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Harvard Online
Harvard Online · delivered by SkillsPro360

Executive Program in
Data & AI for Business

Become a Data Specialist.
  • Curriculum: Three Harvard Online courses on data science and AI, business decision-making and data privacy. Nearly code- and mathematics-free throughout.
  • Live sessions: 36 hours of live group sessions on presenting analysis and defending decisions, scheduled between your Harvard modules. Plus twelve months of app access and Voca practice.
  • Credential: Certificate of Specialization from Harvard Online on completing the program.
Program fee
USD 4,690
3 installments available
Duration
10 months
4–5 hrs/week
Certificate of Specialization fromHarvard Online
Duration
10 months
Three Harvard modules
Live sessions
36 hours
With industry experts
Effort
4–5 hrs/week
Self-paced within deadlines
Format
Cohort-based online
Plus live coaching sessions
Credential
Harvard Online
Certificate of Specialization
Leaders in discussion during a working session

Data & AI for Business Program

For managers and leaders who receive data-driven recommendations, work alongside data scientists, and must decide what to act on.

1
Program outline
Featuring faculty from Harvard Faculty of Arts & Sciences, Harvard Business School, Harvard John A. Paulson School of Engineering and Applied Sciences and Harvard Kennedy School, alongside industry experts.
01
Data Science and AI Principles
Module one
What is data science, and how does it underpin AI, machine learning and large language models? A nearly code- and mathematics-free foundation, built around real-world examples that prompt you to think critically about your own workplace.
Nine topicsTaught by Dustin Tingley
→
02
Data Science for Business
Module two
Designed for managers: a hands-on approach to demystifying the data science ecosystem and becoming a more conscientious consumer of information, so you can judge the analysis that reaches your desk.
Six topicsTaught by Yael Grushka-Cockayne
→
03
Data Privacy and Technology
Module three
Technology is not value-neutral. Weigh the legal and ethical implications of personal data, the risks and rewards of collection and surveillance, and the need for policy, advocacy and privacy monitoring.
Five topicsTaught by Michael D. Smith and Jim Waldo
→
2
Included throughout
Live sessions with expert coaches
Instructor-led group practice alongside your coursework
Voca practice access
Mock interviews, presentation practice and CV review
What you receive

Earn a Certificate of Specialization from Harvard Online.

Complete the three modules and Harvard Online issues your Certificate of Specialization in Harvard on Digital.

✓

Designed and taught by Harvard faculty

Curriculum developed and delivered by faculty from Harvard Faculty of Arts & Sciences, Harvard Business School, Harvard SEAS and Harvard Kennedy School.

✓

Posted to your home address

SkillsPro360 posts the hard copy to you, alongside a Certified Electronic Credential for LinkedIn.

✓

Recognized internationally

A professional credential from Harvard Online, listed on your resume and LinkedIn profile.

Certificate of Specialization in Harvard on DigitalIssued by Harvard Online. A sample of this certificate will be shown here soon.
Issued by Harvard Online on completing the program.
The live component

Turning analysis into decisions.

Harvard teaches you to interrogate an analysis. The harder part comes next — getting a room of decision-makers to act on it. Between modules your cohort meets live to practice exactly that.

A live cohort session with participants joining globally

Presenting the analysis

Structuring a data-backed recommendation so it lands with executives and boards — what to lead with, what to leave out, and how to show uncertainty without losing the room.

Defending the recommendation

Holding your position when the numbers are challenged, and handling the colleague who prefers instinct to evidence.

Your own live problem

Each session works on a real decision you are facing at work, with peer consultation and expert critique rather than hypothetical cases.

Communicating under pressure

Harvard names the pitfall — communicating insights — and this is where you practice avoiding it, live and with feedback.

Sessions are scheduled between Harvard modules, never on top of them. A certificate for the live executive component is awarded on completion.

Between the modules

Your practice never stops.

Harvard cohorts run a few times a year, so there are natural gaps between modules. Two things keep you moving through them — so the momentum never drops.

Self-paced human skills app

  • Over 150 hours of curated content, in short daily formats
  • Covers leadership, communication, critical thinking, creativity and emotional intelligence
  • Skill assessments with scoring, so progress is measured rather than assumed
  • Points, streaks and leaderboards to keep the habit alive between modules
  • Digital certification on completion
  • Twelve months of access, on web and mobile

Voca — AI-powered rehearsal

  • Rehearse presentations before you deliver them for real
  • Practice the difficult conversation as many times as you need
  • Mock interviews for the role your new credential opens up
  • CV review against the roles you are targeting
  • Private, on demand, with no audience and no schedule
  • Three months of access, timed to when you need it most
Detailed syllabus

What you study, module by module.

Each module is taught through real organizational cases, with assignments that apply the thinking to your own workplace.

01

Data Science and AI Principles

Module one

A nearly code- and mathematics-free introduction to prediction, causality, visualization, data wrangling, privacy and ethics — with examples relevant to your own work environment.

Topics covered
  1. Data 101 — why data collection matters, what affects data quality, and judging whether data is high-quality. Case: flu detection
  2. Predictions and recommendations — the structure of a predictive algorithm and where human decisions shape it. Case: predicting sepsis
  3. Cause and effect — classifying relationships by correlation or causation, and the limits of randomization. Case: the Google Tax
  4. Data governance and privacy — formulating privacy guidelines and evaluating existing policies for ethics. Case: privacy and facial recognition
  5. Beyond the spreadsheet — sentiment analysis, supervised versus unsupervised learning, neural networks. Case: Burning Glass and text data
  6. Introduction to algorithms — evaluating algorithm performance and selecting the right one. Case: reducing food waste with Shelf Engine
  7. Data science ecosystems — the lifecycle of data, cloud infrastructure and where bottlenecks appear. Case: Harvard Link
  8. Data science and AI — mapping AI capabilities to business tasks, assessing data readiness, and treating adoption as a leadership challenge. Case: AXA Insurance
  9. The road ahead — auditing the data science process and recognizing how algorithms reinforce bias. Case: health care prioritization
Learning outcomes

Understand core data science and AI concepts

  • Explain foundational ideas such as prediction, causality, and data privacy in clear terms, and how they underpin AI, machine learning, and large language models
  • Recognize how data science and AI fundamentals apply across industries and roles

Evaluate and interpret data quality, algorithms, and AI systems

  • Identify high-quality versus low-quality data, common sources of bias, and their impact on AI and machine learning models
  • Assess the strengths and limitations of predictive systems, AI-powered recommendations, and other algorithmic tools

Apply data science and AI principles to real-world problems

  • Use frameworks to classify data relationships, spot opportunities, uncover causal insights, and determine when AI approaches are appropriate versus traditional analytics
  • Develop guidelines for ethical data and AI use and for making effective, responsible decisions in your work environment
Format: self-paced within cohort deadlinesAssessment: modules with quizzes
02

Data Science for Business

Module two

Beyond the spreadsheet: a hands-on approach that starts with the questions you need to ask when using data for decisions, so you know when to trust your data and how to interpret the results.

Topics covered
  1. The data science shift — applying the Data Driven Decision Framework and translating business problems into data hypotheses. Case: Carvana, good data and bad buys
  2. Data wrangling — assessing data quality, designing table joins and managing missing data. Case: Fannie Mae, identifying investments
  3. Visualization — critiquing charts, generating insight with graphs and designing for maximal impact. Case: StockX, drawing demand
  4. Time series forecasting — matching the time scale to the business problem and selecting smoothing techniques. Case: NICU beds, creating capacity
  5. Linear regressions — interactions, dummy variables and interpreting results. Cases: Bark Gift Shop, ATO Pictures
  6. Logistic regressions and machine learning — confusion matrices, CART, random forest, lasso and neural networks. Cases: Carvana, Fannie Mae
Learning outcomes

Build a data-driven decision framework

  • Use business analytics and data science tools to develop structured approaches that drive organizational success
  • Create and apply data-driven frameworks to develop hypotheses, identify trends, and guide strategy

Build competence in core business data science techniques

  • Apply methods such as data curation, regression models, predictive analytics, and data visualization
  • Assess and select appropriate methodologies in statistics and data analytics for business contexts

Strengthen data literacy and interpretation skills

  • Read and interpret datasets, metrics, visualizations, and basic code to inform decision making
  • Recognize and avoid common pitfalls when analyzing data and communicating insights
Format: self-paced within cohort deadlinesAssessment: six topics with quizzes
03

Data Privacy and Technology

Module three

Privacy as an ethical, business, technological and societal concern — helping you become a better-informed decision-maker about data-sharing practices in your organization.

Topics covered
  1. What is privacy? — constructing a definition rooted in your own experience and applying ethical frameworks. Case: Stop LAPD Spying Coalition
  2. Data collection, use and reuse — how laws differ and how usage shifts notions of privacy. Cases: the California Consumer Privacy Act, Henrietta Lacks and HeLa cells, GEDmatch
  3. The technology battleground — k-anonymity, differential privacy, and the difference between anonymized and de-identified data. Cases: data re-identification, edX research data, the US Census
  4. The price of privacy — algorithmic discrimination, privacy as a business model, and information silos. Cases: algorithmic bias in advertising, Proton, extremism online
  5. What's coming? — the privacy risks presented by deepfakes and emerging technologies. Cases: deepfakes, birth and death records
Learning outcomes

Engage confidently in data privacy decision-making

  • Participate in informed dialogue about data collection, security policies, and the ethical use of personal information
  • Evaluate the trade-offs between privacy, personalization, and business objectives

Analyze legal and regulatory frameworks

  • Explain the evolving definitions of privacy and the conflicts between laws, norms, and technological change
  • Identify key global regulations and understand their impact on data protection strategies

Assess emerging risks and future trends

  • Examine challenges of data anonymization, algorithmic bias, and the rising threat of deepfakes
  • Anticipate how evolving technologies will influence privacy, compliance, and consumer trust
Format: self-paced within cohort deadlinesAssessment: five topics with assignments

Syllabus topics are set by Harvard Online and may be revised between cohorts.

Who it is for

Built for leaders, not analysts.

If data-driven recommendations reach your desk and you are accountable for acting on them — but you are not the person writing the code — this program is designed for you.

No mathematics, programming or technical background required. Taught in English; participants should be 18 or over.

Who teaches you

Learn from Harvard faculty.

Your coursework is designed and delivered by Harvard faculty, with industry practitioners bringing real cases into each module.

Dustin Tingley

Dustin Tingley

Thomas D. Cabot Professor of Public Policy, Harvard Kennedy School and Harvard Government Department

A data scientist at Harvard and Deputy Vice Provost for Advances in Learning, Professor Tingley helps direct Harvard's education-focused data science and technology team and has helped organizations across sectors apply data science in practice.

Yael Grushka-Cockayne

Yael Grushka-Cockayne

Visiting Professor of Business Administration, Harvard Business School

Professor Grushka-Cockayne's research and teaching focus on data science, forecasting, project management and behavioral decision-making. In 2014 she was named one of twenty-one thought-leader professors in data science.

Jim Waldo

Jim Waldo

Gordon McKay Professor of the Practice of Computer Science, Harvard SEAS

Professor Waldo teaches distributed systems and privacy, serves as Chief Technology Officer for the School of Engineering and Applied Sciences, and is a Professor of Policy at the Harvard Kennedy School.

The learning experience

How you actually study.

Structured enough to keep you moving, flexible enough to fit around a full-time role in any time zone.

Cohort-based

You study alongside a global cohort, with discussion boards where peers from other industries and markets debate the same cases.

Weekly deadlines

Modules open on set dates with weekly deadlines, so the program carries momentum — but you choose which hours you study.

Applied assignments

Each module is assessed through assignments applying the frameworks to real cases and to your own organization.

Live coaching

Live instructor-led sessions with expert coaches turn the concepts into how you brief, decide and persuade at work.

Program fee

One fee. Everything included.

One fee covering the three Harvard Online modules, 36 hours of live executive sessions, twelve months of app access, three months of Voca and a dedicated advisor throughout.

USD4,690
per participant · complete program
  • All three Harvard Online modules
  • Certificate of Specialization from Harvard Online
  • Hard-copy certificate posted to your address
  • 36 hours of live sessions with industry experts
  • Three months of Voca — interviews, presentations, CV review
  • Twelve months of self-paced app access
Reserve your seat

Pay in three installments

Interest-free, one payment per module. No additional charges.
Installment 1 — on enrollmentUSD 1,570
Installment 2 — before Module 02USD 1,560
Installment 3 — before Module 03USD 1,560
Interest free. Paid by international card or bank transfer. Organizations enrolling teams are invoiced directly — multi-seat rates apply from ten participants. Fees are quoted in US dollars; your bank applies its own conversion rate.
Enrollment

From inquiry to first day.

Four steps, usually completed within a week.

Step one

Book a call

A twenty-minute conversation with a program advisor to check the program fits your role and goals. No obligation.

Step two

Choose your start

We confirm the upcoming cohort dates that suit your schedule and map your route through the modules.

Step three

Reserve your seat

Confirm your place, then complete payment by international card or bank transfer. An invoice is issued for employer-funded participants.

Step four

Begin

We enroll you directly with Harvard Online. Your access details arrive by email before your start date.

For organizations

Many participants are funded by their employer.

Organizations across banking, technology, manufacturing and government fund data and AI leadership programs as adoption accelerates. If your employer funds professional development, this program is straightforward to propose — we provide a scope document and invoice directly, and multi-seat rates apply from ten participants.

Common questions

Everything you might be wondering.

Do I need a technical background, or any coding or mathematics?

No. The foundation module is deliberately nearly code- and mathematics-free, and no module requires programming. Harvard describes these courses as particularly suited to people who are not data scientists but who work alongside them as managers and decision-makers.

How much time will it take?

Modules run four to five weeks each, at roughly four to five hours a week. Most participants complete the program in about ten months, since Harvard cohorts run a few times a year.

What does it cost, and how do I pay?

The program fee is USD 4,690 per participant, covering all three Harvard Online modules, the live sessions, twelve months of app access and three months of Voca. You may pay in full or in three interest-free installments. We accept international cards and bank transfers, and organizations are invoiced directly. Discounts apply only when you pay in full; installment payments are not eligible for discounts.

What is Voca, and how do I use it?

Voca is SkillsPro360's AI-powered practice tool. You can rehearse a presentation, run a mock interview, or have your CV reviewed — privately, on demand, as many times as you like. Three months of access are included, timed to the point in the program where it is most useful.

Who awards the certificate?

Harvard Online. On completing the program you receive your certificate directly from Harvard Online. SkillsPro360 is a delivery partner — we are not Harvard University.

What if I miss a deadline or need to pause?

Cohorts run to fixed deadlines, but the program is built around the natural gaps between Harvard cohorts. If work demands it, you can take a break between modules and join a later cohort — your advisor will map a revised route with you.

What support do I get from SkillsPro360?

You are assigned a program advisor throughout, and your enrollment includes live instructor-led sessions with expert coaches plus Voca, our AI-powered practice tool for interviews, presentations and CV review.

How do I receive my certificate?

Harvard Online issues your certificate, and SkillsPro360 posts the hard copy to your home address, usually six to eight weeks after you are notified of your eligibility. You also receive a Certified Electronic Credential to share on LinkedIn.

Decide with data. Prove it with Harvard Online.

Reserve your seat in the next cohort, or book a call to plan your route through the three modules.

Reserve your seat