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Capital One associate Pradeep stands in front of a white wall wearing a Capital One 'Reboot' sweatshirt. His picture has Capital One yellow and blue triangular treatment, and the image is next to a two-toned blue triangular background

Pursuing a passion for machine learning

This story is part of an ongoing series in which we highlight graduates of Capital One’s Machine Learning Engineering Training Program (MLETP), a 160-hour program that teaches software and data engineers the skills necessary to work in machine learning and AI. Learn more about MLETP.

Pradeep picked up the value of continuous learning from his mother, who earned multiple master’s degrees and a Ph.D. in education. So after becoming a software engineer at Capital One in 2017, he was quick to embed himself in our culture of growth and development.

Pradeep followed his curiosity and began developing skills in machine learning, a form of artificial intelligence that can automatically predict outcomes. Capital One uses machine learning to create real-time and intelligent customer experiences that bring simplicity to banking.

“I was inspired to gain machine learning expertise after hearing leaders in the company discuss the strategic importance of it at Capital One,” said Pradeep, now a lead software engineer. “Machine learning is going to help us achieve things we never thought imaginable for both our customers and the broader business.”

Pradeep used our tuition assistance benefit to earn a master’s degree in information technology at Virginia Tech, where he learned the foundations of data science and machine learning. He also enrolled in MLETP, which all software and data engineers can apply to, for a deeper understanding of machine learning algorithms and how Capital One applies them. With MLETP, Pradeep enjoyed the camaraderie of learning alongside associates. Watch the video below to learn more about Pradeep's experience in the MLETP, including how the team supported him as he experienced some personal life moments.

Pradeep felt like he was in a classroom again. He had access to subject-matter experts who taught him machine learning applications on Amazon Web Services, performance metrics, parameter tuning and model validation.

“The level of resources at our disposal was a big highlight,” Pradeep said. “I graduated with a more hands-on application of what is needed to deploy machine learning on Capital One’s own homegrown, enterprise-wide tools, services and platforms.”

MLETP, which lasts approximately five months, gave Pradeep the hands-on experience he was craving while balancing his day job and maintaining a healthy wellbeing.

“It speaks a lot to the culture that Capital One gave me the time and resources to focus on pursuing my education while doing my day job,” he said.

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