{"id":9974,"date":"2020-10-28T11:00:51","date_gmt":"2020-10-28T05:30:51","guid":{"rendered":"http:\/\/ivyproschool.com\/blog\/?p=9974"},"modified":"2021-06-10T13:58:16","modified_gmt":"2021-06-10T08:28:16","slug":"data-science-success-story-of-pranjal-biyani","status":"publish","type":"post","link":"https:\/\/ivyproschool.com\/blog\/data-science-success-story-of-pranjal-biyani\/","title":{"rendered":"Data Science Success Story of Pranjal Biyani"},"content":{"rendered":"


\n\"pranjal<\/a><\/p>\n

Undoubtedly, data science has taken down most industries, making data scientists the most sought job of the 21st century as per the Harvard business review. Despite the increasing demand and appetite for experienced data scientists, the job is ambiguously described most of its time. This lack of real industry-standard still confuses a lot of professionals who desire to switch to a data science role. After having a conversation with many analysts and software developers, we realize how overwhelming the available information about artificial intelligence and machine learning can be.<\/p>\n

Our student, Pranjal Biyani, shares his story with us and explains how we helped him find his potential in Data Science and Analytics. Pranjal is a third-year undergraduate at the Indian Institute of Engineering, Science, and Technology. Pranjal is fascinated by the finance industry and has spent two and half years in data science by now, Pranjal has done projects that have made him realize the value of what data can potentially do to any industry in the world.<\/p>\n

Pranjal joined Ivy in mid-2018. His interest in learning data science has brought him to Ivy as he inquired about all the projects that we do, all the coursework that we prepare the students for, and the entire structure of the program that one has to go through. While Pranjal was able to find a lot of courses on the internet, however, practical exposure to a project is something that excited him much more. He thinks the incorporation of projects is very important for the course and that should be done at frequent intervals. Ivy provides projects from different industries, problem statements that excited him the most.<\/p>\n

He felt that there is a significant level of tactical experience and practical exposure is required to significantly define one\u2019s potential as a data scientist or machine learning engineer. Pranjal did a data science project and the industry demand for data science and found that there is a miraculous increase in the demand for data scientists. the first year where the demand for data science is going to exceed even software engineers. Pranjal learned MS-Excel and then moved on with other projects, figuring out a way to create a data science project of his own. He took help from our faculty and with their help, he outlined every single aspect of the project. The faculty also provided him with a lot of resources that were required based on which, he created a data science project. He worked as an intern on the same project with a company named \u00c5kerlund, which is where he was introduced to the real and practical world of data science.
\nLearning with Ivy has been fun for most of our students and Pranjal\u2019s excitement is the best example of it. At the end of the course, there will be a portfolio that one can provide to any recruiter across the world.<\/p>\n

Any time is the best time to start a career as a data scientist, is one thing that Pranjal believes he would always remember from his Ivy\u2019s instructors. He believes that it is not age-specific and depends more on personal understanding and analytical skills.<\/p>\n

\u201cThere are a lot of people who are confused about what data science really is. It is the sum of all possible things that you can do with data. But once you start specializing in a particular industry like machine learning or artificial intelligence, you can be a deep learning engineer. You can be a neural network algorithm maker. There are a lot of possibilities with respect to it. But the one thing that data science is other than others is that it’s not about coding, it’s about creativity with your analytical mindset.\u201d<\/em><\/strong><\/p>\n

So, let\u2019s not get scared by just seeing the coding part. As a data scientist or as a particular engineer in any particular field related to data science, one will surely not need just one skill and but an entire plethora of skills that can enhance every project. Doing personal projects and building GitHub, Amazon AWS course can help in learning about the cloud and its technologies. There are so many other things that one needs to constantly practice and that can only be encouraged in an environment than what normally projects in normal courses.<\/p>\n