Meet the Instructor
Aditi Joshi | AI Program Lead at Google Cloud, Core ML
Aditi thrives in navigating the fast-paced world of product management, and enjoys tackling complex AI challenges at Google. Her experience spans teaching product management for six years in NYC to thousands of students, fellowships in privacy and security fields at Harvard and Yale, and mentoring rising startups at TechStars and Google for Startups Cloud. Aditi holds degrees from Yale and Stanford.
For more information, visit Aditi’s LinkedIn profile.
Description
Understanding the AI product management field has become more crucial now than ever, particularly in light of recent advancements in artificial intelligence and Machine Learning technologies including the recent proliferation of generative AI large language models. Considering the speed with which AI is becoming pervasive in our lives, having a strong grasp of AI concepts and frameworks is critical. This becomes more pertinent especially for aspiring AI product managers without significant technical (e.g., coding) background.
This learning sprint explores opportunities recent advancements in artificial intelligence bring to the field of AI product management, with an emphasis on applying an ethical lens to developing and deploying AI products. By catering to non-technical professionals, this sprint aims to make the AI product management field more accessible, which is a precursor for innovating and building groundbreaking products that address complex, real-world challenges through leveraging cutting-edge technology. This course is ideal for tech-savvy professionals who want to acquire domain knowledge and foundational skills in order to thrive in the exciting field of AI product management.
Learning objectives
Ready to unlock the power of AI in your organization?
Through a series of hands-on activities and guided discussions, participants will learn how to leverage AI concepts and tools in order to tackle real-world technological problems. At the end of this learning sprint, participants will walk away with:
- Foundational knowledge of key concepts in AI product management.
- Practical experience for building a simple AI project, and useful skills for integrating AI into existing projects.
- A firm understanding of key ethical considerations in the process of developing and deploying AI products.
- Lasting connections while learning with and from a network of like-minded individuals passionate about the field of AI product management.
This course does not require any level of technical (e.g., coding) background. A basic, theoretical understanding of artificial intelligence and machine learning technologies is helpful. Alternatively, participants are encouraged to watch this fundamentals of AI product management webinar prior to joining the sprint.
Framework
This learning sprint is organized around three main components.
Case study
This sprint uses a short case study around which live workshops and asynchronous activities are structured. Ahead of a live workshop, the instructor will assign a topic based on the case study and may record a short video discussing pre-workshop tasks. Participants are encouraged to complete assigned tasks prior to convening for a live workshop.
Live workshop
These are synchronous, discussion-based sessions in which participants, guided by the instructor, synthesize the content of the topics covered in each module toward building expansive knowledge and practical skills. Live workshops will constitute hands-on and immersive activities conducted in large and small groups. All live workshops are one hour-long and will be delivered on June 5, 12, 18, and 26 between 7:00 PM – 8:00 PM ET. There will be two additional sessions exclusively for Front Row participants on July 2 & 3, 7:00 PM – 8:00 PM.
Problem of Practice
As participants go through this learning experience, they are encouraged to identify a problem related to AI product management within their organization and/or their respective roles. Using the knowledge and skills gained from this sprint, participants will have the opportunity to develop a simple strategy aimed at mitigating the problem they have identified over the course of the four live workshops. Front row participants will be able to present their strategies and receive additional feedback from the instructor at two complementary sessions.
Schedule
| Modules | Date and time | Description |
| Primer: Concepts opportunities, and challenges | Wednesday, June 5: 7:00 PM – 8:00 PM ET | Overview of foundational concepts, emerging opportunities, and ethical challenges in developing and deploying AI products inside large and small organizations. |
| Tools of the trade that leverage human-centered design | Wednesday, June 12: 7:00 PM – 8:00 PM ET | What popular and cutting-edge tech tools are being used to create and deploy AI products? How can aspiring or current AI product managers use these tools to create innovative and impactful solutions for solving complex, real-world challenges? |
| Data-driven decision making (measurement & metrics) | Tuesday, June 18: 7:00 PM – 8:00 PM ET | How can AI product managers rely on data to make informed decisions? How can they leverage specific measurement and metrics tools to evaluate the performance of AI products? |
| Ethical considerations, upskilling, and future prospects | Wednesday, June 26: 7:00 PM – 8:00 PM ET | What are the key ethical challenges in the field of AI product management, and what are the skills and dispositions required to mitigate them? How can AI product managers leverage continuous learning to successfully navigate the evolving and exciting field of AI product management? |
*Front Row participants are eligible for two more additional sessions to take place on July 2 & 3 from 7:00 PM – 8:00 PM ET.
Registration details
Registration is now open! The deadline to register for this learning sprint is June 3, 5:00 PM ET. Limited Front Row seats are available. Register now to secure your spot!
Fees
Front Row ($279); General Admission ($129)
Additional information regarding this learning sprint including Frequently Asked Questions can be found here. For additional inquiries, please reach out to us at d3ln@hbs.edu.