Making Quantum Computing Accessible and Convenient Through Online Learning
IBM Watson AI Lab and MIT xPRO Collaborate to Support Lifelong Learners
IBM Watson AI Lab has collaborated with MIT xPRO to develop an online quantum computing curriculum intended for professionals and leaders in business, government, and technology interested in the theoretical and practical aspects of quantum computing (QC).
Learners in this online program apply the principles of QC to real-world examples using IBM’s Quantum Experience System (IBM Q), a state-of-the-art web-available quantum computer. We spoke with two of the online learners about their experiences completing the course.
Andrew Ochoa earned a Ph.D. from Texas A&M in computational physics and currently works as a physicist at Austin-based Strangeworks, an IBM Q partner that “humanizes quantum.” As Ochoa explains it, “by the time IBM rolled out their Q Experience, I was already neck deep in finishing my experiments and writing my thesis, so I didn't get a chance to play around with gate model computation. Consequently, I had this gap in my knowledge, which became my motivation for taking the course.” An additional motivation was Ochoa’s desire to see how the course approached teaching QC, which would help in his educating role in “humanizing quantum” on behalf of Strangeworks.
Melvyn White is Director of the London-based Deutsche Bank AI Lab, having worked over a decade for the financial services giant. As someone with a deep knowledge in AI, White took the course because, as he says, “I’m an engineer and data scientist who’s curious and wanted to extend my theoretical knowledge. I also knew that the course was practical, exploring how QC is being applied. I thought the course might also help me in my professional development.”
Benefits for Online Learners
Ochoa and White are busy professionals with families, and both found the online course an accessible and convenient way to learn about QC. “Part of my job is traveling a lot,” says Ochoa, “I was in Geneva, in Japan, and other places, so being able to work online was definitely helpful.” Ochoa also became a new father when the course began: “my daughter was only three months old when the course got started, and being able to do the work at my own pace, when it was most convenient, definitely helped me juggle my multiple obligations and finish the course.”
What did learners enjoy most about the course? For Ochoa, it was the breadth of the material covered and the industry perspectives. “The most useful topics for me were the different qubit modalities. I knew what a qubit was, but learning what is current and having that broad overview helped me start doing my own work.” Ochoa also liked “how instructors tailored the materials for beginners in quantum mechanics or quantum information theory, especially in the first course, Introduction to Quantum Computing.”
Especially valuable for Ochoa was the course’s coverage of quantum error correction for gate model computers. “I had zero knowledge of that before, but now I have a working, fundamental knowledge.” Ochoa notes that “quantum error correction is going to be very important for near-term quantum computing because you definitely need error correction as you add more qubits. The quality of qubits is still not very good, so it's just this unavoidable consequence that I hadn't considered before I began the course.”
Deutsche Bank’s Melvyn White had “a great overall experience” with the course, adding that it “opened up so many new possibilities for me on both a theoretical and practical level. I especially liked how the course put the development of QC into a historical context, how it compared the development of QC to the way classical computing developed over time, although QC is developing much faster of course.”
Both Ochoa and White were enthusiastic about the course’s use of the IBM Q Experience. “Having the ability to program on a quantum computer from home,” says White, “was a unique and fantastic experience. It made the theoretical so much more more practical and hands-on.”
Applying Lessons Learned
Ochoa is already applying what he learned during the course, especially as it relates to making quantum computing accessible in his role with Strangeworks. “We're constantly meeting with potential partners, with people in industry, and they’ll usually say, ‘I read about this photonic quantum computer. I read about what IBM is doing. What does it mean?’ Having this broad overview from the course helps me explain concepts to people who may not have so much scientific background,” says Ochoa.
For Melvyn White, the next step is sharing what he learned from the course with his colleagues at Deutsche Bank AI Lab. “I’ve been asked to give presentations internally about what I learned during the course,” White says, “It’s important for me to be early in this emerging technology space.” What’s clearest from Ochoa and White is that the QC course served both to deepen their theoretical knowledge while also helping them apply lessons learned to their professional lives, all in an accessible, convenient way through online learning.
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