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I joined Analytics Vidhya as an intern last summer. I had no clue what was in store for me. I had been following the blog for some time and liked the community, but did not know what to expect as an intern.
The initial few days were good – all the interns were smart, motivated and fun to be around. We played cricket in office, did internal hackathons over weekends and learnt a lot of data science. But, if there was one defining moment for me in the internship – it was when I realized the impact Analytics Vidhya was having in data science community.
I saw thousands of people following Analytics Vidhya religiously. I saw people looking up for guidance in our meetups and hackathons. I saw people transitioning their careers because of the resources we provide them. That is when this good internship transformed into a mind blowing experience.
That is the day I decided that this is my calling. It just felt that this is what I would want to do daily.
Why create this learning path?
Among various resources on Analytics Vidhya, learning paths are special. The amount of effort and thinking they need is tremendous. The number of drafts they undergo is mind-boggling. But, the kind of impact they create for our audience is HUGE. That is why I decided that I will create a learning plan for 2017 for all our followers.
We created a similar plan for 2016 and we saw transitions happening by people following this learning plan. This time we have created a much granular and a more detailed learning plan. The sole aim behind creating this comprehensive plan is to create a much bigger impact for our followers this year.
Who should use this learning path?
This learning path would be extremely useful for any one who wants to learn machine learning, deep learning or data science in this year. If you plan to wait for a year, we will publish something similar in 2018 as well 
But, for the people looking for action this year, this framework and plan of action should be extremely useful. Whether you are a complete fresher or a transitioner or you are looking to up-skill yourself, this plan should give you the necessary direction.
We published a similar plan in 2016 and we saw followers making transition by simply following the plan. This year’s plan is more nuanced than last year’s one – so if you plan to pick up / improve data science skills – this plan will guide you through the journey.
How can you use this learning path?
In creating this plan, we have removed the confusion from the process of learning. The biggest challenge which people face while learning is not dearth of learning material – but too much of it. You are not sure where to start learning, what to practice, how much time to spend on a concept, where to get the useful resources etc. For most of the beginners, this becomes overwhelming and they simply drop out before even learning a single skill.
This plan takes this confusion out. This path contains both theoretical resources as well practical examples. We have also provided you with resources / tests to apply your learning and benchmark yourself. As part of this plan, you will apply the concepts you learn on real-world problems and gain hands-on experience.
Table of Contents
- A few definitions before we start
- Setting a target and timelines for yourself
- Beginner’s Path for 2017
- Transitioner’s Path for 2017
- Intermediate’s Path for 2017
- End Notes
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