Kunal Jain — Updated On July 26th, 2020
Beginner Business Analytics Learning Path Python

We are jumping on our feets right now!

We can’t find any other way to express our excitement. We said that 2015 is going to be a year when Analytics Vidhya will become the place to learn analytics and data science. We launched our discussion forums 2 weeks back and there are awesome discussions already happening there. Check them out here to see what you are missing.

Learning path

Today, we launch another milestone in data science learning – the learning paths. The aim of creating these learning paths is to take out the confusion from learning process.

Why create learning paths?

We live in a world of information overload. We come across people daily who are following too many things and chasing too many directions in their attempt to learn data science. It is hard to blame them, when there is so much content to absorb. These people start doing a MOOC – 2 videos down the line, they switch on to a blog, then a notebook and end up reaching nowhere.

These learning paths will provide crystal clear direction to your learning so that you can focus on learning the subject rather than worrying about what to learn. If you are a complete beginner on a topic, you couldn’t have asked for a better roadmap – you will find the entire learning journey mapped in front of you. If you are some one who has already spent some time learning – you can pick up the journey from where you are and the remaining journey should be faster, clearer and more focused!

Our first Learning path – Python for data science

The first learning path which we are launching is on Python for data Science. The learning path starts from why you should learn Python and goes on to provide the resource you need to become a Python machine learning expert! The Python learning path consists of 8 steps:

  1. Setting up your machine
  2. Learn the basics of Python language
  3. Learn Regular Expressions in Python
  4. Learn Scientific libraries in Python – NumPy, SciPy, Matplotlib and Pandas
  5. Effective Data Visualization
  6. Learn Scikit-learn and Machine Learning
  7. Practice, practice and Practice
  8. Deep Learning

If you are completely new to Python, you should just follow the steps as mentioned in the path. On the other hand, one of my friends has already learnt the basics of the language – he can directly pick things from step 3 onwards. If you already know Python and want to pick up machine learning, start from step 5 or 6.


End Note:

We are super excited about launching learning paths. We think that these should help our readers immensely. So check out the learning path and let us know how you plan to use them. There will be more learning paths, we will add in coming days. If you have any suggestions on this awesome initiative, please feel free to reach out to me and shout in the comments below.

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About the Author

Kunal Jain
Kunal Jain

Kunal is a post graduate from IIT Bombay in Aerospace Engineering. He has spent more than 10 years in field of Data Science. His work experience ranges from mature markets like UK to a developing market like India. During this period he has lead teams of various sizes and has worked on various tools like SAS, SPSS, Qlikview, R, Python and Matlab.

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11 thoughts on "Launch of learning path – Data Science in Python"

Tesfaye says: January 14, 2015 at 9:42 am
Dear Kunal, Thank you for clearing the fog out of the way. One can now see where he is driving without headlights on. One thing to ask: can you clear the path using R the same way as Python? thank you. Reply
Raju Kommarajula
Raju Kommarajula says: January 14, 2015 at 11:14 am
Hi Kunal, I am also learning Data Science with Python. Reply
Kunal Jain
Kunal Jain says: January 14, 2015 at 6:08 pm
Tesfaye, Stay tuned, the one on R is on its way along with a few others! Regards, Kunal Reply
Kunal Jain
Kunal Jain says: January 14, 2015 at 6:08 pm
All the best. Hope this path would be useful Reply
Nikhil Goyal
Nikhil Goyal says: January 14, 2015 at 6:44 pm
Hi Kunal, Great Idea. Very useful. Congratulations on the launch and best wishes ! Reply
Praveen says: January 15, 2015 at 1:56 am
Good initiative.I started following your blog and find that the contents are in easy to understand language with examples and applications Reply
Divyum Rastogi
Divyum Rastogi says: January 15, 2015 at 7:53 pm
Hi, Thanks for the blog. They are really helpful and fun to read. My question is, I am a beginner and have tried kaggle for practicing, but frankly speaking its quite difficult for beginners like me to get hands on kaggle. Can you suggest some resources (or dataset or any other source) from where I can practice data science and learn how and where to apply an algorithm or any worked out examples. Reply
Pankaj Singh
Pankaj Singh says: January 16, 2015 at 5:06 am
Thanks Kunal for sharing this great idea. Really this will help me to update with different tool and language. Reply
mukul says: January 19, 2015 at 8:43 am
Dear Kunal Small and a short question . i am part owner of a SEO firm . We wish to add Analytics to our services . i have 20 years of exp in manufacturing and solar power etc . i am an Engineer . DO u think itwould be good to start from Google analytics and then progress to Web Analytics ,Sicne we are getting lot of work for Google and Data Analysis . Our compnay is based in Delhoi and Bangalore . Cannot find a good trainign academy here which does classroom courses . Any suggestions? Could we talk over phone ? my nos is +919810090449 Reply
Kunal Jain
Kunal Jain says: January 19, 2015 at 5:53 pm
Divyum, Kaggle is difficult, if you want to start competing today. But, if you approach it step by step, start by following Knowledge competitions. Once you get comfortable with it, then you should start competing on some competitions. Take help from various communities and you will be good. Regards, Kunal Reply
aadon says: March 01, 2015 at 5:42 pm
how do you audit the machine learning course at edX? Reply

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