion a data-driven approach in their organizations to be able to make informed decisions.

  • More established organizations as well as younger start-ups seeking to improve data management and processing.

  • Professionals and executives in data management roles Chief of Data Analytics, Chief of Data, Chief of Machine Learning.

  • Organizations with a medium to high number of databases and medium-high data volumes that need to integrate and connect their sources with their databases to better leverage their use.

  • Other roles with significant responsibility wanting to improve their data analytics and optimize their utilization.

  • Organizations that operate with legacy systems, such as SAP, need to update their data structure.

Instructors

MPE - Faculty - Abel Sanchez
Dr. Abel Sanchez

Executive Director, MIT Geospatial Data Center; Research Scientist, Center for Complex Engineering Systems, Sociotechnical Systems Research Center, under the Schwarzman College of Computing 

MPE - Faculty - John R. Williams
Prof. John R. Williams

Professor of Information Engineering, Civil and Environmental Engineering; Director, MIT Geospatial Data Center; faculty member, Center for Computational Science and Engineering, Schwarzman College of Computing 

Past Participants Profile

Work Experience

Work Experience

Top Industries

Top Industries

Top Countries

Top Countries

Participant Testimonials

MIT Professional Education's Data Leadership course has changed my perspective and I think it impacted my way of thinking. First of all to understand why data plays a vital role in order to build a da...
Syed Aamir Jafri
CEO,
E-Ocean
I definitely feel more confident in my work. As a sole innovator on the team in the operations space, I previously felt siloed. Since taking this course, I've networked with other professionals and co...
Denval Lawrence,
Director, Enterprise Talent Management Operations,
Travelers
I really liked the structure offered! It was a comprehensive program covering all the aspects of data, AI, its transformations and how it is shaping the world. The assignments and extra material are t...
Betty Chiu Chu
Head of Data & Linguistics,
Hand Talk
Certificate

Certificate

All the participants who successfully complete their program will receive an MIT Professional Education Certificate of Completion, as well as Continuing Education Units (CEUs)*.

To obtain CEUs, complete the accreditation confirmation, which is available at the end of the course. CEUs are calculated for each course based on the number of learning hours.

*The Continuing Education Unit (CEU) is defined as 10 contact hours of ongoing learning to indicate the amount of time they have devoted to a non-credit/non-degree professional development program.

To understand whether or not these CEUs may be applied toward professional certification, licensing requirements, or other required training or continuing education hours, please consult your training department or licensing authority directly.

MIT Professional Education in Numbers

+60K

Participants in our courses

+155

Countries represented by our participants

92%

Rate the experience as extraordinary

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