Learning Data Science as a Software Engineer An interview with Applied Data Science Alum, Sunny Ghosh
Sunny is a senior software engineer working in the energy sector. He completed the Applied Data Science Bootcamp to master new skills for his work and personal interest in AI for autonomous drones.
In his industry capstone project, Sunny brought everything together and combined software engineering practices with Natural Language Processing for predictive modeling.
I’ve learned a lot about the thought processes and how to implement each application appropriately. The learning activities always introduced new useful concepts for me — machine learning, unsupervised learning, supervised learning, NOSQL in realistic ways.
What did you most enjoy working on during the Bootcamp?
I enjoyed everything about the Applied Data Science Bootcamp, starting from the lectures and assignments. Through to the social atmosphere, working with classmates from different backgrounds and evening meetups.
What were your key takeaways from the programme?
When I started the Bootcamp, I was not confident about mathematics and statistics and I got a good grasp after the sessions. It’s also noticeable how much I’ve learned about applied machine learning and deep learning techniques.
Tell us a bit about your final project, what did you work on?
I worked with Cytora, a UK-based Insurtech start-up. The project allowed me to combine software engineering practices with the new Natural Language Processing techniques. The first subproject was finding grammatical errors as the complexity of a sentence. Then the second ongoing subproject involves finding associations between companies.
What piece of advice do you have for those looking to join the Applied Data Science Bootcamp?
I would say to brushup maths and statistics before the course — the preparation helps. Also, never skip an assignment, the practice is essential.
The overall experience is great for everyone joining this course. The best parts are the lectures, assignments and working for a company for the final project.
If you are coming from a software development or engineering background and want to get into Data Science, check out our Applied Data Science Curriculum for more information about the Machine Learning techniques we cover.