Alexandra took the course in 2022-2023. She now works at Palantir Technologies as a Forward Deployed Software Engineer.
What was your background before starting the MPhil?
I had a BSc in Computer Science from the University of Bucharest and I had also completed two software engineering internships. Thus I had gained a real insight into the potential of machine learning to empower decision making. This inspired me to apply for the course.
What did you get out of the course?
First, top notch machine learning technical skills (both theoretical and practical). The course exposed us to most facets of machine learning, from probabilistic algorithms, Gibbs sampling, Gaussian processes to large language models, graph neural networks, adversarial learning, vision transformers, AI safety and many more.
I had a BSc in Computer Science from the University of Bucharest and I had also completed two software engineering internships. Thus I had gained a real insight into the potential of machine learning to empower decision making. This inspired me to apply for the course.
What did you get out of the course?
First, top notch machine learning technical skills (both theoretical and practical). The course exposed us to most facets of machine learning, from probabilistic algorithms, Gibbs sampling, Gaussian processes to large language models, graph neural networks, adversarial learning, vision transformers, AI safety and many more.
I developed the habit of reading related research publications and worked on my own ideas during the research project. I also learned the importance of clarity and precision when presenting my research. Conveying findings effectively can be challenging. By carefully crafting a structured narrative that is coherent, concise and cadent, your audience will quickly assimilate your material. The MPhil has equipped me not only with the ability to identify gaps in the current literature and build upon them, but also to present my results in an effective way.
What were the highlights?
One of the highlights for me was the Research Review in June when we presented interim results to our peers and professors. We had prepared posters and our classmates enthusiastically gathered around, eager to discover more about each other’s research. The atmosphere resembled that of a proper research conference and further ignited our interest in academia. However, the most notable aspect of the course was undoubtedly the people. The MLMI cohort evolved into an extremely bright and talented collective, keen to find solutions together and to actively contribute to the machine learning community.
One of the highlights for me was the Research Review in June when we presented interim results to our peers and professors. We had prepared posters and our classmates enthusiastically gathered around, eager to discover more about each other’s research. The atmosphere resembled that of a proper research conference and further ignited our interest in academia. However, the most notable aspect of the course was undoubtedly the people. The MLMI cohort evolved into an extremely bright and talented collective, keen to find solutions together and to actively contribute to the machine learning community.
What have you gone on to do afterwards and what are your longer-term plans?
I joined Palantir Technologies as a Forward Deployed Software Engineer and I plan to continue working in leading edge AI environments. I aspire to help bring intelligence to the core of the decision-making processes and to empower the human in the loop.
I joined Palantir Technologies as a Forward Deployed Software Engineer and I plan to continue working in leading edge AI environments. I aspire to help bring intelligence to the core of the decision-making processes and to empower the human in the loop.
What advice would you give to people applying for the course?
If you have an appetite for knowledge and a strong passion for machine learning, this MPhil is for you. Bonus points if you dream of spending your days in enchanting libraries, surrounded by towering shelves adorned with countless volumes.
The course is intense, yet undeniably serves as a door opener. Students come from all over the world and have different STEM backgrounds, ranging between maths, physics, computer science and engineering. Prior knowledge of probability and statistics helps and if you are curious to get a glimpse of the Introduction to Machine Learning module, I’d recommend delving into “Pattern Recognition and Machine Learning” by Cristopher Bishop!
What advice would you give to people taking the course?
Don’t forget to enjoy the Cambridge experience. Make the most of societies. Attend as many formals and May Balls as possible and nurture friendship. Be curious, ask questions and engage with the academic staff who are extremely supportive and kind. The course carries quite a substantial workload and will probably take most of your time but remember to also relish the Cambridge MPhil experience. After all, you are wandering through the very halls where Alan Turing once lived.
Don’t forget to enjoy the Cambridge experience. Make the most of societies. Attend as many formals and May Balls as possible and nurture friendship. Be curious, ask questions and engage with the academic staff who are extremely supportive and kind. The course carries quite a substantial workload and will probably take most of your time but remember to also relish the Cambridge MPhil experience. After all, you are wandering through the very halls where Alan Turing once lived.
16th February 2024