Life started late…… But it’s rocking😊
“Anyone who stops learning is old, whether at twenty or eighty.” — Henry Ford
I switched my career to Data Science at the age of 46 that too after so much criticism and pressure from friends and family. I am passionate about coding and that’s long-time dream to achieve. This started after fighting with myself first as I was well settled in life and career, working as a People manager for Infrastructure team with Fortune 500 company and enjoying life of a much hyped manager (with minimum work, 90% delegation 😊). Practically, never did any coding except during my under-graduation diploma courses, I learnt little bit Oops (like C++) only to clear my semester exams.
There is saying “ Be stubborn about your goals and flexible about your methods.”
I have this feeling, in fact a dream to do coding on any programming language like C++, Java or Perl but I heard and read somewhere about Python and the next big thing in 21st Century i.e. Data Science. I started learning Python as well as R in spare time, I loved both and regularly followed some of the free coding sites as well as my office tutorials (IBM has long list, which helped a lot). While browsing internet, I got a free pdf of ‘The hard way to learn Python’ that was the first book which helped me to learn basics and push me to learn more. I am an avid reader and love to read books articles as much as I can.
I subscribed to Medium and read almost 4–5 articles every day, one of the biggest sources of knowledge. I joined Kaggle one of the best thing in life and next best thing was GitHub. There are many others however these three MKG (Medium, Kaggle & Github) helped a lot and I never miss them, and if time permits, I go through some other sites like AnalyticsVidya, Data Stories, Flowing Data, Reddit and many more. I used to code almost every day and participate on Kaggle and learn from previous grand masters from their projects and from various repositories by greats on GitHub.
Apart from these, I did a six months Executive program from XLRI in Data Science, and used to attend and learn from various sites some of them are:
MIT free Courses
Andrew NG classes (Coursera or Stanford)
AnalyticsVidya (courses)
3Blue 1Brown
LinkedIn Courses
Khan Academy (specially for Math, Algebra)
Udemy courses (cheapest courses and easy to access)
I refer many books and I am still reading some of these and suggest data science aspirants to go through these, these are wonderful:
- Python Data Science Handbook: Essential Tools for working with Data — By Jake VanderPlas
- Statistics in Plain English — by Timothy C. Urdan
- Data Mining and Predictive Analytics — by Daniel T. Larose
- Storytelling with Data — by Cole Nussbaumer Knaflic
- Learn Python the Hard Way — by Zed Shaw
- Deep Learning — by Ian Goodfellow, Yoshua Bengio & Aaron Courville
- SUPERINTELLIGENCE — Nick Bostrom
Initially, it was very tough to know everything about Data Science as it’s diverse field. The journey was tough from being a non-productive people manager to a sort of developer, in past two years it was kind of tough learning period, sometimes it looked like I joined school again and started learning basics of Statistics to Algebra to Machine learning to Neural Networks and many more, however, now I feel all those efforts helping now, and keep myself engaged to improve it further and to learn more.
Currently, working on various Machine Learning projects along with one of the most prestigious team with lots of learning and guidance. I am vying for more interesting projects to explore more and test my knowledge and enhance it further.
Although, I am still not a veteran in this new field however, I love to continue this journey and keep myself updated as much as I can to walk along with the new gen 😊. At last I am happy to fulfill my long time dream and working on those tech which I am passionate about.
Thank you for reading, appreciate your feedback and suggestions on how to improve it further.
Mail me at tej_on@outlook.com
