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My Data Science Journey and Suggestions - Part 2


If you haven't read the Part 1 of my Data Science journey, I recommend you to read it before you go through this article. Link to the Part 1.

In the early days of my third year (5th semester), I decided to have a career in Data Science, after taking feedback from my relatives, professors and seniors. At that time, I heard only three words on the internet i.e, Artificial Intelligence, Big Data and Cloud computing. The Machine Learning course by Andrew Ng was awesome and showed me a path to explore a different domain.

My performance was good in the first four semesters, so I got an opportunity to work under a professor for two years in a specific domain. I didn’t want to lose this opportunity. There were two main streams in my college, Natural Language Processing and Computer Vision. There was a huge competition for Computer Vision in my college as there were many professors working on Computer Vision problems. I never explored both domains.

Finally, text processing and NLP looked more attractive to me. So, I started working on a research project Aspect based Sentimental Analysis on Codemix data. The team size was 2 and my professor helped us a lot by providing resources to get started with NLP and text mining. The whole pipeline starting from data collection to modelling was done by us. This project lasted for one year and I learnt a lot. During this span, I have experienced the whole NLP pipeline. One of the helpful resources was Machine Learning Mastery website. This helped me to get started with coding in ML and explored different articles form the website to get hands-on experience. I will recommend everyone to visit the website to get started with Natural Language Processing or Computer Vision.


Deep Learning Specialization by Andrew Ng was released course by course during the fifth and sixth semesters. You can find the link to the course here. The specialization has five different courses. You can find the contents of the specialization below:
  • Course 1 - Neural Networks and Deep Learning
  • Course 2 - Improving Deep Neural Networks
  • Course 3 - Structuring Machine Learning Projects
  • Course 4 - Convolutional Neural Networks
  • Course 5 - Sequence Models

I have done this course after the machine learning course. He taught all the deep learning concepts in a simple way. And the assignments are at a different level. The whole course was amazing. I recommend everyone to take this course who wants to explore Deep Learning. He introduced all the basic concepts to get an intuition of what the deep learning is. I also started improving my GitHub profile by uploading all my Data Science related projects and assignments. I documented my codes and added a readme file to make my profile more attractive and understandable.

In December 2017, I got an opportunity to attend the Google Developer Days conference that was held in Bangalore. The two days event was amazing and it was organized superbly. It was very exciting to hear how Google is using data to solve complex problems using Machine Learning and Artificial Intelligence. Throughout the years, it has gathered an enormous amount of data in all formats. This conference pushed me to explore more in Data Science. So, I started attending meetups to get updated with the latest technology and networking with the professionals.

This is the end of Part 2. I hope you enjoyed reading my journey. If you have any queries, comment in the comments section below. I would be more than happy to answer your queries.

Link to Part 3 of my Data Science journey.

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