How Ashutosh Got an UpGrad and Transitioned to Data Science

This article was originally published by Ashutosh Agrahari (UpGrad Data Science Program Alumnus) on LinkedIn Pulse

I am a Data Analyst working in Gain Theory, a WPP company based in Bangalore. Right after doing my M.Tech in Computer Science from Pondicherry University, I joined TCS. There I worked as an analyst in the testing domain (manual testing). After completing more than 1.5 years in the software testing domain, I was very uncertain about my future. My job role didn’t match my educational qualifications nor my research work in soft computing. So, I started looking out for re-skilling opportunities in advanced data analytics techniques with open source programming.

I came across many online data science course with fees varying from INR 30,000 to 5,00,000.

I researched for around 2 months; conducting a detailed analysis of all the courses available in the market. Then, I decided to enroll in the UpGrad program due to the course structure and affiliation with IIIT-Bangalore. The decision to choose UpGrad wasn’t easy as it was the first batch and did not have a detailed course review.

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The UpGrad course structure is very well suited for people who don’t have experience in statistics and data analysis using R programming. Here, I learned the basics of statistics as well as advanced data science techniques. We had several webinars with industry experts along with the weekend online classes from IIITB Professors. I learned the real implementation of analytics in Industry and bridging concepts and their implementation gap. Each topic had an individual case-study and a group case study which helped me understand the solution in multiple ways. UpGrad has an excellent student support team as well, who was always ready to resolve issues related to the program.

How Ashutosh Got an UpGrad and Transitioned to Data Science video calling UpGrad Blog
There were times when I used to spend around 4-5 hours a day, along with 9 hours office time, studying. I was spending around 20 to 25 hours a week on this course. The course was rigorous, we had to submit the case studies in a short time. It helped me to learn fast and implement learnings from our real industry projects, in a smarter way.

My transition as a data analyst wasn’t easy. 5 companies interviewed me before  I got selected by Gain Theory. I faced many problems in interviews and many concepts that I had learned in analytics I was unable to explain mathematically to the panel. Most interviewers were keen to know the mathematical and statistical concept behind an algorithm and not just the usage of R command to run a model. So, I started to focus on mathematical concepts, which helped me to secure the job at Gain Theory after 6 rounds of interviews including one case study.

Currently, I am working in an R&D team for product development for Market Mix Modelling using cases in marketing analytics. We have been able to build the model for 1000 variables with a different kind of regression model like OLS fixed effect, mixed effect using the Shiny web app for UI design.

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All data science enthusiasts should have knowledge of data management, data analysis, statistics, business domain and especially the interpretation of model results. UpGrad’s team, along with IIITB professors, are excellent in their approach. I think people in the IT industry should think about the future of IT after 5 to 10 years where every decision maker will use data. Machine Learning, Automation and IoT will all require data, which is the future. We need to upgrade ourselves to be relevant in the industry with data science and analytics as the next big move.

The UpGrad team has been extremely helpful throughout the course. I really appreciate their effort in delivering quality and value to the course. Their career support team is also very efficient. They provide enough support for interviews, including personalized support for interview preparation, resume formatting, etc. I really thank UpGrad for helping me in my transition as a data scientist.
Everybody should make their own path to achieve their dream. Sometimes all it takes is a little help from others who have been through the same to save added time and effort.

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What is the course structure for Data Science?

The Data Science programme is structured to assist students in gaining business knowledge as well as utilising tools and statistics to address organisational difficulties in the near future. Whether you’re looking for a Data Science Curriculum for beginners or specialists, a general Data Science syllabus followed by most of the universities has 4 main components namely Big Data, Machine Learning, Business Acumen and Artificial Intelligence and Modelling in Data Science.

Can a non-data science person land a role in data science?

It may be challenging but it is entirely possible for a non-data science professional to transition into data science. You need a good foundational knowledge of statistics because most machine learning concepts and data science use cases involve statistics. You will need to upskill yourself with programming languages and SQL, NoSQL etc, learn linear algebra fundamentals and data manipulation. It is also a good idea to take up a foundational or short term course in data science to get a comprehensive overview of the discipline.

Once you have a basic understanding of programming, you can start by taking up projects via courses or platforms. It’s also advisable to join collaborative projects. Start building your network in the data science domain and applying for opportunities through job portals and LinkedIn. You will be able to find a footing in a data science career soon.

Which are the best companies hiring Data Scientists in India?

There are various companies in India that are suitable to collaborate with for Data Science projects. These businesses are proud of their target industry, work culture, welcoming workplace, and diverse initiatives that expose employees to a variety of tasks, allowing them to advance their careers. Some renowned companies to work for Data Science are Cartesian Consulting, bridgei2i, Fractal Analytics, Oracle Cloud Solution Hubs, Accenture Analytics, Crayon Data, Datalicious, IBM, Wipro Ltd, Amazon, LinkedIn, Deloitte, Flipkart, HCL and many more.

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