How to achieve multiple offers in Data Science as a College Student…


First of all, I would like to introduce myself. My name is Chitwan Manchanda and I am currently pursuing B.Tech in Mechanical Engineering from Delhi Technological University. I have offers from Simpl, Editorialist YX and Slice for Data Science roles. I was in my penultimate year when the Covid-19 Pandemic hit and we all had to stay inside our homes. At that point I had to make a choice, either I could have wasted my time by constantly binging on web-series, scrolling through Instagram the whole day, etc. or I could have utilised this time to learn something new. Thankfully, I chose the latter one.

My Learning Journey

So, I was aware of this term “Data Science” for a while now and it was always in the back of my mind to one day go for it and this lockdown period finally gave me the chance to try my hands on one of these online courses on Python from Coursera, but it was still a beginner level course and I was not much satisfied with it, it did not give me much hands on experience. So, I went to YouTube and found a few good playlists on Python for Data Science, I have listed down the links below in “Reference Materials” section. These playlists helped me get a good grasp and hands on experience with Python programming language. While python is the most basic tool required to start with Data Science, one must also have a good grasp on Machine Learning concepts and most importantly Problem Solving. For that again I found internet as my best buddy. I found this in-depth course on Data Science and Machine Learning by Coding Blocks which had this concept of Live Online Classes that allowed us to directly interact with the Instructors. These interactive sessions not only helped me understand the concepts of Machine Learning and Deep Learning well but it also taught me how to think like a Data Scientist while trying to solve a problem.

Along with these online courses, I referred to a book as well. This book is really famous within the Data Science community. It’s called “Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems” by Aurélien Géron. It is available for purchase online as well as for free in PDF format. I personally feel that it is better to go ahead with the hard copy or the physical version of the book. This book covers the Machine Learning and Deep Learning concepts along with their practical use-cases as well. I highly recommend this book. I have attached the link for the same below in the “Reference Materials” section.

I would also like to mention some YouTube channels which I referred from time to time for various concepts and their applications. These really helped me a lot and are listed as follows (not in any particular order):

  1. Krish Naik
  2. Codebasics
  3. 3Blue1Brown
  4. Khan Academy

P.S. You can follow me as well, I provide the best Data Science Content that really can help you in your career. ( Did you see what I just did there 😉 )

Anyways, another important point is while making projects one must always try to approach the problem analytically and the proposed solution should make sense as well.

So, in this section I talked about the resources that I referred and in-fact still refer to brush up my concepts and learn new things. I also talked about how to think while approaching a problem. One must always remember that the LEARNING NEVER STOPS.

In the next section, I will talk about how to get Internships in Data Science off campus as freshers (college students).

How to get Internships in Data Science

Once there is a grasp on Machine Learning concepts, Python programming language and SQL. One should start making projects and start putting up the same on their GitHubs and resumes. While preparing the resume make sure that you put the right keywords and explain the projects in brief. Along with resume focus on your GitHub profile and Kaggle profile as well. In my opinion, these fetch you brownie points. Once this exercise of resume and profile building is done start using the MOST IMPORTANT PLATFORM….LINKEDIN. On LinkedIn you will find all the opportunities that you need. LinkedIn has given me most of my opportunities and In fact, I firmly believe that this social media platform will give me my next break as well. But the question arises, how to use LinkedIn effectively? So, the answer to this question is pretty simple which I have tried to summarise in the following bullet points.

  1. Keep your LinkedIn profile up to date with all your achievements, certifications, experiences and projects. You can also put up the links of your profile from other platforms such as Kaggle, CodeChef, your own portfolio website etc. (try to be creative with this space).
  2. Make relevant connections. Make sure that you are connected with the Recruiters/Human Resource Specialists/Data Scientists/Engineering Managers from the organisations with which you want to work with.
  3. Lastly, do not hesitate to approach anybody. Do not feel shy while starting a conversation or while seeking a referral. If you will not ask you will not get. It is as simple as that.

Once you are successful in getting your desired internship you should work dedicatedly and give your 100% because this can lead to full-time offers as well. Yes, you read it right. As per my experience, companies do not offer Data Science roles directly to freshers. First you have to prove your merit by completing an internship which is generally 4-6 months long and once you have done that based on the performance a Pre-Placement Opportunity can be offered to the candidate.

So, this is how I achieved 3 Data Science offers as a fresher. I really hope, my experience could become your roadmap and provide you all the success that you desire. Please do let me know your feedback. If you like my blogposts, then please do subscribe. Thank you so much for taking out your precious time and reading my blogpost. I wish you all the very best for your career and like every time….HAPPY LEARNING 🙂

Reference Materials

  1. Machine Learning Master Course
  2. Hands–On Machine Learning with Scikit–Learn and TensorFlow – Online Purchase
  3. Hands-On Machine Learning with Scikit-Learn and TensorFlow – PDF
  4. Krish Naik YouTube Channel
  5. Codebasics YouTube Channel
  6. 3Blue1Brown YouTube Channel

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