Right from the start, Aditya Shivam was always looking toward the future. He started out as a software engineer, but was fascinated with the seemingly endless possibilities in data science and artificial intelligence (AI). He knew these interrelated fields would be the way of the future and he wanted to be a part of it. Undergraduate technology degrees provide a broad basis of knowledge, but it’s up to the individual to hone their skills and specialize in a given niche.
For Shivam, that niche would be big data and AI. All he needed was the right combination of practical, hands-on skills in order to realize his ambitions. This is the story of how Shivam prepared for the challenges he created for himself, including the crucial role of finding the right educational platform.
The Challenge: Making a Lateral Move from Software to Data
Not all career paths are linear; in fact, most probably aren’t. But what’s unique about Shivam is his early realization that he wasn’t quite on his preferred trajectory, even though he enjoyed early success. He started his career as a software engineer trainee with Nucleus Software in Noida, India, working his way up to the role of Senior Software Engineer after two quick promotions.
“During this time, I felt it was time for me to move away from Oracle and SQL and get on to the latest trends in the industry,” he said, referring specifically to the rapidly developing trends in machine learning and big data.
Shivam realized that essentially all industries would be looking for ways to leverage the tremendous amount of raw data generated every second in order to gain an edge and create efficiencies. His specific interest was in how this data could be used for predictions, classifications, and language processing within the context of AI and machine learning.
“Machine learning has changed the way we see data,” he said. “Now, with the help of easier programming languages like Python, we can create magic with code.”
His other passion, also enabled by big data, is robotics process automation (RPA). While the term “robot” may conjure images of industrial machines welding steel automobile chassis together, or perhaps your automated vacuum cleaner robot, RPA has more to do with the automation of administrative work. RPA may automate such processes as IT support, shipping logistics, data migration, or other jobs that reduce the time humans spend on repetitive tasks while reducing errors.
Every magician must learn the tools of their trade, however. Shivam was confident he had the requisite foundation in technology, but needed specific skills training to get onto his preferred career path.
The Simplilearn Solution: Patience and Planning for the Future
Shivam knew he wanted to learn the core skills that would enable a future career in big data and AI, but he wasn’t sure where to turn at first. He watched numerous free tutorials online but realized he wasn’t getting anything “concrete” that would help him make this transition. One of his relatives suggested he look into Simplilearn’s offerings.
In order to make the big shift he had planned, Shivam decided to take his relative’s advice and enrolled in Simplilearn’s extensive Big Data Engineer Master’s Program. This program combines several key courses on data science that help prepare learners for a wide variety of roles involving data and AI, including instruction in Hadoop, Spark, MongoDB, Data Science with R, and Data Science with SAS.
While he found the Hadoop ecosystem to be the most interesting part of the program, he truly appreciated the comprehensive nature of the program. He learned the fundamentals of data science and how it could be applied in addition to hands-on training on how to use Python, R, and other tools and processes.
“All these courses actually helped me to see my way through to become a data scientist,” he explained, pleased not only with the subject matter but in how it was packaged and presented in a practical, career-ready manner.
But Shivam didn’t simply go out and look for a job upon completion. He took about four months to fully immerse himself in these technologies, while working his software engineer job, during his free time. That meant less time for his other personal interests, including cricket and spending time outdoors, but he had a singular goal in mind.
The Results: Exciting New Career and a Big Pay Day
When he was ready to make the shift, Shivam said he was able to line up several interviews for a data science role. He said the interviewers, who were big data architects themselves, asked very specific questions about the projects they were working on—questions that he was able to confidently answer in detail. He said they were very pleased that he had such a compelling skill set in Python, data science, and machine learning.
“Once I started interviewing with companies, I realized that the training by Simplilearn had set up a solid foundation for me,” he said. “Overall, I was able to gain confidence in those niche techs and eventually landed a great gig where I was able to [apply what I had learned] to real-life problems.”
Shivam accepted a consultant role with Atos, working in the areas of AI, machine learning, and RPA. This lateral shift in careers also resulted in a 40 percent pay increase from what he was earning as a senior-level software engineer. He said he uses Python quite regularly for machine learning algorithms and other AI applications.
He’s not done advancing his career, not by a longshot. He hopes to manage a team of skilled AI, machine learning, and RPA professionals within five years, and sees himself leading an entire practice in the next 10 years, either in one of those disciplines or “any other niche technology that is yet to be discovered.” He also would like to help others achieve their goals someday, perhaps as a mentor.
Clearly, Shivam is not bound by what’s currently possible—the mark of any successful technology professional.
“Learning with Simplilearn has been a game changer for my career,” Shivam said. “Their learning platform and strategy is built to help each candidate understand and focus on upskilling themselves for a better future.”
The following video provides better clarity -
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