Presenting to you the Accredian Spotlight Budding Data Science Leader interview series. This is a series of interviews of budding data science leaders, enrolled with Accredian in different courses. These students coming from diverse backgrounds and even different fields, have rich experience in their own domains. They have interesting views to share with the world, their experience in the industry, what brought them to the field of data science and many other such interesting aspects. These interviews will enrich the readers about the insights, trends and many other related points.
In a recent conversation, we spoke to Ujjawal who is enrolled in the CDF program at Accredian.
Name: Ujjawal Gautam
Current Organisation: Accenture
Total Experience: 5.9 years
Batch: Certificate Course in Data Science Foundation (CDF) January 2019
Ankita: Ujjawal, walk me through your career journey. What has been your educational qualification and the professional experience you have? Also, tell something about your current role.
Ujjawal: I completed my BTech. in Mechanical Engineering in 2013. I started my professional journey from Congnizant Technology Solution and worked here as a Test Engineer for 3.5 years. Post this, I switched to Accenture, my present company. Here, I am working as a Test Engineering Analyst since November 2017.
Currently, I am working on a BFS project where I have to do automated scripting of manual test cases using UFT and VB script. Along with this, I have also worked on the project of mobile application, wherein I scripted manual test cases using UFT and VB script with Perfecto integration.
Ankita: Given that you are working in such an intricate profile and pursuing a course at Accredian too, how are you able to take out time to study? Do you have a schedule that you follow to balance your work and study? Ujjawal: Yes. 9:00 am-5:00 pm is the time I have reserved for my Accredian study. The Accredian session timings are from 11:00 am-1:00 pm in the morning. So, I study for two hours before and after this session on Saturday and Sunday. To be very frank, I don’t get much time to study in the weekdays, as most of my time is consumed in work and to and fro office commute. So, apart from attending the two-hour Accredian sessions on the weekend, I devote the time to self-study on the weekends. I make the most of my time on Saturday and Sunday and invest it in learning; this can be going through the learning management portal, brushing up the concepts etc.
Ankita: Now, Ujjawal if you could tell me some tools and packages in Data Science and machine learning that you have mastered so far.
Ujjawal: Python is the basic tool which is used for Data Science. This is why we have installed Anaconda navigator and we have worked on Jupyter notebook. I have also used Python packages like NumPy and Panda; data visualization packages of Python like Matplotlib, Seaborn and Plot.ly.
Along with this, I have also worked on EDA through Python and learnt some basic machine learning algorithms like Linear Regression, Logistic Regression, Random Forest and Decision Tree. Talking about packages, Scikit-learn is the one that I have worked on.
Ankita: Out of all these packages, tools and algorithms that you mentioned, which are your favorite ones?
Ujjawal: For packages, I feel NumPy and Panda are the most interesting ones because we can access the data and filter, clean and segregate it easily. Also, some basic functions which we used to perform earlier using Excel, can now be easily done through these packages.
As far as machine learning algorithms are concerned, my pick will be Random Forest. It is a collection of decision trees and thus, gives accurate predictions.
Ankita: Okay! So, my next question to you would be- What according to you is the goal of Data Science?
Ujjawal: The goal of Data Science is to use large amounts of data to make predictions in a way that proves to be useful to the business. The aim of the company- to increase sales, retain customers, build a brand etc. can be realized through these predictions.
In short, the major goal of Data Science is to predict the future to uplift the business and nurture it.
Ankita: Were there any initial challenges that you faced when you entered the Data Science field? If yes, how could you overcome them?
Ujjawal: The primary challenge I faced was that I have already worked in Java and VB script but Python is advanced than these two languages.
There were many points that seemed to be confusing like when coding in Python, we don’t use semicolon after every line of code; something we do when coding in Java.
I guess this happens when you are studying several languages together and out of which, one is an advanced-level language. You tend to be confused. But practice makes you perfect at everything.
The second challenge was to understand the types of data visualization– graphs, charts, histograms and plots etc. This was because getting the insight (what it is trying to show) merely by looking at it, was difficult.
To analyze it in the most meaningful way, we need to look at everything and consider the broader aspect of it.
Ankita: How do you think has Data Science evolved over the last few years? What current trends do you see in it?
Ujjawal: Data Science has evolved a lot over the last few years. One very simple example of this is the “Recommender System”.
Online shopping has been there since long but recommender systems were not. And, it is with the help of Data Science that the recommender system is now in place; available data was extracted and used to device this system.
For instance, if a person is buying butter, there are high chances that the customer will also buy bread. So, the recommender system will show ‘bread and other products‘ that will be helpful to the user.
With the introduction of this system, the business of these e-commerce sites has increased manifold. Data Science has had a tremendous impact on their business, which will continue in the future in a more effective manner.
Ankita: What current trends in Data Science & AI do you see becoming very big in coming years?
Ujjawal: What I feel is that with the inclusion of Data Science in every domain, whether it is healthcare, BFS or e-commerce sites, it is going to be extremely helpful.
That day is not far when we will be able to predict from the analysis of the patient’s history, whether he will suffer from a deadly disease. With the help of machine learning algorithms, life-saving predictions like this will actually be possible in the near future.
Ankita: Ujjawal, are there any Data Science and AI influencers you follow?
Ujjawal: Yes, I follow DJ Patil and Elon Musk. I read their blogs and follow their LinkedIn and Twitter profiles.
Ankita: At Accredian, students are encouraged to maintain high-quality GitHub profiles. Have you also built a GitHub profile? How do you think this will help you?
Ujjawal: Basically, I have just started learning Data Science and don’t have many projects. But yes, I have completed the Capstone projects, both through EDA and machine learning algorithm and have uploaded it in my profile.
This means, I can also mention the link of my GitHub profile in my LinkedIn as well as in my resume. Now, if the recruiter will go through my resume or LinkedIn profile, they will have a better idea that I have worked on some real-time data and know basic machine learning and EDA.
Together with this, we can also maintain our GitHub profile in a very standard way, with the help of indexes and relevant pictures. When someone visits our profile, he would instantly know about our work. This is why I feel that GitHub profile is a very good way of representing our real-time projects for EDA and machine learning.
Ankita: Crafting a great Data Science resume is a critical part of getting shortlisted for Data Science roles. Tell us some ways in which you have improved your resume as a part of Data Science Career Launchpad.
Ujjawal: Yes, I did attend the Career Launchpad sessions, wherein many crucial points were discussed. These included some facts, such as there are some keywords that will naturally occur during the resume search.
This is why I designed my resume again, based on the Career Launchpad sessions and it really helped a lot. I included relevant keywords based on my profile. I had the main pointers like explaining everything in a very comprehensive way. As a result, my resume was complete in two pages.
Now my resume has all the key points- education, certifications, awards and achievements, skills in data science and projects done in data science. My resume also highlights my work experiences in different companies I have worked in; profile description and summary. This way I can say that these resume sessions helped me a lot. Anyone who looks at my resume now can say that it is far better than the previous one.
Not only resume but my LinkedIn profile also improved a lot with the help of the Career Launchpad sessions. I was told in the sessions that including GitHub profile link will give a glimpse of our background and will have an impact on the person viewing the profile.
Ankita: Okay, so now my next question to you would be- Accredian’s mission is to groom Data Leaders of tomorrow; what do you understand by Data Leaders? And how are they different from Data Scientists?
Ujjawal: Data Leaders are the ones who guide a group of data scientists for the future prediction modeling. They are the pioneers who hold a pivotal role in any Data Science project and interact with clients, understanding their requirements and conveying the results and keeping them updated about the progress of the project. Data Leaders also create a team of Data Scientists that works on data and aids in predictive modeling, which can be useful for the clients.
Ankita: Are there any applications of Data Science and machine learning in the industry that you are excited about?
Ujjawal: Recommender system is one of the applications of Data Science and machine learning that interests me a lot. This is because it is used in our daily life. The recommender system also finds a use in digital entertainment too, on various websites like Netflix and Amazon.
Ankita: What is your advice to anyone wanting to start a career in Data Science, someone who is new to this field and is interested to make a career in this field?
Ujjawal: Data Science is indeed the buzzword. It is the combination of art and science and howsoever attractive it might look from a distance, only a Data Scientist knows the amount of effort that goes into reshaping the available data.
The freshers need to have an ideal mix of mathematics, programming language and business. Or if they don’t have an ideal combination of these three components, they should be ready to learn and hone their skills. In this way, they will not only be successful in this field but will also prove to be useful to the organization.
Ankita: Indeed, a great piece of advice. My last question to you would be about your journey with Accredian so far. How has it been? Anything that you wish to share- reviews, feedback or anything, about us.
Ujjawal: Yes. I have had two terms so far; Term 1 was of statistics and basic Python, including NumPy and Panda packages and EDA; Term 2 was about machine learning. Both these terms were too good and helpful.
If we had any questions or doubts, those were cleared in that particular session. Even after the sessions, we could post our queries or doubts in the discussion forum or share them through an e-mail and those were cleared within no time. The instructors made sure that all the students attending the sessions have clearly understood the topic.
Ankita: Good to know about your experience. Thanks a lot for your time, Ujjawal. All the best.
Ujjawal: Thanks!
