Developer to Data Scientist

 Where to start:

As a developer you would be keenly looking to re-use your development skills into data science and that’s a good thing as development skills are important part of the Data Scientist’s toolbox.

  • Up-skill on Python/R : If you are already comfortable with Python/ R you saved yourself a lot of time and you should be ready to move to the next step. If you are new to Python / R you would need to get yourself comfortable with anyone of them to begin with. Python is great for beginners who especially those who are new to programming.  As a C# developer I was immediately drawn to python and was amazed how easy it is to get things done in python. A great way to learn python is to start doing it, I would recommend HackerRank . Start doing the easy ones get comfortable with the syntax and then move onto medium and hard ones. It is completely fine if you are not able to solve all the problems, the idea here is get comfortable with the language and not to master it, our real goal is master machine learning.
  • Up-skilling SQL: If are new to SQL then you should spend time learning SQL as most of the data especially the enterprise data resides in relational databases, so it’s very important to understand how to query them and the best resource out there to practice SQL is .
  • Apply machine learning: This is the most interesting part of the journey as you acquire some new skills and concepts here. Make sure to select one online course from the plethora of the courses available out there and make sure to complete that. Luckily for us, the courses have been curated and listed here based on their popularity.

Gamify the learning process:

  • Kaggle : The most fun way to make progress is to gamify the whole experience. Kaggle does that to some extent. Leader boards, points, progressing from novice to master, forums help you stay motivated and keep trying again and again.

Staying Connected(Community):

Pet Projects:

Start doing some pet projects that you feel passionate about. Try to find the right datasets, perform the pre-processing and then start applying the machine learning models to uncover insights. I like sports and hence any dataset that is about sports gets me interested. You can find interesting datasets in the links below. just search for them and start exploring.


Create a online presence:

  • Blogging/Teach/Share your journey : Make sure you share your journey and your learnings with the data science community as it will help you keep motivated. Teaching is the best way to learn something so make sure you create content which helps the community. Start a blog and try to add value to the community.

Don’t forget the soft skills:

Uncovering insights from data using a fancy algorithm is an awesone skill to have but it’s of no use if those insights are not shared and presented well. Meetups and events like Toastmasters can be a great place to start and improve your presentation skills. Always start small with a presentation to a small group of people and get their feedback and then slowly progress towards a larger group.

Staying motivated:

It’s very to stay consistent with your goals. It’s very easy to over do it and then burn out , pace yourself so that you can sustain yourself in this journey. Optimize your life to help you reach your goals.

Iterate the above steps:

Data Science is ever evolving field so it’s always important to iterate , track your porgress, learn and unlearn concepts. The important bit is staying motivated and enjoying the journey.


This blog post is a work in progress as i am myself taking this journey and these have been my findings. I will keep updating this post as and when i uncover great resources.