MIT Media Lab

WSJ+ members receive a 15% course cost reduction for the Data Strategy: Leverage AI for Business course.

COURSE STARTS
Sept. 21, 2022
Registration closes Sept. 27

PRICE
$2,350 $1,998
Payment options available

Length:

6 weeks

Language:

English

Effort:

7-10 hours per week, self-paced online learning

Data Strategy: Leverage AI for Business

WSJ+ members receive an exclusive 15% course cost reduction for the Data Strategy: Leverage AI for Business course.

COURSE STARTS

Sept. 21, 2022

Registration closes Sept. 27

 

PRICE

$2,350 $1,998

Payment options available

Length: 6 weeks

Language: English

Effort: 7-10 hours per week, self-paced online learning

About the Offer


WSJ+ members are invited to register for the Data Strategy: Leverage AI for Business course presented by MIT School of Architecture and Planning in collaboration with Esme Learning. The upcoming presentation of the course starts 4 May 2022, and new presentations are available each quarter. As a part of this offer, learners will receive a 15% course cost reduction with code MITWSJ2022, alongside exclusive access to a white paper from Prof. Alex "Sandy" Pentland, Professor, Institute for Data Systems and Society, MIT Sloan School of Management. Upon completion of the course, participants will receive an additional $500 credit towards any future course with Esme Learning.

 

About theLaunching Data Strategy: Leverage AI for Business course

AI and data-driven decision making are reshaping the way companies do business. These powerful and disruptive tools allow organizations to develop new business strategies to accelerate workflow, scale faster and create new opportunities.

Data is the lifeblood of AI. It has to be protected and managed. Companies must learn to analyze data to tease out the hidden truths that lead to insight and change. AI is the engine that drives innovation. It allows companies to identify opportunity and optimize for success.

Through a review of current best practices, Data Strategy: Leverage AI for Business participants will learn how to secure data access and outline a successful AI strategy, as well as identify the resources and AI tools necessary to execute their plan.

In partnership with

What's Included?


Course: Data Strategy: Leverage AI for Business
Format: online, collaborative learning
Course starts: September 21, 2022
Duration: 6 weeks
Effort: 7-10 hours per week
Price: $2,350 $1,998
Certificate issued by: MIT Media Lab
Language: English

 

Offer details*

  • 15% course cost reduction to accelerate your career with code MITWSJ2022
  • Access to exclusive faculty white paper for cutting-edge industry insights
  • Collaboration with C-suite speakers, experts and colleagues to develop a global peer-to-peer network
  • An invitation to a live eventwith an MIT faculty member from the course
  • A distinguished professional profile differentiated by a certificate of completion issued by MIT School of Architecture + Planning
  • Upon completion of the course, participants will receive an additional $500 credit towards any future course with Esme Learning.

What You Will Gain


 

  • Actionable understanding of how to harness the power of data and AI to drive innovation.
  • Knowledge of the steps necessary to properly secure data and identify the optimum AI tools for success.
  • Future-facing skills that include the ability to outline and execute an AI strategy that creates new business opportunities.
  • Coveted industry knowledge from market-driven curriculum designed and delivered to the standard of an elite academic institution.
  • A powerful professional network from building connections with a global cohort of leaders, influencers and course participants.
  • Proof of knowledge through the prestigious certificate of completion issued by MIT School of Architecture + Planning.

Course Content


Module 0: Orientation

An overview of the course, the next-generation AI platform used to deliver it and the community of fellow innovators and leaders.

Module 1: Data Ownership

A look into how internal data is managed, tracked and integrated into the business processes. Learners will develop a heightened awareness of how data is a critical part of the business that needs to be protected.

At the end of the module, learners will be able to:

  • Recall key data concepts
  • Recognize the importance of data ownership
  • Differentiate between the data owner and steward
  • Identify the right data owners
  • Explain the main components of data governance

Module 2: Opportunities for AI and Data in Business

Explore the building blocks for developing a successful AI Strategy in an organization. This module looks at opportunities for Data and AI to deliver value for an organization, and lays the foundation for the modules that set core strategic frameworks and steps for developing good AI strategy.

 

  • At the end of the module, learners will be able to:
  • Identify foundational components needed for an AI Strategy
  • Evaluate and assess an organization’s AI and Data Strategy, identifying gaps and areas for improvement
  • Outline steps required to implement a successful AI Strategy

Module 3: Data-Driven Decision-Making

Examine the steps needed to develop a successful data strategy, and how data and analytics make predictions that can inform the strategic decision-making process. Highlighted are the types of predictions that can be drawn and discussions of types of decision-making they inform.

 

  • At the end of the module, learners will be able to:
  • Identify core components needed for a Data Strategy
  • Understand how data analytics are used to support decision-making
  • Apply prediction data to make better decisions

Module 4: Insights and Application

Focuses on the costs and deployment considerations to successfully adopt an AI and Data Strategy. We'll also look at Big Data Strategies and discover how companies must evolve their data strategies or risk being outdated.

 

  • At the end of the module, you will be able to:
  • Identify cost implications related to developing an AI and Data Strategy
  • Develop a framework to deploy and adopt an AI and Data Strategy in your organization
  • Identify outdated data practices and gain insights into new data practices

Module 5: Understanding the Risks

Understanding the importance of AI transparency and accountability to avoid missteps and build trust with customers and other stakeholders.

At the end of the module, learners will be able to:

  • Understand the ethics of AI and its impact on businesses
  • Explain best practices for the responsible use of AI
  • Identify and manage the risks associated with AI

Module 6: Data Privacy and Security

Businesses are subject to scrutiny from governments and governing bodies with regards to the collection, storage, use and sharing of customer data. This module provides a snapshot of the landscape of data and AI policies, regulations and governance activities in the US and abroad.

At the end of the module, learners will be able to:

  • Explain federated AI and its application across various industries
  • Identify privacy and security vulnerabilities in data collection
  • Describe data protection laws in their region, the EU and Asia

Your Faculty Director


Our international faculty is comprised of thought leaders from MIT School of Architecture + Planning, industry experts and successful entrepreneurs to facilitate rapid application of theory to practice.

Prof. Alex "Sandy" Pentland

Faculty Director

Professor, Institute for Data Systems and Society 

Alex “Sandy” Pentland is founding faculty director of the MIT Connection Science Research Initiative, which uses network science to access and change real-world human behavior, and is the Toshiba Professor of Media Arts and Sciences at the Massachusetts Institute of Technology (MIT). He also holds a triple appointment at MIT in Media Arts and Sciences, Engineering Systems Division and with the Sloan School of Business.

Sandy has helped create and direct MIT’s Media Lab, the Media Lab Asia, and the Center for Future Health. He chairs the World Economic Forum's Data Driven Development Council, is Academic Director of the Data-Pop Alliance, and is a member of the Advisory Boards for Google, Nissan, Telefonica, the United Nations Secretary General, Monument Capital, and the Minerva Schools.

In 2012 Forbes named Sandy one of the “seven most powerful data scientists in the world”, along with Google founders and the CTO of the United States, and in 2013 he won the McKinsey Award from Harvard Business Review. He is among the most-cited computational scientists in the world, and a pioneer in computational social science, organizational engineering, wearable computing (Google Glass), image understanding, and modern biometrics. His research has been featured in Nature, Science, and Harvard Business Review, as well as being the focus of TV features on BBC World, Discover and Science channels. His most recent book is Social Physics, published by Penguin Press.

Over the years Sandy has advised more than 50 PhD students. Almost half are now tenured faculty at leading institutions, with another one-quarter leading industry research groups and a final quarter are founders of their own companies. Sandy's research group and entrepreneurship program have spun off more than 30 companies to date, three of which are publicly listed and several that serve millions of poor in Africa and South Asia. Recent spin-offs have been featured in publications such as The Economist and The New York Times, as well as winning a variety of prizes from international development organizations.

Guest Experts


Rosalind Picard

Professor, MIT Media Laboratory; Director of Affective Computing Research; Chairman, Cofounder, and Chief Scientist of Empatica, Inc; Faculty Chair, MIT MindHandHeart

Bradley Horowitz

VP Product at Google

Wilson D'Souza

CTO, Akoya

Hossein Rahnama

Founder/CEO of Flybits, Associate Professor at Ryerson University, and Visiting Professor at MIT Media Lab

Marta Tellado

President and CEO at Consumer Reports

Yaniv Altshuler,

CEO and Co-Founder of Endor

Additional Guest Speakers

 

Jinhua Zhao - Associate Professor of Transportation and City Planning and Director, MIT Mobility Initiative / Beth Porter - COO, Cofounder and President, Esme Learning / Roberto Fernandez - Co-Director, Economic Sociology Ph.D Program, William F. Pounds Professor of Management, MIT Sloan School of Management / Alex Lipton / Wilson D'Souza - CTO, Akoya /Stuart Rubinstein - CEO, Akoya / Anmol Madan / Ken Gabriel / Roberto Rigobon / Tanzeem Choudhury / Yves de Montjoye / Andrew Lo / Nelson Repenning / Beth Noveck / Barak Berkowitz - Founder, MarketCentrix, and Connection Science Fellow at MIT / Yaniv Altshuler - CEO and Co-Founder of Endor / Ben Waber - President and Co-Founder at Humanyze

 

Download Brochure


In partnership with

Data Strategy is delivered as part of a collaboration with MIT School of Architecture + Planning and Esme Learning. All personal data collected on this page is primarily subject to the Esme Learning Privacy Policy.

 

© 2022 Esme Learning Solutions. All Right Reserved.