About this course

Unlock the power of AI in this accelerated 1-month experience. Brought to you by Founding Editor-in-Chief Harvard Professor Xiao-Li Meng; HDSR Board Members and Authors.

Gain the insights you need to leverage generative AI effectively, manage its risks responsibly, and drive innovation in your organization. This intensive demystifies generative AI, offering practical knowledge tailored to working professionals across sectors. Whether you're a business leader, educator, healthcare provider, or government official, you'll learn the fundamentals of generative AI, explore ethical considerations, identify innovative applications, and create actionable strategies and use cases to implement AI responsibly within your workplace.

Based on articles from Harvard Data Science Review, especially a guided reading of the Special Issue: "Future Shock: Grappling With the Generative AI Revolution"

That's why Board Members at the Harvard Data Science Review created this intensive program. In one month, you'll be on your way to gain wisdom and build confidence to turn AI uncertainty into AI leadership.

Get the outline Apply now

Your 1-month AI journey

5 weeks · 90min live sessions Tuesdays & Thursdays at 12 pm EST · ± 7 hrs/week

LIVE & ONLINE

Pre-course

Orientation & Foundations
Self‑paced, complete before 21 Oct

Mon - Thurs (13 Oct)

Personalized welcome from Prof Meng's AI Avatar

Discuss your background with AI Tutor

Personalized podcast to your goal

Initial strategy mapping from curated readings

Friday (17 Oct)

12 PM EST Lecture: Visions, Variations, Values

Week 1

History and Context

Mon (20 Oct)

Tues (21 Oct)

12 PM EST Lecture: History & context of Generative AI

Work with AI Tutor on your strategy: organizational intelligence, data, human skills, privacy and ethics

Wed (22 Oct)

Continue work with AI Tutor on your strategy

Submit strategy document for review

Thurs (23 Oct)

12 PM EST Lecture: Ethics of GenAI

1 PM EST Lecture: Strategic building blocks

Week 2

Strategic planning

Mon (27 Oct)

Recieve feedback on strategy document and implement changes

Work with AI Tutor on your strategy: strategy and vision, use cases, leadership, organization and culture

Tues (28 Oct)

12pm EST Lecture: Strategic vision and use cases

1 PM EST Group activity

Wed (29 Oct)

Continue work with AI Tutor on your strategy

Submit strategy document for review

Thurs (30 Oct)

12 PM EST Lecture: Use Case Deep Dive

1 PM EST Lab: Hands on building

Week 3

Data Minding; How machines learn

Mon (3 Nov)

Recieve feedback on strategy document and implement changes

Tues (4 Nov)

12pm EST Lecture: How Data Informs and Misinforms

Wed (5 Nov)

Work with AI Tutor on your strategy: data, tech architecture, analytics and AI portfolio

Submit strategy document for review

Thurs (6 Nov)

12 PM EST Lecture: How machines learn

1 PM EST Lecture: Use Case Deep Dive

Week 4

Implementation

Mon (10 Nov)

Recieve feedback on strategy document and implement changes

Work with AI Tutor on your strategy: operating model

Tues (11 Nov)

12pm EST Lecture: GenAI Implementation

1 PM EST Group activity

Wed (12 Nov)

Continue work with AI Tutor on your strategy

Submit strategy document for review

Thurs (13 Nov)

12 PM EST Lecture: Overall Strategy & Implementation Deep Dive

1 PM EST Lab: Practical prototyping

Week 5

Presentations / communication, wrap up, and celebrate

Mon (17 Nov)

Recieve feedback on strategy document and implement changes

Work with AI Tutor on your strategy: preparing for presentation

Tues (18 Nov)

12pm EST Group activity: Present / Share Strategy or Implementation Plan

Wed (19 Nov)

Work with AI Tutor on your strategy: refining ideas following peer feedback

Submit strategy document for review

Thurs (20 Nov)

12 PM EST Lecture: Final reflections & key insights

1 PM EST Celebrations & wrap up

Pre‑course (self‑paced, complete before 3 Oct)
‍Orientation & Foundations

AI‑tutor onboarding: short chat with Paski to set goals and explore the platform.
Personalized welcome video from Prof. Xiao‑Li Meng's AI Avatar
Curated readings + an optional "Foundations Path" to level‑set anyone new to Gen‑AI.
Use‑case inspiration gallery to spark ideas you'll refine during the week.
Outcome: prepared and inspired for the week ahead

Friday (3 Oct) – Welcome, Vision, Variation, and Values; Group Formation
‍Live with Prof. Xiao‑Li Meng

Lecture: Visions, Variations, and Values
Meet your 5‑person group, class, facilitators and TAs
Outcome: Fundamental data science concepts; meet your small group and class

Monday (6 Oct) – History of Intelligence & Ethics
‍Live with Prof. Stephanie Dick

Lecture: "What is intelligence: Making up minds"
1‑to‑1 tutorial with Paski to identify it's intellect; 1-1 tutorial on ethics in AI
Optional evening lab for deeper discussion on evaluating data bias.
Outcome: Clear historical perspective and an ethical framing of Gen‑AI

Tuesday (7 Oct) – AI Strategy
‍Live with Dirk Hofmann & Ulla Kruhse‑Lehtonen

Complete the AI‑Readiness Checker diagnostic.
Lecture and Strategic vision and opportunity matrix to spot high‑impact, low‑risk plays.
Optional evening lab for use case demos with no‑code prototypes.
Outcome: A first‑draft AI vision statement and mapped opportunity areas.

Wednesday (8 Oct) – Keynote 1: Data; Keynote 2: How Machines Learn
‍Live with Prof. Xiao-Li Meng, Prof. Ani Adhikari & Vinitra Swamy

Harvard's Deep Statistics Keynote: "How Data Inform and Misinform"
Berkeley College of Computing, Data Science, and Society Keynote: "How Machines Learn"
Continue development of strategic framework. Attend optional lab: Technical topics covered.
Outcome: Clarity and questions on data and how machines learn; progress with AI strategy formulation.

Thursday (9 Oct) – Use‑Case Definition
‍Live with Dirk Hofmann & Ulla Kruhse‑Lehtonen

Talk: From strategy to implementation
Playbook documentation sprint—capture governance steps, KPIs, owners.
Peer‑review lab and 1‑to‑1 Paski prototyping support.
Outcome: Documented use cases

Friday (10 Oct) – Panel Discussion and Celebrations
‍Live with Prof. Xiao‑Li Meng

Faculty panel discussion and reflections
Class-based individual contributions and celebrations
Celebrations of randomized 15 students in cohort
Outcome: AI Strategy & Use‑Case Playbook; Certificate of Attendance

Get the outline

Who is the course for?

Senior leaders and executives developing organizational AI strategies and implementation roadmaps

Department heads and project managers translating AI initiatives into actionable plans with measurable outcomes

Healthcare and education professionals integrating AI into patient care, teaching, and institutional operations

Consultants and government officials advising on AI transformation, governance, and regulatory compliance

Innovation and R&D directors building internal AI capabilities and sustainable innovation frameworks

Intensive format

FRIDAY

"Unsure about applying AI."

WEDNESDAY

"I am clear on my AI strategy and key use cases."

NEXT FRIDAY

"Now implementing with confidence."

The 1-month accelerator difference

Your actual challenges

(not generic cases)

Apply learning to your business context with personalized AI guidance and optional privacy accommodations.

LIVE faculty

(not pre-recorded)

Daily 90-minute sessions with Harvard Data Science Review Board Members and Authors.

Personal AI tutoring

(not chatbots)

AI Tutor trained on course content provides personalized guidance throughout your learning.

1 month of structured learning: Prep work + 90-minute live sessions on Tuesdays and Thursdays + strategy application work - all with Harvard Data Science Review Board Members and Authors, personalized AI tutoring support and teaching assistants working in industry.

How it works

A progressive 1-month journey from AI history and foundations to strategic clarity, with each day building your personalized AI strategy and use case definition through structured learning sequences.
‍

Progressive Learning Journey

Move from AI foundations to strategic implementation across one focused week.

Pre‑course (self‑paced): Welcome & Group Formation → Week 1: History & Ethics of Intelligence → Week 2: Strategy and Use Cases → Week 3: How Data Inform & Misinform; How Machines Learn → Week 4: Implementation → Week 5: Panel Discussion & Celebrations

Weekly Structure: ~7 hours (built for a work week)

Each week follows a structured learning flow designed for working professionals.
‍
Monday & Wednesday AI Tutorials (in own time) → Tuesday & Thursday Lunchtime Live Sessions (90 mins)
‍‍Live sessions include faculty presentations, peer collaboration, and guided work on developing and implementing your AI strategy.

Strategy, Use Case Definition and Implementation Plan

Throughout the week, build your personalized AI strategy, use case definitions and implementation plan.

‍AI tutor trained on course content provides personalized guidance as you apply each day's learning to your organizational context. Group work and labs allow for peer review and cohort feedback.

Get the outline

Meet your faculty

Prof. Xiao-Li Meng

Whipple V. N. Jones Professor of Statistics at Harvard University & Editor-in-Chief, Harvard Data Science Review

Statistician and former Harvard Dean of Graduate School of Arts and Sciences. He is well known for his depth and breadth in research, his innovation and passion in pedagogy, and his engaging and entertaining style as a speaker and writer.

Prof. Ani Adhikari

Teaching Professor of Statistics at UC Berkeley

Ani Adhikari is a Senior Lecturer in Statistics at UC Berkeley and a recipient of Berkeley’s Distinguished Teaching Award and Stanford’s Dean’s Award for Distinguished Teaching. With a Ph.D. from Berkeley and an undergraduate degree from the Indian Statistical Institute, Ani focuses on teaching and mentoring students.

Dr. Stephanie Dick

Assistant Professor, Simon Fraser University & Harvard Data Science Review Board Member

Stephanie Dick is a historian of artificial intelligence, computing, and mathematics. She is an expert on AI's societal impacts and the historical development of automated reasoning, and co-editor of "Mining the Past" column at Harvard Data Science Review.

Dirk Hofmann

Co-Founder, CEO DAIN Studios Germany & Harvard Data Science Review Board Member

Dirk Hofmann is a co-founder of a Finnish-German Data and AI consultancy. He has executed Data and AI strategies for many different companies and industries. Before DAIN, Dirk headed up global Data/AI and innovation initiatives at Siemens, Nokia and Deutsche Telekom.

Ulla Kruhse-Lehtonen

Co-founder, CEO DAIN Studios Finland & Harvard Data Science Review Board Member

Ulla Kruhse-Lehtonen is a co-founder of DAIN Studios, a Finnish-German Data and AI consultancy. She executes data and AI strategies for many different companies. Before DAIN, Ulla headed up large data and AI departments in global companies such as Sanoma Media and Nokia.

Vinitra Swamy

CEO & Co-founder, Scholé AI

Vinitra Swamy is a human-centered AI researcher and CEO of Scholé AI, an edtech spinoff focused on AI for education. She holds a PhD in Computer Science from EPFL, where she was recognized as a Rising Star in Data Science and received multiple awards for her contributions to machine learning and education research.

Meet your industry TAs

Take optional evening labs and learn from Berkeley Data Science graduates and Scholé deep dives

Julie Vu

Preceptor in Statistics

Kevin Miao

Machine Learning Research Scientist

Anna Nguyen

PhD Candidate

Angela Guan

Product Manager

Ryan Roggenkemper

Software Engineer

Will Furtado

Quantitative Researcher

Jacob Warnagieris

Software Engineer

Tam Vilaythong

Software Engineer

What participants say about this format

A world-class course
"The combination of AI tutoring, group work, and expert insights made the learning process dynamic and engaging. The best part? Real-world applications and practical solutions that I can implement immediately. You guys are absolutely world-class!"

Gavin J.

A fresh learning experience
"I loved the balance between AI-led discussions and group collaboration. The conversational format allowed for immediate understanding of complex issues, and the AI tutor’s ability to clarify and expand on topics was impressive. This was a perfect blend of modern learning techniques!"

Vikki A.

Exceeded my expectations
"I’ve attended many training sessions, but this course stood out. The flexibility, the deep discussions on real-world challenges, and the AI tutor’s ability to guide and support learning made it a truly unique experience. I walked away with a refreshed understanding of key key issues!"

Joey N.

The future of training is here
"I never imagined AI could be such a helpful tutor! The combination of expert lectures, interactive discussions, and AI-driven feedback made learning efficient and enjoyable. This course set a new standard for online training!"

Victoria N.

Challenging, engaging, & useful
"The case studies and breakout discussions forced me to think critically and learn from others. It was outside my comfort zone at times, but the structured format made it an incredibly valuable experience."

Alna K.

A must-do for professionals!
"Understanding financial management and legal aspects is crucial in this industry. This course provided clear insights and practical applications. The expert-led lectures and AI tutor made it one of the most informative sessions I’ve attended."

Carl V.

The best course I’ve attended
"This course was insightful and well-paced. The group discussions provided a great way to learn from others’ experiences, and the AI tutor kept things structured and engaging. I highly recommend it!"
‍

Somaria R.

Perfect balance of AI & experts
"The combination of AI and live discussions made learning effective and exciting. The real-world case studies and group work gave me valuable insights I don’t usually engage with. I walked away with practical knowledge I can apply immediately."

Poena M.

Your 1-Week AI Strategy Journey

Friday → Friday • 12 pm EST daily

LIVE

FRI - SUN

Gen AI Foundations

Build conceptual understanding and start individual application

Prof. Xiao-Li Meng

Pre-course onboarding & foundational readings
Faculty presentation & group discussion (90 min)
Begin AI strategy framework with tutor guidance

MON

Gen AI Foundations

Build conceptual understanding and start individual application

Prof. Xiao-Li Meng

Pre-course onboarding & foundational readings
Faculty presentation & group discussion (90 min)
Begin AI strategy framework with tutor guidance

TUE

Technical Deep Dive

Strengthen understanding of key systems and methods

TBC

Technical primer preparation (30 min)
Technical deep-dive & hands-on tutorials (90 min)
Apply technical concepts with AI guidance

WED

Strategic Planning

Develop evidence-based vision and strategy framework

TBC

AI-guided strategy preparation (30 min)
Strategic framework session & peer consultation (90 min)
Refine strategy with AI feedback

THU

Implementation & Use Cases

Translate concepts into practical implementation plans

TBC

Implementation case study preparation (30 min)
Implementation methodology & risk analysis (90 min)
Finalize implementation approach with AI support

FRI

Presentations & Integration

Present your strategy and integrate feedback for next steps

TBC

Presentation preparation with AI support (30 min)
Presentation training & peer feedback setup (30 min)
Present AI strategy to faculty & peers (60 min)
Faculty synthesis & next steps planning

Enrol Now

FAQs

What's the weekly time commitment?

Plan for approximately 7 hours per week, designed for working professionals:
‍
- Preparation work (flexible timing)
- 2 x 90 minutes: LIVE faculty sessions (12:00-1:30pm EST on Tuesdays and Thursdays)
- AI-guided application work (flexible timing)

Additional optional work available for those who want to go deeper. The live sessions are fixed, but preparation and application work can be completed at your convenience.

What will I develop during the program?

You'll develop your personalized AI strategy framework, use case formulation and implementation plan throughout the month, working with both faculty guidance, small group feedback and AI tutoring support.

The program is designed to give you a solid foundation and framework you can continue developing and implementing in your organization.

Can I participate if my company has data sharing restrictions?

Yes. This course is designed for you to apply the learning to your own business context. You’ll be invited to work on real issues and opportunities from your professional environment — but you can choose how much or how little you wish to share.

We fully respect organizational data policies and confidentiality. If needed, you can use hypothetical or anonymized examples.

Is this LIVE with HDSR Board Members & Authors?

Yes, the 90-minute faculty sessions are LIVE with Harvard Data Science Review Board Members and Authors, led by Editor-in-Chief Prof. Xiao-Li Meng, Prof. Ani Adhikari (UC Berkeley), Prof. Stephanie Dick (SFU), Dirk Hofmann (AI Consulting CEO), Ulla Kruhse-Lehtonen (AI Consulting CEO) and Vinitra Swamy (AI Startup CEO).

All sessions are recorded for later review.

Who will be in my cohort?

Leaders across sectors: business executives, healthcare administrators, education leaders, government officials, and innovation directors.

This creates valuable peer learning opportunities and networking with professionals facing similar AI strategy and execution challenges.

How does the AI tutoring work?

The AI tutor is trained on course content and provides personalized guidance as you develop your strategy framework and use cases. It adapts to your business context and helps you apply each day's learning to your organizational challenges.

The AI tutoring supports your work during preparation and application phases, allowing you to progress at your own pace while building your strategy.

What level of technical knowledge do I need?

No coding required. This program is designed for business leaders and strategic decision-makers focusing on strategy, applications, and implementation—not technical development.

What happens if I miss a session?

All LIVE sessions are recorded. We strongly encourage LIVE attendance for maximum value, especially for peer collaboration and real-time faculty interaction.

What if I'm in a different time zone?

LIVE sessions run 12:00-1:30pm EST. That's:

9:00am PST (West Coast)
5:00pm GMT (London)
10:30pm IST (India)
1:00am CST next day (Singapore/Hong Kong)

All sessions are recorded for international participants.

Will I receive a certificate?

Yes, students receive a certificate of attendance from the Harvard Data Science Review if they attend and participate in a minimum of 5 of the 6 live sessions and complete all self-study activities that are marked as required. One additional absence from live sessions is possible upon request with justifiable reasons (e.g., medical absence).

Still have questions?

Reach out - we're here to help you succeed.

Email:

‍info@hdsrcourses.org

Book a call

AI Wisdom & Warnings · Harvard Data Science Review

Gen AI Strategy and Implementation

Wisdom and Warnings from Harvard Data Science Review

Get more info

About this course

Unlock the power of AI in this accelerated 1-month experience. Brought to you by Founding Editor-in-Chief Harvard Professor Xiao-Li Meng; HDSR Board Members and Authors.

Your 1-month AI journey

Pre‑course (self‑paced, complete before 3 Oct)
‍Orientation & Foundations

Friday (3 Oct) – Welcome, Vision, Variation, and Values; Group Formation
‍Live with Prof. Xiao‑Li Meng

Monday (6 Oct) – History of Intelligence & Ethics
‍Live with Prof. Stephanie Dick

Tuesday (7 Oct) – AI Strategy
‍Live with Dirk Hofmann & Ulla Kruhse‑Lehtonen

Wednesday (8 Oct) – Keynote 1: Data; Keynote 2: How Machines Learn
‍Live with Prof. Xiao-Li Meng, Prof. Ani Adhikari & Vinitra Swamy

Thursday (9 Oct) – Use‑Case Definition
‍Live with Dirk Hofmann & Ulla Kruhse‑Lehtonen

Friday (10 Oct) – Panel Discussion and Celebrations
‍Live with Prof. Xiao‑Li Meng

Who is the course for?

Intensive format

The 1-month accelerator difference

How it works

Meet your faculty

Meet your industry TAs