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Harsh Tushar Magiya

Meet Harsh, he studied Machine Learning MSc at UCL Computer Science and graduated in 2024. Find out more about his experience.

Harsh UCL Computer Science student sat on steps
What's your background

I am originally from Mumbai, India where I graduated with a BSc in Mathematics from the University of Mumbai, Ramnarain Ruia College.

 While studying at this University, I delved into courses such as Calculus and Discrete Mathematics. Before joining UCL, I worked as a Jr. Data Scientist at Novacept (Smartedge) and Zummit Infolabs LLP, where I gained substantial experience in building and deploying machine learning models.

Why did you choose to study Computer Science at UCL?

UCL's reputation for academic rigour and its pioneering research in Machine Learning drew me to enrol here. The curriculum offered advanced courses on Bayesian Deep Learning and Statistical Natural Language Processing, aligned perfectly with my career aspirations.

UCL provided the ideal platform to deepen my expertise in machine learning, an area I am very passionate about.

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What were the highlights of your CS programme?

The CS programme at UCL was filled with numerous highlights: from engaging lectures and approachable lecturers to innovative teaching methods.

The hands-on projects and the modern approach to problem-solving have been particularly enriching, enhancing both my theoretical understanding and practical skills.

What were the highlights of your time generally at UCL?

My time at UCL has been greatly enriched by the diversity of its community. I enjoyed interacting with peers from various backgrounds and disciplines, which provided a richer learning environment.

The active societies at UCL were also a highlight, allowing me to engage with enthusiastic groups who had a variety of interests which made my experience more fulfilling.

What industry and career opportunities did you get access to on your programme?

The ML programme at UCL opened doors to research-based roles and provided me with exposure to industry leaders through guest lectures.

I participated in a dissertation with a London startup, which deepened my understanding of the UK's work culture and the evolving market applications of machine learning.

What did you write your dissertation on? 

I chose to focus on developing a Q&A bot for the legal domain using the RAG architecture, intrigued by the potential and novelty of this technology. This project allowed me to delve deeply into advanced concepts like text chunking and embedding models, significantly enhancing my understanding and skills in cutting-edge ML technologies.

How did you manage your workload, and what advice would you give to prospective students in terms of being successful and making the most of the opportunities at UCL?

Balancing academic work with leisure activities was crucial for managing stress. I participated in various societies, including dance and kick-boxing, which not only helped in stress management but also allowed me to meet new and interesting people. My advice for prospective students is to engage actively in campus life to enrich your educational experience.

If you were an international student, how easy was it to settle in? How did you find studying in the UK?

Transitioning from India to the UK was made smoother by UCL's welcoming orientation week and various student societies. These initiatives were instrumental in helping me establish a new social network and integrate into the vibrant UCL community. London’s dynamic environment was both exciting and enriching, adding greatly to my overall experience.

Where are you working now, and what are your career goals? How did your programme help you achieve this?

Currently, I am preparing for a PhD in Deep Learning, aiming to further my research in this innovative field. While I am in the process of job hunting, my experiences at UCL have been instrumental in shaping my academic and professional path towards this goal.

Why would you recommend this course?

I highly recommend this course for anyone interested in advancing their understanding and application of machine learning. The curriculum is thorough, and the academic staff are not only knowledgeable but also genuinely supportive.

The diverse opportunities for hands-on learning and the dynamic environment at UCL make it an outstanding place for both personal and professional growth.

Want to hear more from our students?

Register for our Virtual or In-Person Open Days  

Virtual Open Day (Graduate Open Events: Computer Science)

  • Date: Wednesday 22 January 2025
  • Time: Choose a session: 12:00 noon OR 5:00 pm (UK time)
  • Content: Discover the department, our careers support, scholarships, opportunities with industry and more. Ask your questions to staff, students and alumni.

Both sessions are identical - pick the one that suits your time zone best.

In-Person Open Day (Graduate Open Events: Faculty of Engineering Sciences)

  • Date: Saturday 25 January 2025
  • Time: 10:00 am – 4:00 pm
  • Content: Meet us in-person and explore what makes UCL such a unique place to study. Attend insightful talks, get a feel for the campus, and speak to our staff and students face-to-face.

Important: If you'd like to attend both events, please register for each separately by clicking back to this page after submitting your first registration.

We’ll send you more information about the department, your programme, and the next steps after you register.

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