Data Science and AI Principles

• Course Code: EXE-DSAP2026.01
• Course Duration: Five weeks from August 26 – September 30, 2026
• Language: The course will be delivered in English by Harvard lecturer and in Vietnamese by Fulbright lecturer
• Venue: Online through the Harvard Online platform, and live instructor-led sessions with Fulbright faculty (attend either on campus or online)
• Registration Deadline: 20 August 2026
• Course Schedule and Brochure: HERE 
• Course registration: HERE
• Course Tuition: 30,000,000 VNĐ

Discount:

• 35% for early bird registration by 15 July 2026
• 10% for standard registration by 05 August 2026
• 35% for group registration from 3 people
• 30% for alumni of Fulbright MPP program, executive or short courses.

COURSE DESCRIPTION

Data science is at the core of any growing modern business, from health care to government to advertising and more. It also underpins today's most powerful AI technologies, including machine learning models and large language models (LLMs). Insights gathered from data collection and analysis practices have the potential to increase the quality, effectiveness, and efficiency of work output in both professional and personal situations.

Data Science and AI Principles makes the foundational topics in data science and AI approachable and relevant by using real-world examples that prompt you to think critically about applying these understandings to your workplace. You'll explore how data science provides the building blocks for AI, machine learning, and LLMs, and learn how organizations can use these tools to transform products, services, and decision-making.

LEARNING OUTCOMES

By the end of this course, participants will be able to:

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

Participants who complete all 9 modules & instructor-led sessions, including satisfactory completion of the associated quizzes, by stated deadlines, can earn the Dual Certificates from Program, in which a Certificate of Participation from Fulbright School of Public Policy and Management, and a Certificate of Completion from Harvard Online.

PROSPECTIVE LEARNERS

The course is designed for early and mid-career professionals who want to understand how data is transforming industries and develop a data-driven mindset to advance their career opportunities, as well as for students and recent graduates looking to build a strong foundation in essential data-related concepts, vocabulary, skills, and business intuition to prepare for their careers.

LECTURER

• Dr. Huynh Nhat Nam, MPP Director, Faculty member at Fulbright School of Public Policy and Management.
• Prof. Dustin Tingley – Harvard University