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Placement Preparation for B.Tech Students

I have been asked from some of my friends on how to prepare for their upcoming campus selections. It is said that, if a question is asked more than twice, write a blog about it. Here I am, writing with my campus selection experience at IIT Kharagpur 2018, on a better than a random way to prepare for placements.

Campus Selections 2019-20

I am writing in particular on how to prepare for Data Science and Software Development Positions.

This is gonna be a long article with links and suggestions. I am not going in detail on why — but will be focusing on what.

The contents of this article are as follows: - Usual Procedure - Software and Analytics - Software Development - Data Science Preparation - Quant Preparation - What I have missed - CV Preparation - Some Useful Resources

Usual Procedure

  • In different colleges, the campus placement procedure could be different. In IIT Kharagpur, the placement procedure is detailed in the CDC internship and placement page. Go through your college’s placement instructions and make sure to follow them.
  • Companies usually conduct a series of pre-assessment tests and shortlist students for final interviews. The tests could be on a combination of the following topics: Domain Knowledge, Quant, Coding, Data Science Competitions, Case Students…
  • The final interviews could be in-person, phone calls, video calls or a combination of these.

Software and Analytics

I have prepared for both Software Development positions as well as Data Science Positions. Both have a few common areas which to be prepared for no matter the position.

Basic Data Structures

Prepare for the following topics — arrays, linked lists, stacks, queues, trees and basic hashing from GeeksforGeeks Data Structures. These are asked in almost every interview and are assumed that every student knows about them. Also, practice coding. You can use CodeMonk from Hackerearth for this.

Basic Machine Learning

Go through Prof. Andrew NG course on Coursera and learn about the basics of Machine Learning. This course is done by almost every student and lacking basics sure reflects a lot in the interviews. Link: https://www.coursera.org/learn/machine-learning or https://www.youtube.com/watch?v=qeHZOdmJvFU&list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW

I suggest that you complete the assignments. There are a few GitHub repositories with solutions for the assignments in Python language as well.

Few Points to Remember

  • Pick up a good programming language — Better C/C++ or Python or R or Java. Python can be used both for Coding as well as Data Science. I learnt both Python and C++. I used C++ for competitive programming and Python for Data Science. It depends on personal preference, so pick up a combination which suits best for you.
  • Few companies allow only certain programming languages in their coding competitions depending on the profile requirements. But most companies allow most of the popular languages. This also applies to Data Science competitions.
  • Most companies allow the usage of Standard Template Libraries whereas few companies don’t.

Software Development

This has a lot of fields — I will be focusing on Software Development for non-CS students.

For better results, it is suggested to start early. Few start preparing for placements way before — even from their pre-final year. Better don’t lose hope, with good planning and discipline any profile can be cracked.

Suggested Preparation

  • Go through Introduction to Algorithms from MIT OCW — gives a good understanding of algorithms.
  • Go through GeeksforGeeks and read on articles on Data Structures and Algorithms — till Graphs and Dynamic Programming.
  • Use InterviewBit and/or LeetCode to prepare for coding. Remember competitive coding is different from placement preparation and these two sites are best for placement preparation.
  • Use Cracking the Coding Interview book — the best suggestion I can give to myself.

Few Points to Remember

  • Depending upon the position you are applying for, you may have to learn — Operating Systems, Networks, Distributed Systems, Web and/or Android Development.
  • The more the better — Always applies for Coding practice. Practice as many problems as possible.
  • Download GeeksforGeeks App and read articles in popular and interview experiences sections.
  • Start working on good projects and build your GitHub profile. A lot of companies are asking for LinkedIn and GitHub links.

Data Science Preparation

The various other names for the profile are — Data Analyst, Data Scientist, Data Engineer, Deep Learning Researcher, Research Analyst among others.

I am assuming that you have enough coding experience.

Machine Learning

Complete Machine Learning Course by Prof. Andrew NG and Complete the assignments. Go through CS229 — Machine Learning Notes. They give a good mathematical understanding of the basic topics.

Link: http://cs229.stanford.edu/notes/

Tip: If you don’t have enough projects to include in your resume, use the assignments in the course and develop on them and use them as projects in your resume.

Deep Learning — Advanced Level

Go through Deeplearning.io or CS224 or CS231N courses of Stanford. Each of these courses is good and gives a good understanding of Deep Learning. Pick up either Computer Vision or Natural Language Processing and work on projects and develop your GitHub.

Data Competitions

Most of the companies are starting to go for Data Science Competitions as their initial screening tests. So better prepare for them using Kaggle or Analytics Vidhya or HackerEarth.

Few Points to Remember

  • American Express conducts AnalyzeThis every year and gives Pre-placement Interview offers for students who have performed well.
  • Learn how to document projects well.
  • Read Introduction to Statistical Learning Book for a good understanding of Mathematical Machine Learning.

Quant Preparation

This is a company-specific preparation. Few companies have mostly quant while others don’t even ask a single quant question. Go through GeeksforGeeks interview experiences and find out about the company - The type of quant questions asked depends on Companies and Profiles. - Go through https://www.geeksforgeeks.org/placements-gq/#GRP and prepare for important topics. Solve as many problems at a time as possible with a time constraint. If you feel uncomfortable in some topics, focus more on them. - Try different books and pick up one that suits best for you. - For quant — both time and accuracy are important.

What I have missed

  • I have not specified other profiles — finance, consulting, core…
  • I have not gone through company-specific preparation. Go through GeeksforGeeks interview experiences for that.

CV Preparation

  • Go through Udacity Resume Revamp course. It gives a good understanding of what interviewers look for in your resume and how to prepare a profile specific resume.
  • Colleges may allow the preparation of more than one resume — IIT Kharagpur allowed students to prepare up to 3 resumes. It is best to prepare different resumes for different profiles and apply with the one which suits best for the profile.

Some Useful Resources

This article is being updated from time to time.

credits: Cover Photo by https://unsplash.com/@nirzar on Unsplash