Prateek Agrawal Apr 18, 2026 No Comments
A few years ago, enrolling in a data science program almost guaranteed a job. But in today’s evolving landscape, the question has changed.
In 2026, the real question is not whether data science is in demand—it is whether a data science course in 2026 will actually deliver meaningful ROI for your career.
Let’s break this down across three key dimensions: ROI, salary, and long-term career growth.
Before evaluating whether a data science course in 2026 is worth it, you need to understand one major shift.
Data science hasn’t declined—it has matured.
Companies today are not hiring people who just know tools. They are hiring professionals who can use data and AI to drive decisions.
What has changed:
This means that simply completing a data science course in 2026 is not enough—you need to bring real-world value.
Let’s address the most practical concern—earning potential.
The average salary is around ₹10 LPA.
However, completing a data science course in 2026 does not guarantee these numbers.
Your salary depends on:
A certificate alone does not create value—execution does.
Let’s evaluate the ROI of a data science course in 2026 in practical terms.
A well-designed data science course in 2026 offers:
The key is not the course—it’s how you leverage it.
One of the strongest arguments for a data science course in 2026 is long-term career flexibility.
A data science course in 2026 is not just about a job—it is a foundation for the AI economy.
Let’s be direct.
A data science course in 2026 is NOT worth it if:
But it is worth it if:
This is the difference between:
₹4 LPA candidate vs ₹15 LPA candidate
A common concern is whether AI will replace data scientists.
The reality is different.
AI is:
Companies now expect professionals to:
A data science course in 2026 should prepare you for this shift.
The future role is not just a “data scientist”—it is an AI-enabled decision-maker.
A data science course in 2026 is ideal for:
Short answer: Yes—but only if done right.
A data science course in 2026 is worth it if:
Because:
But one thing is clear:
The shortcut era is over.
The “learn → build → apply → communicate” era has begun.
If you treat a data science course in 2026 as:
❌ Just a certificate → Not worth it
✅ A career transformation tool → One of the best investments you can make
Success in 2026 is not about knowing more tools.
It’s about creating real impact with data.
Prateek Agrawal is the founder and director of Ivy Professional School. He is ranked among the top 20 analytics and data science academicians in India. With over 16 years of experience in consulting and analytics, Prateek has advised more than 50 leading companies worldwide and taught over 7,000 students from top universities like IIT Kharagpur, IIM Kolkata, IIT Delhi, and others.
Team Sep 21, 2022 No Comments
Updated on August, 2024
Data science interviews can be scary.
Just imagine sitting across from a panel of serious-looking experts who are here to judge you. Your heart is racing, your palms are sweating, and you start breathing quickly. You can feel it.
It’s normal to feel a little overwhelmed in interviews. But here’s the good news: You can overcome this fear with the right preparation.
In this blog post, I will guide you through the essential steps and useful tips for data science interview preparation. This will help you walk into the room feeling confident and positive.
But before that, let’s first understand this…
The simple answer is data science interviews can be challenging. You need to prepare several different topics like data analysis, statistics and probability, machine learning, deep learning, programming, etc. You may have to revise the whole data science syllabus.
And these technical skills aren’t enough. You also need good communication skills, business understanding, and the ability to explain your work to business stakeholders.
You know the purpose of a data science interview is to test your knowledge, skills, and problem-solving abilities. If you haven’t brushed up on your skills recently, it can be a lot of work. So, let’s start from the beginning…
As I said earlier, preparation is the key to success in data science interviews. And it all starts with a strong foundation that involves:
If you don’t have these, you can join a good course like Ivy Professional School’s Data Science Certification Program made with E&ICT Academy, IIT Guwahati.
It will not only help you learn in-demand skills and work on interesting projects but also prepare for interviews by building a good resume, improving soft skills, practicing mock interviews, etc.
Besides, you will receive an industry-recognized certificate from IIT on completion of the course. This will surely boost your credibility and help you stand out in the interview.
Now, I will share some tips for data science interview preparation that have helped thousands of students secure placements in big MNCs.
These tips will boost your preparation and help you understand how to crack a data science interview like a pro.
This is the first and most important thing to do. Why? Because it will show the interviewer that you are serious about the opportunity. It will also help you provide relevant answers and ask the right questions in the interview.
All you have to do is go to the company’s website and read their About page and blog posts to understand their products, services, customers, values, mission, etc. Also, thoroughly read the job description to understand the key skills and responsibilities.
The goal is to find out how your knowledge and experiences make you a suitable candidate for the role.
Your resume is your first impression. It helps you stand out, catch the interviewer’s attention, and show why you are the right fit for the job. So, you have to make sure it’s good.
What do you mention in your resume? Here are some of the important sections:
Here’s the most important thing: Tailor your resume according to the company’s needs, values, and requirements. That means you should have a different resume for each job application.
What projects you have worked on is one of the most common areas where interviewers focus. That’s because it directly shows how strong a grasp you have over data science skills and whether you can use your skills to solve real-world problems.
So, go through each project you have listed in your data science portfolio. See the code you wrote, the techniques you used, the challenges you faced, and the steps you took to solve the problem. You should be able to explain each project clearly and concisely, from the problem statement to the results you got.
Technical interviews are where the interviewer evaluates whether you have the skills and expertise to perform the job effectively. For this, you need a solid foundation of the latest data science skills.
You should revise all the tools and programming languages like Excel, SQL, Python, Tableau, R, etc., which you have mentioned in your resume. Besides, go through the core concepts like data analysis, data visualization, machine learning, deep learning, etc.
Pro tip: Learn from the data science interview experience of people who have already cracked interviews and secured placements. For instance, this YouTube video shares the experience of one of Ivy Pro’s learners who cracked the interview at NielsenIQ:
I can’t emphasize the importance of this step. Being prepared helps you answer effectively and make a lasting impression.
So, find common questions asked in data science interviews and prepare clear and concise answers. Here are some technical and behavioral questions:
These are just examples. You can do your research or ask professionals in your network to find the most common questions. This will surely make you more confident about your data science interview preparation.
Albert Mehrabian, a professor of Psychology, found that communication is 55% body language, 38% tone of voice, and 7% words only.
So, while your technical skills and experience are important, your body language can make or break your chances of success in the interview.
Here are simple ways to improve your body language:
Your body language shows your confidence and attitude, so try to make it perfect.
Mock interviews can boost your data science interview preparation. It helps you improve your answers and body language, increase confidence, and get used to the scary interview environment.
You can simply practice it with your friends or do it alone by recording yourself while you speak. But the best way to do it is to join a course where they let you practice mock interviews.
For instance, Ivy Pro’s Data Science Course with IIT Guwahati helps you practice mock interviews and learn soft skills. This way, you get feedback to understand your strengths and areas of improvement.
Now, you know how to prepare for a data science interview and crack it with confidence. You need to build a strong foundation in relevant skills, gain hands-on experience, and create a compelling portfolio. Your technical expertise, body language, and attitude are what will help you stand out and land your dream job. So, get started with it. The stronger the preparation, the more your chances of success.
Prateek Agrawal is the founder and director of Ivy Professional School. He is ranked among the top 20 analytics and data science academicians in India. With over 16 years of experience in consulting and analytics, Prateek has advised more than 50 leading companies worldwide and taught over 7,000 students from top universities like IIT Kharagpur, IIM Kolkata, IIT Delhi, and others.