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Interview With Lalit Garg – A Chartered Data Scientist from Mechanical Engineering Background

Lalit Garg is amongst those top candidates who qualified for CDS. Analytics India Magazine got in touch with Lalit to know more about his experience of writing the examination and being a CDS charter holder.
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Chartered Data Scientist™(CDS) is one of the most prestigious distinctions a data science professional can have. This distinction is given by The Association of Data Scientists (ADaSci), a premier global professional body of data science and machine learning professionals. The candidates need to crack a rigorous exam in order to achieve this distinction. The qualified candidates demonstrate a thorough understanding of advanced analytics and data science skills.

CDS examination is a global standard exam to test the 360 degrees of the skill-sets one has. Lalit Garg is amongst those top candidates who qualified for CDS. Analytics India Magazine got in touch with Lalit to know more about his experience of writing the examination and being a CDS charter holder. 

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AIM: Could you tell us about your professional and educational background?

Lalit: I completed my graduation in Mechanical Engineering in 2003, and since then, I have worked in different industry verticals like Manufacturing, Construction, Oil and Gas, Garments and apparel, Finance and IT. My Techno-Functional profile has enabled me to handle different kinds of problem-solving for different industry verticals. Since then, I have worked on at least 10+ different ERP Projects across India and overseas.

That has helped me to develop a strong understanding of business domains for various business functions/processes like Enquiry to Order, Order to Cash, Procure to Payment, Hire to Retire, and Records to Reports across different industry verticals, as mentioned above.

My job as a project manager is to handle triple constraints of Scope, Schedule and Cost from both sides (Client and Partner). Also, I am well versed in project management methodologies like waterfall and agile. Currently, I am handling a team of talented professionals and positioned as Project Manager for Digital Transformation through ERP, Analytics and BI Projects across India and Overseas.

AIM: How did your career begin in the data science field? 

Lalit: In typical ERP projects, there is a lot of data generated through transactions in the system. When I came across the ERP applications during my career, it fascinated me to jump into the data science field. Here my interest in the field and my career began. I came across different use cases of data captured using ERP tools and worked on generating many exciting results that are used by the organisation to add many more values to the business.

AIM: What were the initial challenges you faced in the field? How did you overcome them?

Lalit: As a mechanical engineer, I have not learnt coding as a subject or as a profession. In any data science project, you should have 3 areas to look at predominantly — Domain Knowledge (Business Function – What business requires), Statistics (Looking at the data and doing basic statistics around it) and computer programming (Coding). Even if you do 2 areas better, it’s fine because, anyways, it’s teamwork and not an individual project.

I started learning coding by Excel VBA programming and understood how object-oriented programming works. Learning coding was definitely not the easy part for me, but it’s not that difficult also. Consistent efforts over a period of time and practicing the same has helped me to overcome the coding constraints as well. Transitioning from a non-coder background to this level itself is a challenging journey altogether, and I have overcome all these challenges.

AIM: How did you come to know about the CDS™ examination? What motivated you to take the CDS?

Lalit: I came to know about CDS through the news by Analytics India Magazine around 2020. Along with that, I was continuously looking for the best exams/certifications in the data science field so that I could get recognition for my skills. After much analysis and advice from experts, I found CDS to be suitable for me to test my skills and knowledge.

What has motivated me to take this exam is to differentiate myself from the rest of the crowd with a very high distinction and test my skills and knowledge in this domain through this rigorous exam. It also tests you, your patience, time management skills, commitment to your profession also along with technical understanding of the subject matter expertise.

AIM: How did you prepare for the exam? How many hours did you dedicate each day to master the domain? How long did it take to prepare for the exam?

Lalit: As it is a self-study program, it requires a lot of commitment and dedication to complete the same. So I prepared my schedule in an excel sheet first and divided each topic area into some days and weeks to cover. After that, I did forward and reverse calculations based on the volume of content to study as per their weightage. 

As I had already covered a lot of syllabi as a habit of learning, I just needed some more time to get myself comfortable with the topics as per the exam content outline. So for me, it’s a journey altogether, and 6 months final touch-up was a required timeline for me to get the confidence to take this exam. But it can vary from person to person.

Also, I made sure that if I am not covering the syllabus on a daily basis, at least I should meet the weekly target by managing the time. I followed a daily routine of at least one hour for five days as a five-hour weekly rule.

AIM: What books and other learning resources have you followed in your journey to prepare for CDS?

Lalit: I started with the CDS Candidate Guide provided by ADaSci to get more information about the CDS exam. There are several free resources and books available to download from the ADaSci website as well. Once you register for the exam, you can refer to the CDS – Book of Knowledge also. ADaSci also has released video lectures related to course content as part of the CDS registration process. So, there is enough learning content on the ADaSci portal itself.

Along with these, I followed MOOC platforms like Coursera, Edx, and Udemy for course-related content, and it was a mix-and-match from different sources. Also, I followed a lot of documentation on the internet related to the particular topic. 

Certain books can really help you, like Hands-on Machine learning using Sci-Kit Learn and TensorFlow by Aurelien Geron and Deep Learning with Python by Francois Chollet, to get the Machine Learning and Deep Learning fundamentals. I recommend these two books if you are fond of reading and reading excites you a lot.

AIM: What was your strategy for cracking the exam? During the exam, how did you manage your time across different sections?

Lalit: The strategy was very simple. I just focused on my core competency areas like deep learning, Business Analytics, Computer Vision, Natural Language Processing, Python and R, and Statistics, where I realised that I can really do well. During the exam I found questions from these concepts really standard and easy to moderate in difficulty levels.

Before taking the actual exam, I had taken a lot of mock exams also, like there is a sample question set already provided by ADaSci. There are mock tests available on MachineHack. Practicing them before taking the actual exam gives you a flavour of how it is going to be in the exam. I suggest interested candidates look at those mock exams and feel how real an exam environment can be. 

The only strategy is not to panic even if you don’t know the answer, it’s ok. The exam is based on the percentile method and not the percentage method. So relatively, you have to do better than others. 

Always try to use the elimination technique so there might be 1 or 2 options which are totally out of context, and then focus on the rest of the options. Since there is no negative marking, just park the question if it’s not readily answerable, and then you can revisit it again if time permits.

Regarding time management, I just focused on completing the number of questions per minute. You need to answer 150 questions in 180 minutes. So ideally, in the first hour, you should be able to finish 60 questions which you have to identify as per your comfort subject area. The exam may surprise you with a mixing of questions also from one area to another area so be mentally prepared for that as well.

AIM: How has your experience been after becoming a Chartered Data Scientist? How do you think CDS will help in your professional journey as a data scientist?

Lalit: Well, it was a great feeling, of course, especially when you clear the exam on the first attempt itself. First of all, I did not believe it, but gradually I realised that it’s a reality. 

The journey has been quite beautiful altogether, and the experience was amazing, especially when you are preparing for the long-term exam where competition is there. The area is very vast, and we have to cover a lot of content to consume and that too in depth.

Also, it asks for industrial practical experience of 2 years in a similar role, which reflects your knowledge and experience not only theoretically but practically also. Any Charter comes with a lot of responsibility/accountability also, so we have to follow that code of ethics and character shown throughout the charter, and it’s also one of the primary reasons I chose to become a chartered data scientist.

CDS has made an impact in my life, and the charter itself speaks a lot about its bigger responsibility towards your people, employer, society and country at large. We become more responsible and take that responsibility towards our duty and profession, and that is what makes an impact on our job and career.

AIM: How was your overall CDS program experience? What would you like to tell the data science community about the CDS program? What are your thoughts on a career in the data science field and how CDS can help a professional?

Lalit: My overall CDS program experience was really awesome. Starting from downloading the CDS content exam guide to the preparation for the exam and finally becoming a chartered one, it’s become like a dream come true for me. I would really like to thank the whole community and the Association of Data Scientists for providing me with the opportunity to become a chartered data scientist. 

In my opinion, CDS is not just another exam, there are a lot of data science-related courses and certifications in the market, but when you become chartered, you carry a sense of responsibility and commitment to this profession, and that is where this exam differs from others and unique in its own approach.

Not everyone can be provided chartered unless you pass those stringent criteria. Of course, your technical and professional experience will also carry weightage, but when it comes to using AI responsibly for the betterment of humankind, that is where differentiation happens.

Every exam will test you in some or other skills (technical/managerial), but CDS will test you through patience as well, including the above. Because of its rigorous scope and curriculum, you might lose your patience while preparing for it, but that’s where the game is. I also have waited patiently for almost 2 years, but patience has its own rewards as well.

So, in my opinion, CDS can help you become a true professional in the data science field by testing you in subject matter areas, your soft skills, your patience and your attitude towards handling a problem and situation in real life. Don’t think it’s just another exam. CDS is a designation which can be awarded to individuals. It can help you become a better person/professional, and the world needs many of them.

Good luck and all the best. Happy learning.

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Dr. Vaibhav Kumar
Vaibhav Kumar has experience in the field of Data Science and Machine Learning, including research and development. He holds a PhD degree in which he has worked in the area of Deep Learning for Stock Market Prediction. He has published/presented more than 15 research papers in international journals and conferences. He has an interest in writing articles related to data science, machine learning and artificial intelligence.

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