Drive Measurable Business Value Through Strategic AI and ML Leadership
AI and ML: Leading Business Growth
Application closes on
16th Oct 2026
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AI and ML: Leading Business Growth
Application closes 16th Oct 2026
Why should you participate in this program?
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Technical fluency without coding
Learn complex AI concepts, Generative AI, and Agentic AI without writing code, allowing you to focus on strategic execution, business value, and enterprise growth.
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Built on MIT’s legacy of innovation
MIT is ranked #1 in the world, #1 in AI and Data Science, and #2 among U.S. national universities, reflecting its global leadership in research, innovation, and technology education. (2026 Rankings)
LEARNING OUTCOMES
What will you learn to build and apply?
Through a structured learning journey, you will build the capability to:
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Navigate the full lifecycle of an enterprise AI initiative with realistic milestones and accountability
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Develop the intuition to recognize a business problem's need before committing enterprise resources
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Learn frameworks to employ a data-driven decision-making approach, enabling robust enterprise AI capabilities
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Understand passive automation v/s autonomous AI agents that can plan and execute enterprise-wide processes
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Build the operational toolkit needed to take projects from lab experiments to enterprise-scale production
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Express the business value of AI initiatives to stakeholders and link your technical plan to enterprise goals
Receive a Certificate of Completion from MIT Professional Education
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#1 in World Universities
QS World University Rankings, 2026
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#1 in AI and Data Science
QS World University Rankings by Subject, 2026
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#2 in National Universities
U.S. News & World Report Rankings, 2026
What program benefits will you receive?
Join the MIT Professional Education alumni network, including the exclusive MIT Professional Education LinkedIn group
Benefit from access to MIT Professional Education–sponsored events, webinars, and networking opportunities
Enjoy one year of digital access to MIT Horizon
Stay current on faculty research, new programs, and MIT initiatives via MIT Professional Education communications
Benefit from a 15% discount on enrollment in future MIT Professional Education short-duration open-enrollment programs (five days or less)
*All benefits are subject to change
KEY PROGRAM HIGHLIGHTS
Why choose this program?
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Live learning with MIT faculty and industry practitioners
Engage with MIT faculty and industry experts through live online sessions, gaining real-world insights alongside academic rigor.
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Practical AI problem review
Work through real-world AI problem scenarios in a structured review format, applying frameworks to practical business situations.
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Team Impact Project
Tackle a real-world business problem using AI and ML knowledge, frameworks, and tools gained in the program.
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Hands-on vibe coding exercise
Build and deploy a live application through a guided, no-code exercise, translating AI concepts into a working outcome.
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Build a long-term professional network
Become a member of the MIT Professional Education alumni network and join the exclusive MIT Professional Education LinkedIn group.
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Globally recognized credential
Earn a certificate of completion from MIT Professional Education upon successful completion of the program.
Skills you will learn
Identify AI opportunities
Evaluate AI solutions
Build business cases
Assess AI ROI
Apply responsible AI
Develop implementation roadmaps
Lead AI transformation
Identify AI opportunities
Evaluate AI solutions
Build business cases
Assess AI ROI
Apply responsible AI
Develop implementation roadmaps
Lead AI transformation
- Overview
- Learning Path
- Curriculum
- Projects
- Certificate
- Faculty
- Fees
Who is this program for?
Designed for mid-to-senior leaders, managers, consultants, and strategic business professionals
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Leadership, enterprise C-suite, and founders
Including CXOs, business heads and entrepreneurs who wish to convert AI capability into measurable business value and build a board-ready roadmap.
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Business strategy and operations directors and VPs
Including managers seeking to ingrain a data-driven decision-making approach and automate enterprise workflows using practical AI and ML frameworks.
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Technology, data, and AI leaders
Looking to build robust, scalable AI capabilities and translate technical feasibility into strategic business growth.
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Product and program management leaders
Seeking to enhance product roadmaps and user experiences with AI-driven automation, LLMs, and Agentic AI.
What makes the program distinctive?
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Technical Fluency Without Coding
Go beyond AI awareness to understand the concepts behind AI and ML, with no programming background required
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Strategic Value Across the Entire AI/ML Lifecycle
Learn how AI initiatives move from a high-value opportunity aligned with business strategy through to deployment, monitoring, and improvement at scale
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Enterprise-Ready AI Capabilities
Explore emerging enterprise-relevant AI capabilities, including ML, Deep Learning, Gen AI, LLMs, Agentic AI, and intelligent decision systems
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Responsible AI Governance
Explore explainability, transparency, responsible implementation, and AI governance considerations involved in developing and deploying AI solutions
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Regularly Updated Curriculum
Benefit from a regularly updated curriculum to reflect the latest innovation in AI and ML, because the program is delivered live by MIT faculty
What will you learn in the program?
The program curriculum is uniquely designed to transform ambitious professionals into strategic AI and ML leaders capable of driving enterprise AI adoption at scale. It follows a structured arc across five modules, from strategic foundations through hands-on data and modeling work to decision systems, deployment, and applied practice
Module 1: Program Foundations
Course Overview: Strategic AI Alignment Across an Organization
Managing the Lifecycle of an AI/ML Initiative: From Ideation to Deployment
Articulating Business Value for an AI/ML Initiative
AI Fundamentals: Key Building Blocks
Guest Speaker Session
Module 2: Finding Patterns Within Data
Cohorts
Images
Text
Tabular Data
Time Series
Guest Speaker Session
Module 3: Modeling and Predictions
Predicting Values: Trends and Baseline Impact
Predicting Categories: Segmentation and Tradeoffs
Predicting in the Real World: Bridging the Reliability Gap
Predicting Scenarios: Simulating Outcomes for Strategic Planning
Predicting at Scale: Deep Neural Networks and LLMs
Guest Speaker Session
Module 4: Decisions and Deployment
Agentic AI: From Co-Pilots to Auto-Pilots
Autonomous Sequential Decision-Making
From Lab to Production: Deploying, Testing, and Monitoring AI/ML Solutions
Guest Speaker Session
Module 5: Applied Practice
Practical AI Problem Review
Hands-On "Vibe Coding" an App
Note: The curriculum listed above is indicative and subject to updates as technology evolves.
Team Impact Project
A practical strategy project that enables you to translate concepts and frameworks into solutions
Project Details
Strategic AI Roadmap: End-to-End Business Deployment
Description
Collaborate in global, cross-functional teams to tackle high-impact business opportunities by designing a complete, production-ready AI and ML initiative. Each group may select a topic of interest, preferably inspired by a real-world challenge. Guided by MIT faculty insights and proven enterprise frameworks, your team will execute a complete lifecycle methodology—moving seamlessly from problem definition to model deployment, monitoring, and governance.
Skills you will learn
- AI/ML Problem Framing & Business Case Formulation
- End-to-End AI Lifecycle Management
- Data Strategy & Sourcing
- Responsible AI & Governance
- Lab-to-Production Deployment
- Strategic AI Roadmapping & Communication
- Agentic & Decision Systems Design
- Cross-Functional Team Leadership
Note: The projects listed above are indicative and subject to updates to the curriculum.
Who are the faculty for the program?
Learn from MIT faculty.
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Devavrat Shah
Professor of EECS at MIT IDSS
Director, Statistics and Data Science Center, MIT
Winner, 2010 Erlang Prize from INFORMS
Know More -
Jehangir Amjad
VP of Engineering, AI, Ikigai Labs
Computer Science Lecturer at Stanford
Winner, Jerome H. Saltzer Teaching Award, MIT
Know More
LinkedIn Profile
University LinkEarn Elite Credentials From MIT Professional Education
Upon successful completion of the program, receive a certificate of completion from MIT Professional Education
* Image for illustration only. Certificate subject to change.
What are the fees for the program?
The program fee is USD 9,000
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The application fee for the AI and ML: Leading Business Growth program is USD 100
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The application fee is refunded only in the case an applicant is not offered admission to the program
Admission process
The program follows a simple 3-step application process. The step-by-step process is outlined below.
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Online Application
Complete the online application form.
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Resume
Keep a resume in Word or PDF format ready to be submitted via the upload tab in the online application form.
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References
Provide one professional reference who can discuss your candidacy in detail.
Program Eligibility
- A minimum of 5 years of work experience with demonstrated career progression across business, technical, or leadership roles.
- Experience leading teams or managing projects/products is preferred but not required.
- An undergraduate degree with a strong academic track record is preferred.
- Fluency in written and spoken English is required.
Delivered in Collaboration with:
MIT Professional Education is collaborating with online education provider Great Learning to offer AI and ML: Leading Business Growth program. This program leverages MIT's leadership in innovation, science, engineering, and technical disciplines developed over years of research, teaching, and practice. Great Learning collaborates with institutions to manage enrollments (including all payment services and invoicing), technology, and participant support. Accessibility
Application Closes
16th Oct 2026
