October 29, 2024, by Prof Meghan Gray

MSc Machine Learning in Science: Aakansha’s experience

Guest post by Aakansha Dhawan, MSc Machine Learning in Science 2023

Coming from a computer science background, I always had a strong foundation in algorithms and programming. However, I was eager to delve deeper into the evolving world of artificial intelligence, which led me to pursue the MSc in Machine Learning in Science at the University of Nottingham. The program’s blend of theoretical coursework and hands-on projects made it an ideal choice to sharpen my skills in machine learning techniques and their scientific applications.

While studying, I also worked part-time as a Data Analyst and ML Researcher at Oak Brook. This role provided me with valuable real-world experience where I could apply machine learning algorithms to solve practical business problems, such as customer segmentation, churn prediction, and process automation. I tackled diverse challenges, including working with noisy datasets and optimizing model performance, which refined my skills in data preprocessing, feature selection, and hyperparameter tuning.

One of the highlights of the program was an interdisciplinary project where I applied natural language processing (NLP) techniques to analyze financial data, extracting trends and predicting sentiment around certain events. This project gave me a chance to explore different machine learning approaches, such as recurrent neural networks (RNNs) and transformers, and understand their strengths in handling sequence data.

The supportive learning environment at Nottingham was invaluable, featuring expert faculty members who guided me through cutting-edge research in areas like deep learning and reinforcement learning. The opportunity to collaborate with peers from various scientific disciplines also broadened my understanding of how machine learning could be applied across diverse fields, including healthcare, finance, and environmental science.

Completing the MSc program laid a solid foundation for my career in AI. The skills and experiences I gained helped me secure a research internship focused on deep learning applications in computer vision, and later, a full-time position at a leading technology company. I now work on developing AI solutions for real-time data processing and predictive analytics, applying the knowledge and insights I gained during my time at Nottingham every day.

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