A First-Hand Dive into Duke’s AI for Product Innovation Master's Program

April 1, 2022 | By Shyamal H Anadkat

An account of the first year in as Duke 'AIPI' student

Glasses sitting on a laptop keyboard

AI/ML science has truly gotten to the where machines are able to “upsample” a small vector space to “realize” reality with AI.

Shyamal H Anadkat is a first-year graduate student in Duke's Artificial Intelligence for Product Innovation (AIPI) Master of Engineering program. He has a dual Bachelor’s degree in computer engineering and computer science from the University of Wisconsin-Madison and certifications in Business Analytics & Entrepreneurship from the Harvard Business School Online (HBX). Find out how he got to Duke, why he pursued Duke’s AIPI program and his experience in the program so far.

I came to Duke with a background in software engineering and a few years of work experience in the internet industry. I pursued my undergraduate degree in computer engineering and computer science from Wisconsin. Before moving to Durham, I worked as a senior software engineer based out of Chicago for Grubhub—one of the leading independent same-day delivery platforms in the United States.

During my time as a software engineer, I realized an increasing need in our organization to innovate and experiment, especially with machine learning (ML). Within our team, there were new verticals where machine learning could potentially accelerate automation and make better use of our data and resources—for example, predicting the customer turnover over a specific timeframe or automating how we handle certain delivery flaws. However, I experienced a gap where some engineers and managers, including myself, did not have enough domain expertise to make the best out of opportunities where AI/ML could help. I did not feel confident enough to experiment with machine learning models on such a scale.

After chatting with a few other friends at various tech companies in Silicon Valley, I realized that this AI (artificial intelligence) engineering leadership gap is widespread. This was one of the motivating factors for me to pursue further education to improve my applied machine learning skills and eventually become a leader in the space.

CHOOSING DUKE

In general, I was intrigued by the AI/ML landscape and the current trends. There has been exponential progress in algorithmic advances, compute power and open-source datasets. Moreover, machine learning evangelists are pushing boundaries to democratize data science and its applications. AI is becoming such a general technology that every single organization is investing in it, and it is creating massive opportunities and a lot of rewarding careers. With its broad spectrum of applications, AI/ML is at the forefront of solving some of the more rigorous problems across various disciplines.

I wanted to immerse myself in hands-on machine learning, from the ground up.

I wanted to immerse myself in hands-on machine learning from the ground up. That is when I came across Duke’s brand-new Artificial Intelligence for Product Innovation (AIPI) program. Duke launched AIPI in 2021 to train early-career engineers and scientists in using AI to solve problems. The interdisciplinary nature of this program that targets business, technical and ethical aspects of creating AI solutions in the real world encouraged me to pursue this program. And, practically speaking, Duke’s AIPI is one of the few programs in the nation that offer something like this.

After having a brief conversation with Jon Reifschneider, Director of Master's Studies for AIPI, I was convinced that this program would be a suitable stepping stone for me toward building products that would enable me to be a part of this AI commercialization era by implementing solutions with the right amalgam of sustainability and scalability.

SO FAR, SO GREAT

My experience in the AIPI program so far has been nothing short of amazing. Our cohort is small and immersive, which allows for a personalized learning environment. I have been able to pursue hands-on machine learning projects that address real-world problems with an addressable impact. For example, our fall project team for AIPI 510 (Sourcing Data for Analytics) worked with the government of nearby Wake County, North Carolina, to develop a machine learning model to help its health inspectors identify restaurants with critical food safety violations.

Duke’s novel curriculum, spread across industry seminars and the capstone project, truly prepares one to become a leader and expert

What I love the most about the program is that it is extensive on the application side of machine learning. Coming from a traditional computer science and electrical and computer engineering background, this is something that I appreciate. With AI/ ML, the more you work with data and derive meaningful insights from it, the better prepared you will be for a rewarding career. AIPI’s novel curriculum, spread across industry seminars and the capstone project, truly prepares one to become a leader and expert in this space.

Reifschneider, who worked hard on planning the curriculum, said, “We took a very different approach; we sat down with a blank sheet of paper about three years ago when we started designing the degree.”

Overall, the program encompasses the core aspects of applying AI to solve problems in a very disciplined and holistic manner. I cannot wait to see what opportunities AIPI unlocks for my colleagues and me in the future.

Go Blue Devils! 

Shyamal H Anadkat is pursuing Duke's Artificial Intelligence for Product Innovation Master of Engineering degree, with a graduate certificate in Innovation & Entrepreneurship.

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