Accredian’s Spotlight Series: Exclusive Interview with Srikrushna Panigrahi

Welcome to the Accredian Spotlight Series, where we showcase the achievements and success stories of our talented students. Today, we bring to you the story of Srikushna Panigrahi, former production engineer at Finolex India who made a remarkable transition into the world of data analytics.

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

Srikrushna: I am from the August (GCD) Batch. I was working as a Production Engineer at Finolex India, handling all production-related activities along with MIS reporting as a part of my daily schedule. I found that analytics has become a core need across all industries, so I planned to move into a data analytics portfolio.

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

Srikrushna: I worked with Finolex India as a production engineer for three years. Later, to enhance my career prospects, I pursued a degree in Electricals & Electronics. I am very interested in analytics, and I have noticed that it plays an important role in every industry, especially in production where there is a high demand for it. Therefore, I decided to obtain certification in Data Science & ML.

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

Srikrushna: Up until now, I have acquired knowledge in several areas related to data science, such as Statistics, Exploratory data analysis, and different methods of Machine Learning.

In Statistics, I have learned about various statistical concepts and techniques, including hypothesis testing, probability, and distributions.

In Exploratory data analysis, I have gained skills in data cleaning, visualization, and feature engineering, which are crucial steps in preparing data for modeling.

Lastly, in Machine Learning, I have studied various algorithms used for supervised and unsupervised learning, such as linear regression, decision trees, clustering, and dimensionality reduction.

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

Srikrushna: Coming from a non-coding background, I initially faced challenges in recalling and remembering programming scripts. However, as mentioned by our mentors, the only way to overcome this challenge is through practice, and this helped me to overcome this issue.

Despite this, I still encounter challenges occasionally, but each time it presents a new opportunity for me to learn and develop my problem-solving skills. Through these experiences, I am continuously learning and growing in my abilities to tackle such situations.

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

Srikrushna: All the faculties I have come across have their unique and effective ways of imparting knowledge. The most valuable thing I have learned from my faculties is to stay focused and to analyze every piece of data deeply, as data is the only source of business growth. Their guidance and expertise have been invaluable in helping me develop a strong foundation in data science.

Question 6: What is the goal of Data Science?

Srikrushna: Currently, I am focused on building and strengthening my career in AI & ML. In the future, if opportunities permit, I would like to explore and learn more about Robotics, as it could be a valuable skill set in the production industry.

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

Srikrushna: In today’s highly competitive and data-driven business environment, the importance of data science cannot be overstated. Every sector and industry has increased its dependency on data science to make data-driven decisions and gain valuable insights into market trends and customer behavior.

By using data science techniques and tools, organizations can gather, process, and analyze large amounts of complex data to extract meaningful insights and gain a competitive advantage. These insights can help organizations to plan their business strategies, make informed decisions, optimize their operations, and improve their customer engagement.

In essence, data science has become a vital need of the market, and its influence is only expected to grow in the coming years.

Srikrushna: I am particularly excited about the current trends in forecasting and predictive analysis, which involve using historical data and machine learning algorithms to make accurate predictions about future events and trends.

Question 9: Which are some of the blogs that you follow?

Srikrushna: I have spent a significant amount of time reading blogs and articles on machine learning, big data, and business intelligence, as I am passionate about staying up-to-date with the latest developments in these fields.

Question 10: What is your advice to anyone wanting to start a career in Data Science?

Srikrushna: In today’s digital age, data science has become a rapidly growing field with enormous career potential. By choosing a career in data science, individuals can gain valuable skills and knowledge in data analysis, machine learning, and statistical modeling, which are in high demand across various industries. 

In conclusion, choosing data science as a career path can be a wise and proper move for those who are passionate about working with data and analytics. With the increasing demand for data-driven insights across industries, data science has become a crucial skill set for professionals looking to build a successful career in today’s digital world.

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

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