How I cracked my Data Science Interview

Experience of IIT Kanpur, one of the prestigious colleges in India

Aayush Ostwal
Analytics Vidhya

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Source: https://www.quora.com/How-does-IIT-Kanpur-looks-like-Can-you-share-some-pictures

Brief Introduction to my Background

I am a final year undergraduate at the Indian Institute of Technology, Kanpur, in the Department of Mechanical Engineering and Minors in the Department of Industrial Engineering and Management.

You may find it interesting that belonging to a core field, how I land a job as a Data Scientist.

In the campus placement season (Dec 2020), I got placed as a Data Scientist at HiLabs. HiLabs has a healthcare-focused AI solution that automatically detects data errors without human intervention. It is a combination of Big Data, AI, and medical cosmologies.

How I landed there?

The story behind how I landed as a Data Scientist is quite long. It has many layers and chapters. And every phase is equally contributing to letting me into this job.

I bet that you will find every chapter interesting and inspiring.

Chapter 1: The Begining Phase

Credits: Marek Piwnicki

In summer 2019, I enrolled in a course- Data Mining and Knowledge Discovery, which was the first step towards my goal. I enjoyed that course, and during that, I came to know that I want to be a Data Scientist.

After that, I opted for a course on Udemy, which taught me python, the basic syntax for machine learning, the intuition behind ML algorithms. This course also includes hands-on experience on popular data sets like Titanic and Iris.

It was also my first experience in data exploration using matplotlib and seaborn. The graphs were fascinating every time I plot them.

Chapter 2: I was a NOOB!

Credits: Anthony Tran

That I knew all the primary syntax, I was ready to solve simple predictive modeling problems. So, I went to Kaggle Team. I was sure that I can solve any predictive modeling problem now.

But, when I looked at Kaggle, I was shocked. All the problems that I was deciphering, were very advanced. I was not able to solve a single problem.

After wasting a month, I realized that I need some more knowledge to become a data scientist.

Chapter 3: The golden Lockdown

Credits: Martin Sanchez

During the lockdown, Linkedin was full of certificates. Every single person had done some courses. During the first four weeks of lockdown, I enhanced my competitive coding skills on InterviewBit and GeekforGeeks.

I almost had a streak of 40 days or so on InterviewBit.

After that, I did some online training (paid) in Data Science, which focused on approaching a predictive modeling problem. It was statistics-heavy training. It includes new concepts like Inferential statistics and the student T-test.

Again I felt overpowered and went to Kaggle. But soon, I came to realize that the problems are more intricate now. So I looked for an alternative to Kaggle, which provides some straightforward problem statements. And guess what, I found it!

It was Team AV. Lots of hackathons are available and of varied range. Simple predictive problems, image classification, text, and sentiment analysis… all in one.

I started working on some projects persistent with some courses on Deep learning on Coursera. I took three courses describing ANN and CNN. Also, participated in three hackathons.

Chapter 4: The Internship

Credits: Scott Graham

Internship played a vital role in my journey. It was a startup of IIT Delhi.
Its mission was to combine machine learning and existing knowledge tree to help students learn at their own pace. This idea is called Adaptive Learning.

I learned new things that made me stronger. I was then more confident. I analyzed data using python, plotted various graphs using seaborn and Matplotlib. Also, read the abundant research papers searching solutions for our clients.

It was a three-month-long internship, and I was paid nothing but only experience. For any fresher, experience, this is the best stipend.

Chapter 5: The Placement Preparation

Credits: Green Chameleon

Making a Resume is not only the task during placements. All of the candidates can make a decent resume. But if you want to get hired, you need to do a little more.

I wanted to pursue my career in Data Science. So, I recapitulation Probability, Statistics, Machine Learning (Algorithms, cost functions, evaluation metrics), Deep Learning, Computer Programming, and Mathematics.

Also, I followed some youtube channels that provided me the theoretical concepts behind the algorithms.

Youtube Channels that I followed:

Krish Naik
StatQuest with Josh Starmer

Chapter 6: The Interview Preparation

Credits: Steve Halama

Even if you have done all the required courses with great decency, the Interview needs some extra preparation.

And these are the preparation of HR questions.

Describe yourself!
Why you?
Why we, not others?
Your Strength and Weakness?
Situation where you make tough decisions?
What’s your philosophy of life?

You need to prepare these questions very well and also prepare every single line of your resume.

Youtube Channel For HR:
Prepleaf

Chapter 7: The EndGame

Interviews!

Credits: Ravi Palwe

The final game involves your patience, confidence, and positive attitude. Be relax and do not panic if you are not selected in any company. The placement drive is a long game, each day gives as many interviews as you can.

Not everybody comes first.

The END

Credits: Markus Spiske

Lastly, I would like to say that all the chapters were very interesting for me, and I hope for you too. It was a very tedious and exhausting period of my life. But I enjoyed it!

Please share your views, I would like to hear about your journey too!!

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Aayush Ostwal
Analytics Vidhya

AI Engineer at Qure.ai| Enthusiastic ML practitioner | IIT Kanpur | Drama Lover | Subscribe https://www.youtube.com/channel/UCqq_T7ktsZO62k7CaibgQvA