INSAID’s Spotlight Series: In conversion with Pridarshi Samrat

PS Blog

INSAID’s spotlight series is back with another inspiring story of a determined learner who is making waves in the field of Data Science and AI. Today, we introduce you to Pridarshi Samrat, a Design Engineer at Tech Mahindra Pvt. Ltd. who is currently pursuing the PGP-Data Science & AI program at INSAID‘s August 2022 Batch. 

Question 1: Which program and batch are you part of at INSAID, and tell us more about your current work profile?

Pridarshi: I am currently enrolled in PGP-Data Science & AI, Batch August at INSAID. I work as a Design Engineer at Tech Mahindra Pvt. Ltd. and have one year of experience in design. 

My current responsibilities include leading CAD-design transformation initiatives as well as developing and implementing new ideas.

Question 2: Walk us through your career journey and what got you interested in Data Science & Machine Learning.

Pridarshi: I began my career journey as a Mechanical Engineer, which was my specialization in college. After a few years, I decided to change my field of specialization to Data Science and Machine Learning Artificial Intelligence. 

During my studies, I was exposed to a variety of Data Science and Machine Learning tools and techniques, which piqued my interest in the field. I then gained practical experience in Data Engineering, working on projects related to data ingestion, transformation, and storage. 

This gave me a solid understanding of the data engineering process and its significance in data science. I then transitioned into a role involving Data Visualization, which provided me with an in-depth comprehension of the data analysis process and its importance in data science. 

Following that, I assumed the position of Data Scientist, where I worked on projects related to predictive modeling and machine learning. This experience gave me the opportunity to explore various machine-learning algorithms and techniques that can be used to solve complex problems. This experience further solidified my interest in data science and machine learning.

Question 3: What all tools and packages in Data Science & Machine Learning have you mastered in your Data Science & AI program at INSAID so far?

Pridarshi: At INSAID, I have mastered the following tools and packages in Data Science and Machine Learning:

  1. Python: NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow, Keras
  2. Statistical Analysis: Regression, Classification
  3. Natural Language Processing
  4. Big Data
  5. Machine Learning Algorithms: Linear and Logistic Regression, Decision Trees, Random Forests, K-Means Clustering, Naive Bayes.

Question 4: What are some of the initial challenges when you got started on your Data Science journey and how did you overcome it?

Pridarshi: One of the initial challenges I faced when I started my Data Science journey was getting familiar with the different programming languages and tools used for Data Analysis. I overcame this challenge by taking online courses, reading blogs and articles, and attending data science-related meetups and seminars

Additionally, I read books related to data science and applied the knowledge I gained to different projects. I also reached out to mentors in my network to ask questions and get advice. Through this process, I was able to gain the necessary knowledge and skills to become an effective Data Scientist.

Question 5: Who is your favorite faculty at INSAID and what did you learn from him the most?

Pridarshi: My favorite faculty at INSAID is Professor Deepesh Wadhwani. He taught me the importance of data-driven decision-making and how to use data to take informed decisions. He also taught me the importance of having a logical thought process and how to identify patterns in data.

He was also a great mentor and was always willing to help out with questions or issues.

Question 6: What is the goal of Data Science?

Pridarshi: The goal of data science is to extract meaningful insights and knowledge from data to inform and guide decision-making. Data science combines elements of mathematics, computer science, and business analysis to analyze large amounts of data to uncover patterns and trends

The insights gained from data science can be used to inform decisions in many areas, such as marketing, product development, finance, and operations.

Question 7: In your view, how has Data Science evolved in the last few years?

Pridarshi: In the last few years, Data Science has evolved drastically. We have seen the rise of powerful tools such as machine learning, artificial intelligence, and deep learning, which have opened up a whole new world of possibilities. In addition, the sheer amount of data available today has allowed for a greater level of accuracy in data analysis and predictions

Data Science has also become increasingly accessible to a wider range of users, thanks to the development of cloud computing and the availability of open-source software. Finally, Data Science has become much more focused on the business application of data, allowing organizations to use data more effectively to inform decisions and drive strategic outcomes.

Pridarshi: Here are a few trends I am excited about: 

  1. Automated Machine Learning: Automated machine learning (AutoML) promises to make machine learning more accessible to non-experts, allowing data scientists to focus on more complex tasks and enabling non-experts to adopt machine learning techniques in their own projects.
  2. Artificial Intelligence Applications: AI is being used to develop systems that can recognize images and objects, understand natural language, and provide intelligent recommendations.
  3. Edge Computing: Edge computing is an emerging trend in which data is processed close to the source, rather than in the cloud. This allows for faster data processing and better security.
  4. Big Data Analytics: Big data analytics is a field that uses large datasets to gain insights, identify trends, and make predictions.
  5. Cloud Computing: Cloud computing has become increasingly popular as a way to store and process data. It allows data scientists to access large datasets, as well as powerful computing resources, from anywhere in the world.

We hope you enjoyed reading this interview. Check out the INSAID Spotlight for more interesting student stories like this.


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