T5E’s Placement survey 2022-23 was conducted during February 2023 to study the statistics of the Placement season of 2022-23. The survey witnessed a total of 256 responses across the entire graduating class (UG+PG). The respondents spanned across various degrees (albeit disproportional) and departments who appeared for the placement season. Close to 75% of the respondents were UG’s (B.Tech + DD), and the rest were PG’s (MSc+M.Tech+MBA+PhD+MS)
Note: The correlations found in these articles are from the inputs of the sample size of the number of respondents, although it may or may not reflect the entire placement statistics. The figures for CTC are representative, and are based on the responses that were garnered through the survey. For a more detailed breakdown, please refer to the report released by the Placement Team.
The survey focused on several aspects, such as Preparation, Opinion, Academics, and Career, relevant to the placement statistics of respondents.
Well over 85 percent of respondents got their Pre-Placement Offer through the Institute portal, Almost 90 percent of them worked for the company as interns for two months before they received the offer.
The median CTC offered for PPO respondents is 31 LPA. The median stipend received by them during their intern phase is 1 Lakh per month. Fifty percent of the offers were of profiles Software development and Data Science related.
Median CTC of the respondents who secured jobs Off-Campus is 14 LPA. They learned about the job openings through LinkedIn, Referrals, and Company Career Portals.
More than half of the respondents were from the profiles Quant and Finance, Consulting, etc.
Over 60 percent of respondents agreed that number of internships had a significant impact on placements. As seen from the graph, there exists a direct correlation between number of internships and the CTC obtained during placements. Seems like the sweet spot is three interns before one sits for the placements.
Through the lens of the graduands, extra-curriculars were found to be predominantly useful as talking points during the interviews. Only 30 percent felt that taking diverse extra-curricular activities might get them better placement opportunities.
Around 65 percent of the respondents who were part of CFI felt that their PoRs contributed the most to their placements, followed by Inter IIT Contingents with 48 percent. These numbers dropped for Shaastra (43 percent), Saarang (35 percent), and E-Cell (23 percent). Interestingly, the Internship and Placement team benefited a lot from this, having a staggering percentage of 90, indicating their closeness to the placement scene helped them prep before they were part of the game.
Short Advice, if you are starting from scratch
Here is some valuable advice from the graduates to the gonna-be placement batch.
- Get started with DSA and practice like there’s no tomorrow if you aren’t already
- First, learn one programming language properly, then learn other libraries from it.
- Practice coding daily, participate in coding contests not to win, just to know how the questions will be, and concentrate on graphs, trees, dynamic programming, etc.
- Start with DSA, then only learn languages
- I advise you to take the course from Algozenith, which helped me soo much. The collection of problems here is too good.
- Do Insti courses, esp from the CSE department
- Learn from neetcode.io
- Choose Python if you’re a complete beginner. Go through the entire DSA in a high level in a week or two and start solving problems. Do Codeforces contests and try to bring yourself to a level where you can solve A, B, and C questions consistently in the first 1 or 1.5 hours of a contest.
- Do leetcode after learning the language basics
- Make consultancy your primary target only if you have a stellar profile. If not, focus more on adjacent profiles like PM and BA, which would have a similar prep to tier 2 consulting companies.
- Network and gain experience through internships and volunteering, and Develop your communication skills and ability to think critically and analytically. Go through the “case in point ” at least once.
- Don’t go all-in on the consult profile. Prepare your resume well. Starting case prep after the resume shortlist or after consulting sl results is a good time frame, so you need not worry if you haven’t prepped case-solving before
- Start your preparation right from 2nd year otherwise, you are not going to get the top-tier companies
- Study Victor Cheng
- Have good PoRs
- Do case studies once a week
- Focus on basics like EDA before diving into the analytics part and coding. Start practicing DSA a year before placements.
- Finish 50 challenging problems, Heard on the Street etc. Practice puzzles from GFG and brainstellar.
- Start with Excel, be perfect in that; you can then look at ML/DS
- Start doing some projects and use all the skills that you have acquired from the online courses
- IDDD DS electives are helpful
- Practice more aptitude questions, especially arrangements and data interpretation problems.
- Should work on at least 3-4 datasets and have a good knowledge of pandas before deep diving. Be very proficient in probability, statistics and ML, and DL.
- Get inspiration about ML. NPTEL ML course will give you a strong ML mathematical foundation.
- Internship in Data Analytics, including Python data frame manipulation, EDA, and model building, will greatly help. If you don’t get a good company internship, a good internship from a Startup will also help. For e.g., I did a DS intern related to stock price prediction based on news articles using NLP in a small startup.
- Analytics Vidhya is a good website for prepping for ML theory questions that are asked in tests/interviews.
Courses that are helpful for Finance based roles
- Accounting Finance for Engineers (Insti Course), some CFA L1 topics might help
- Python for Finance MS3610: Accounting and Finance for Engineers, Guided projects on Coursera: Portfolio Management using Markowitz Model/ Risk Management
- Principles of Economics, Money Banking, and Financial Markets
- Download Zerodha Varsity.
- Probability, statistics
Short Advice for Finance Aspirants
- Don’t rely on this profile. Do coding well to have a solid backup
- Start reading Economic Times and keep a note of current affairs at all times.
- Focus on statistics and probability more than finance itself. Solve a lot of puzzles and get familiar with them.
- Try to have a finance intern
- Start quant preparation early.
- Take the course and watch the videos from Think, a channel on YouTube that helped me so much
- Focus on coding. Honestly, most fin roles need you to clear a coding test, too, except trading roles. Ensure you don’t lose out because you’ve never coded.
- PM involves a lot of lateral knowledge in various skills than deep expertise in a specific one. So early on, try doing internships/projects in SDE, design, and data analytics to build a foundation before prepping for PM.
- Join the Product Design Club IITM
- Getting a basic understanding of PM, PM school, product camp, and product space are some resources u could check out. There are boot camps like doremon den, next leap that also helps
- Make a deck. Participate in some competitions to get a feel of how to make a deck.
- Observe the products around u, think of features to improve, or think of a new app u could launch to address some pain points. Keep brainstorming on ideas abt the products u use on a daily basis, discuss it with your friends, and help u get the hang of things.
- Read about PM or be part of cohorts
- Highly recommended to do at least one product internship (APM or analytics role) at a good startup. Depending on interest, do consider joining paid programs of NextLeap/Upraised or unpaid cohorts of The Product Folks.