Sona

Why did you choose to study your course at Surrey?

I chose to study Data Science at Surrey because of the university’s strong reputation for excellence in teaching and research, particularly in computer science and emerging technologies. The university is consistently recognised in UK and global rankings for its academic quality, student satisfaction, and graduate employability, which made it an ideal place to study.

I was attracted to Surrey’s industry-focused approach to learning, the practical nature of the Data Science programme, and the opportunity to gain hands-on experience through real-world projects and placement opportunities. The university’s strong connections with leading companies and its focus on innovation aligned well with my career goals in the field of data science.

What are the best things about Surrey and your course?

One of the best things about studying at Surrey is the supportive and approachable nature of the lecturers. They are always willing to help students during lectures and lab sessions, and I have really appreciated the support from lecturers who have gone out of their way to support with career development and advice. 

Another great aspect of the university is the labs. I love our lab sessions because they provide hands-on practical experience that complements the concepts taught in lectures. Plus, the labs themselves are always accessible for students. Having the flexibility to access university systems and work on projects anytime makes it much easier to manage my coursework, research, and independent learning effectively.

What are your career plans?

My career plan is to work in the Applied AI field and use data science and machine learning to solve real-world problems and create meaningful impact across different industries. I am particularly interested in predictive analytics, intelligent systems, and automation, and hope to apply my knowledge in these areas throughout my career.

My plan is to continue developing my technical and research skills through practical projects, both on this masters course, via practical projects and through industry experience and practical projects. 

What advice do you have for students thinking of doing this course?

My advice for students considering this course is to be prepared for both the theoretical and practical aspects of Data Science. Having a basic understanding of programming, mathematics, and problem-solving will be helpful, but the course also provides strong support to help you improve along the way.

I would also encourage students to actively participate in lab sessions, work on personal projects, and make use of the university’s resources and opportunities to connect with lecturers and other students. Being curious and willing to learn continuously will help you get the most out of the course.

To find out more about our Data Science MSc, check out our course page.