Hewlett Packard Enterprise Data Science Institute

Using computational fluid dynamics to predict and improve oil recovery in hydrocarbon reservoirs, Ritesh Bhakta further applies concepts of data visualization, high-performance computing, and scientific image analysis in his daily work as a Digital SCAL Engineer at Schlumberger. After completing the program’s four courses, Bhakta was able to earn a Micro-credential in Data Science. He was asked to share his experience with the innovative program.

In what ways has the program been helpful to you, and has it helped you get the job you have now?

RB: Through the program, I was able to learn data visualization skills which are paramount when creating 3D models and performing simulations. Data management skills with Python helped me work through large datasets with ease. I eventually want to try to apply machine learning techniques that I learned in the program to develop models in order to enhance the classification of components during image analysis. During my interview, most of the technical questions revolved around my programming skills, data visualization abilities and knowledge of high-performance computing (HPC). Thankfully, I had also completed the Intro to HPC class!

You earned a micro-credential in data science, which means that you also have four-course badges under your belt. Can you tell me about some of your favorite courses?

RB: I'd say my favorite courses were Data Visualization and Machine Learning. I've always had a penchant for data visualization and believe that representing data in a way that is accessible to the masses is just as important as the data analysis. In the machine learning class, I was able to use the skills attained in the other classes to perform powerful data analysis which I adapted to solve problems in the Earth Sciences, my domain of interest.

Can you name some specific moments in your experience that were really engaging and stimulating?

RB: I would say that learning how to create a dashboard and visualize data in multiple ways depending on objectives and goals was very captivating. This helped me become more thoughtful and creative when tasked with creating graphics, tables and other visualizations.

What were some of your favorite projects or assignments that you worked on while taking the courses?

RB: My project for the Principles of Data Management class was my favorite project. We were given the freedom to use any publicly available datasets and since I'm a bit of a space nerd, I used meteorite fall records provided by NASA, to perform data analytics and visualization to better understand the distribution of meteorite falls.

At the HPE Data Science Institute, our research specializes in ML/AI, Visualization, high-performance computing (HPC), Image Analysis, Scientific Computing, Natural Language Processing, and Robotics. What kind of concepts involving data science do you use in your job today?

RB: From the list above, visualization, high-performance computing, image analysis and scientific computing are essential to fulfill my job responsibilities. There are still many challenges to overcome in the field of computational fluid dynamics and machine learning is the right tool for the job. My goal is to implement machine learning techniques to improve the results of current simulations to better reflect what is observed in nature.

How did you apply the teachings of the micro-credentials program to your work now?

RB: What I can say is that with everything I gained from the micro-credential program, I am able to quickly craft and test creative solutions that permit better data management, visualization and overall, a more robust scientific analysis.