How I Got Into Northeastern University, Boston For MS in Artificial Intelligence?

Hey! Who are you, what are you currently doing and what is your background?

Hello, I’m Vishwajeet Hogale, currently pursuing a Master of Science in Artificial Intelligence at Northeastern University. 

I completed my Bachelor of Technology in Computer Science at PES University, where I gained hands-on experience early on through an internship with the student-led startup Multilex Technologies. There, I worked for nearly two years, building a platform that scraped data from news sources for UK-based clients. This role allowed me to dive into backend development, database management, and language modeling while balancing my coursework. Eventually, I led a small team within the startup, honing my skills in both development and project management, which significantly enriched my approach to professional and academic challenges.

Post-graduation, I joined Mercedes-Benz in their procurement division through campus placement. While my role primarily focused on data within the procurement cycle, I also engaged in projects like developing a cost-saving software solution that eliminated vendor dependency for support tickets. Parallel to my job, I contributed to open-source work, notably with Why Waste, building an app for UNICEF’s water conservation campaign across hundreds of schools. While I wish I had published research, my involvement in real-world projects and volunteer work added meaningful depth to my profile.

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How did you decide that you wanted to pursue an MS in the US?

Working at a European company, I learned that workplace culture there often feels more rigid, with long hours and less focus on personal growth. I noticed I wasn’t gaining as much from the experience as my peers, who were learning a lot in more dynamic environments. I believe that early career pressure can drive growth, and the U.S. offers a highly competitive, performance-driven atmosphere that I feel would push me to excel. Financially, too, the U.S. is appealing, providing solid earning opportunities alongside professional growth.

Diversity also influenced my decision to study in the U.S., though I was surprised to find a very Indian-centric community upon arrival, which didn’t fully align with my expectations of broader cultural exposure. However, I chose to pursue a master’s in AI specifically because of the global shift toward artificial intelligence. I’ve been drawn to AI, machine learning, and deep learning since my undergrad, focusing on personal projects and work approaches that align with these fields. I found AI-related problems engaging and was naturally inclined to explore them, whereas topics like database optimization or networks were less compelling to me.

A master’s in artificial intelligence allows me to build expertise in a field I’m passionate about, opening up more opportunities to contribute meaningfully in the data space.

How did you start your application preparation; can you throw some light on profile building, GRE, LORs and SOPs?

GRE/TOEFL

When I decided to pursue my master’s, I prioritized completing the TOEFL and GRE. For the TOEFL, I felt confident given my background, so I reviewed the exam structure and formats without extensive studying. The GRE, however, required more focus, especially since top universities often expect scores above 325. While I found the quantitative section manageable, the verbal section proved more challenging, and I didn’t achieve my target score.

I used the Greg Mat platform, which provided structured study plans and essential vocabulary lists for the verbal section. Although my initial practice tests seemed easy and boosted my confidence, later scores revealed I needed more targeted preparation. To improve, I took timed practice tests every two weeks, dedicating the last two months to intensive study. Despite my efforts, my final GRE split was around 154 in verbal, with an overall score of 318. Although my verbal score fell short of my goal, I was pleased with my performance in the quantitative section.

SOP

For my Statement of Purpose (SOP), I approached it with the goal of making it understandable to any reader. I wanted them to see that I had a solid grasp of AI. Some people choose to tell a story about their inspiration, but I opted for a different approach. I mentioned my inspiration in the first paragraph but focused more on my projects related to AI in the following paragraphs.

I aimed to connect my experiences with the universities I was applying to. I made sure to mention how my background tied into the programs offered, including specific clubs or opportunities at those universities. 

LOR

Regarding my letters of recommendation (LORs), I had two from work and one from a professor. As for my timeline, I started preparing for the GRE in April, and by January or February, I had completed all my applications.

What colleges did you apply for and what was the result?

I applied to 7 universities as below.

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Can you tell us more about the course and what the learning outcomes are?

I selected this program for its strong emphasis on machine learning, which perfectly aligns with my goal of becoming a machine learning engineer. Northeastern offers targeted courses that build a comprehensive foundation in machine learning, including a general machine learning course, an advanced machine learning course, and specialized classes in supervised and unsupervised learning. This structured progression allows me to gain in-depth expertise in core ML techniques, along with the option to explore related areas like reinforcement learning, natural language processing, and robotics—skills highly relevant to current industry demands.=

This program also offers a unique focus compared to a Master’s in Data Science (MSDS). While data science and AI share common topics, like statistics and modeling, data science tends to be more business-oriented, focusing on generating insights for engineering managers and business teams. In contrast, the AI program emphasizes technical development and R&D, with a broader scope that covers advanced machine learning, deep learning, and more specialized areas. This difference allows me to deepen my technical knowledge, preparing me for roles that require advanced modeling and a strong research orientation in machine learning engineering.

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What is the cost of tuition and cost of living, and how are you planning to fund your studies?

The tuition for my program is approximately 48 lakhs INR for two years. Living expenses in Boston are high, with rent around $600–$750 per month depending on shared accommodation, averaging $8,400 annually. Additional monthly expenses are around $1,000, totaling approximately $12,000 annually. Overall, living expenses range from 10–20 lakhs INR for two years, making the total estimated cost for tuition and living around 68–70 lakhs INR.

Regarding funding, Northeastern does not offer many scholarships, and obtaining one seems to be quite rare. I’ve not seen many people receive scholarships here. I did reach out to some professors for research assistant positions; they were open to offering positions, but without pay, mainly because I applied very late in the process. However, securing a teaching assistant (TA) position is more manageable if you score well in the professors’ classes and reach out early. TAs typically earn between $20 and $22 an hour, depending on the professor.

As for my funding plans, I have taken a loan for my education from Bank of Baroda, primarily because they offered a lower interest rate of about 9.7%.

How was your experience with the visa process, finding accommodation and travel?

My experience with the visa process was quite straightforward. When I researched, I found that the visa experiences in Chennai and Hyderabad seemed a bit tough, while Delhi was not even on my radar. Everyone speaks about how Mumbai tends to grant visas easily. I believe that being very confident during the visa process is crucial. You need to know your material well, and if you do, the interview is just like a conversation. People often make it seem daunting, but honestly, there’s no need to be scared. It’s just a normal conversation where you should be prepared.

Regarding finding accommodation in Boston, there are several services available. I used a platform called Roommate, which was incredibly helpful. I reached out to one person from Roommate, and they filtered options for us, providing a couple of choices. There was no brokerage fee involved with this service, which was a plus. They helped us navigate the process smoothly, making it easier to find a place.

When looking for accommodation, it’s also essential to be aware of the area you’re considering. Understanding the neighborhood can significantly impact your experience.

What are the job opportunities after master’s?

Looking ahead after my master’s, I see a couple of pathways. If you work for top-tier companies like Uber, Nvidia, or Adobe, the compensation is quite good. You can expect to earn around $55 per hour, which translates to approximately $100,000 a year. This figure is similar for internships as well; for instance, at Google, if they pay around $55 an hour.

As for my personal career goals, I aspire to become a machine learning engineer, which also tends to have a base compensation around $100,000 or more. I’d also be open to other roles, such as a software engineer. Right now, I’m focused on securing internships and converting them into job offers, so I haven’t planned too far ahead.

Regarding the positions I’m applying for, employers generally look for candidates who are proficient in Python and SQL, as well as someone with experience in TensorFlow and PyTorch. If you’re aiming for research-based internships, having published papers is often essential, so having that background can be advantageous.

Any final words of advice for anyone who aspires to be where you currently are?

I think it’s important not to be demotivated if your GRE score isn’t as high as you hoped. Focus on making your Statement of Purpose (SOP) stand out. A compelling SOP can really catch the attention of the admissions committee. The GRE score, in that context, becomes less critical; it’s just one piece of the puzzle.

For me, the GRE process felt overwhelming at times. I got caught up in the numbers and let it stress me out. It’s essential to remember to prioritize the major components of your application. Learn to let go of things that you can’t control and focus on what you can improve.

Another piece of advice is to apply as early as possible. Aim to submit your applications in the early decision round, ideally before December.

Additionally, from a practical standpoint, I currently live in Roxbury, which isn’t the best area. I recommend looking for accommodation in safer neighborhoods like Boylston Street or similar places. It’s important to research your area carefully and not be lazy about it.

Throughout the process what were some helpful resources, tools and books you used?

For the GRE, I found resources like Princeton Review and official GRE practice tests to be quite helpful. Regarding the TOEFL, I opted for the IELTS instead, using a comprehensive book that covers everything needed, including sample tests.

In selecting universities, I conducted extensive online research using Google to find the top ten universities, although I don’t recall the specific websites. For accommodation, I used platforms like Roommates and Zillow to find housing options.

I managed my travel and visa process independently, without hiring consultants, and flew with Air France. 

For banking, I chose Bank of Baroda for my loan, though I also considered Union Bank, which had a low interest rate but came with some drawbacks. Bank of Baroda has a longer loan sanctioning process, and if you go for a HDFC Credila, expect an interest rate of 9.7%, which is relatively high but offers quicker sanctioning.

Suggested by TheGradPost

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Connect

Linkedin – Vishwajeet Hogale

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