Structured Learning that Fosters Curiosity: Meet Dartmouth MEng Student Naisha S.

After earning her undergraduate degree in electrical engineering, Naisha S. was in the early stages of her career when she began thinking about a graduate degree. There was still a good deal to learn, especially when it came to artificial intelligence (AI). 

Naisha had taken courses on Coursera some years earlier, and when she learned she could earn her Master of Engineering (MEng) in Computer Engineering from Dartmouth—the institution responsible for the 1956 Dartmouth Conference that investigated early AI—via the same platform, it seemed like an ideal opportunity. 

She found the program set up in a way that fostered her natural curiosity. “While the project-based curriculum was well-structured, it was also intentionally open-ended in all the right ways,” Naisha said. “It encouraged students to think independently and problem-solve on their own, but we were supported with a wide range of resources, such as documentation, articles, and example problems.” 

That structured approach to learning, where she was encouraged to discover answers for herself but had a wealth of available resources at her disposal to guide her learning, was a style Naisha truly enjoyed. “This balance helped reinforce my learning, build confidence, and deepen my understanding of the material,” she said. “Overall, it created an environment where I could truly succeed.”

Naisha spoke with Coursera about why Dartmouth turned out to be a good fit for her degree aspirations, what she’s enjoyed about the MEng program, and the advice she has for other potential students. 

Why did you want to earn your MEng?

I was early in my career and there was still so much I wanted to learn, especially when it came to all the recent advancements with AI. Looking over the courses offered in the program, including Natural Language Processing, Machine Vision, and FPGA Design, I knew it would help me develop the skills and knowledge to handle all the new emerging technologies. 

Why did you choose Dartmouth?

The university itself and the program’s flexibility were the biggest factors. Being able to learn about AI from professors at such a reputable institution, especially one where the term “AI” was originally coined, while continuing to work full-time was an incredible opportunity. 

Did anything in particular draw you to the program?

I knew I wanted hands-on experience and access to direct communication with the faculty, and this program provided both: through office hours, different communication channels, and a project-based curriculum that included working with hardware. The faculty were exceptional and incredibly supportive. This extended beyond just professors and TAs—it included program managers and the technical computing team. 

Plus, the more I learned about the range of classes I would take in the program and the depth to which the content would go, I knew it would help me as I progress through my career. And though I finished the program in less than two years by taking a full-time class load, going into it I knew there was also flexibility allowing students to take part-time loads or take term breaks if needed. Having that optional flexibility going into the program was reassuring.

How did you balance learning with your other responsibilities? 

I took one or two classes per term. During that entire time, I was also working full-time as a hardware verification and support application engineer, and I even served as a Teacher’s Assistant (TA) for the Natural Language Processing course for one term! 

My role was remote, which helped eliminate commute time, but balancing all of these responsibilities was still extremely challenging at times. There were definitely late nights (as anyone pursuing a degree can relate to), but the program’s structure and faculty support made it manageable. 

Ultimately, the experience taught me that balancing a full-time job and a rigorous academic program is possible with the right structure and support system. It pushed me to become more intentional with my time, and confident in my ability to take on new challenges. These skills have stayed with me well beyond the program itself.

Was there a particular program feature that helped you stay on track? 

One aspect that really helped was the program’s organization. While the exact time required for assignments can vary (especially in engineering, where debug times can be unpredictable), the courses provided estimated timelines for lessons and coursework. This made it easier to plan ahead. 

There was also a consistent weekly structure, with clear deadlines and regularly scheduled office hours from both TAs and professors, making it easy to get help before assignments were due. The faculty were also incredibly supportive and understanding. For example, when I had to deal with some hardware-related issues, they were responsive and worked closely with me to resolve them. Over time, I developed a better sense of the program’s rhythm and was able to adapt my schedule accordingly. For me, that meant watching lectures during breaks or lunch and dedicating evenings to assignments and projects.

Did you enjoy anything else about the program? 

Connecting with a diverse group of peers who were also working full-time across different industries—and even different countries! The program fostered a collaborative environment through active shared communication channels like Slack, where people regularly asked questions, offered advice, and shared helpful resources. It went beyond coursework with students posting about new technologies, upcoming conferences, and important reminders. That sense of community created a shared motivation that played a major role in my success. 

Despite being fully online, the program also made it easy to feel like part of the broader Dartmouth community. Through the program, I also became part of Dartmouth’s alumni network, which has opened the door to connecting with individuals from a wide range of backgrounds. This includes both people from the online program and those who attended Dartmouth in-person. 

Has your degree had any impact on your life thus far? 

Earning a degree from Dartmouth has impacted my life in so many amazing ways. For one, I feel much more confident working with both new hardware and software tools related to AI. The project-based curriculum allowed me to actively apply what I learned, validate my understanding, and develop the ability to clearly explain and present complex concepts—skills that have been incredibly valuable in my career. 

Another major impact was the sense of community I felt throughout, and even after, the program. I was able to connect with so many amazing people throughout the program—peers I stayed in touch with across different terms and courses, and many I still communicate with even after completing the degree! 

Ultimately, this experience didn’t just help me grow technically; it gave me a strong sense of belonging, a supportive professional network, and the confidence to continue pursuing new opportunities in the evolving field of AI.