Mechanical Engineer to Data Scientist: Kariyappanavar’s Journey

In today’s digital age, the journey from a non-tech background to a growing data science career is no longer uncommon—but it's still highly impressive. Meet Prajwal, a mechanical engineering graduate who carved his path into the tech world and recently secured a position as a Data Scientist at Atomic Loops.

Prajwal shares his inspiring journey—from selecting the right training institute to tackling interviews and gaining real-world project experience. If you're a fresher, a career switcher, or simply aiming to break into data analytics or data science, this Q&A will offer actionable insights and motivation. For more stories like his, you can watch DataMites success stories and see how others have transformed their careers just like Prajwal.

Kariyappanavar’s Data Science Transformation with DataMites

Kariyappanavar’s inspiring shift from mechanical engineering to data science showcases how the right training and determination can redefine your career path.

Q1. Can you give us a quick introduction about yourself?

Yes, I’m Prajwal Kariyappanavar, a mechanical engineering graduate. I’ve always been curious about data analytics, which led me to pursue a course at DataMites. Now, I’ve secured a role as a Data Scientist at AtomicLoops.

Q2. What tools and technologies did you learn during your training?

I learned Power BI, Tableau, MongoDB, MySQL, and a bit of Python. I also focused on Advanced Excel and data cleaning techniques.

Q3. Did you do any internships or hands-on projects?

Yes, I interned at Rubix Solutions in Bangalore, where I worked on real-time projects including Phone Sales Analysis. I created dashboards using Power BI and Tableau, and applied Python for data processing and automation tasks.

Q4. What made you transition from mechanical engineering to data analytics?

During engineering, I developed a strong interest in data. I researched online and came across DataMites, where I attended a demo session that convinced me I could start from scratch—even without any coding background.

Q5. How did you manage your time and learning as a fresher from a non-IT background?

I stayed focused and self-motivated. I watched LMS recordings, took notes daily, and supplemented learning with YouTube tutorials. My goal was to prove that even someone from mechanical engineering can master Python and data tools.

Q6. Tell us more about the course you pursued.

I enrolled in the Certified Data Analyst (CDA) course from DataMites. The program started with basic Excel and moved up to SQL, Power BI, and Python. It was beginner-friendly, even for someone with no prior IT experience.

Q7. What were the rounds like in your interview with Atomic Loops?

There were two rounds: an HR round and a technical round. The HR round was focused on background, strengths, weaknesses, and learning journey. The technical round was about live coding, Power BI, SQL, and Python skills.

Q8. Were there any machine learning questions in the interview?

Interestingly, no. Although I’ve learned some machine learning concepts out of personal interest, the interview focused more on Python, SQL, Excel, and Power BI.

Q9. Did mock interviews help you prepare?

Absolutely. Mock interviews at DataMites helped reduce anxiety, improve stage presence, and understand how real interviews are conducted. It prepared me for the unexpected and gave me confidence.

Q10. How did DataMites support you in preparing your resume?

They helped me refine my resume multiple times. Every time I made a mistake, they provided feedback and shared samples to model. That helped me build a strong, targeted resume that got noticed.

Q11. What kind of projects did you showcase in your resume?

I highlighted:

• Phone Sales Analysis (with web scraping)
• Customer-driven live projects at Rubix Solutions

These projects covered end-to-end data workflows—from collection to dashboarding.

12. What challenges did you face, and how did you stay focused?

Being from a non-tech background, learning Python and analytics was tough. But people telling me "mechanical engineers can’t code" became my biggest motivation. I took it as a challenge to prove otherwise.

13. Where do you see yourself in the next 5 years?

I aim to become a Senior Engineer, moving deeper into Artificial Intelligence and advanced data science, especially in AI solutions and automation.

14. What advice would you give to freshers or beginners?

First, enroll in a proper training program—free resources are not always enough. Focus on mastering tools like SQL, Python, Excel, and Power BI. Build real projects, prepare well, and practice interviews.

15. What would you say to those not getting job calls despite applying?

There are plenty of openings, but companies want job-ready candidates. Just writing “data analyst” on a resume isn’t enough—you need to prove your skills through projects, knowledge, and readiness to commit long-term.

Refer these articles:

• How Pratham Transitioned From ECE to a Data Science Role
• From Aspiration to Achievement: Karthik’s Data Science Jouorney
• Adheeka's Journey: From Fresher to Successful Data Scientist

Key Takeaways from Prajwal’s Data Science Journey

Here are the key highlights from Prajwal Kariyappanavar’s inspiring transition into data science:

• Prajwal is a mechanical engineering graduate with no prior IT background who successfully transitioned into data science.
• He enrolled in the Certified Data Analyst (CDA) course at DataMites, which provided structured learning from basics to advanced tools.
• Learned tools like Power BI, Tableau, Python, SQL (MySQL), MongoDB, and Advanced Excel during training.
• Interned at Rubix Solutions, working on real-time projects like Phone Sales Analysis and Customer Behavior Analysis using Power BI, Python, and Tableau.
• DataMites’ mock interview sessions helped him gain confidence, reduce anxiety, and prepare for actual interview conditions.
• With the help of DataMites, Prajwal created a refined, project-based resume that demonstrated real skills rather than just listing tools.
• The Atomic Loops interview involved HR and technical rounds with questions on Python, SQL, Power BI, and live coding, but not machine learning.
• Doubts from others about mechanical engineers learning to code fueled his determination to succeed.
• Managed time effectively by watching LMS recordings, making notes, and supplementing learning with YouTube tutorials.
• Plans to grow into a Senior Engineer specializing in AI and automation over the next five years.
• Choose a structured course, focus on mastering core tools, build real projects, and practice interviews.
• Just applying isn’t enough—demonstrating real, job-ready skills through practical projects is essential to stand out.
• DataMites course structure allowed him to start from scratch with no prior programming experience.
• Commitment to daily learning and staying goal-oriented helped him overcome challenges.
• Practical exposure and internships played a key role in making him job-ready and confident.

Refer these articles:

• How to Become a Data Scientist in Mumbai
• Data Science Course Fees in Mumbai
• Why Data Scientist Career in Mumbai

Prajwal’s journey is more than a career switch—it’s a powerful reminder that your background doesn’t limit your future. From mechanical engineering to landing a data scientist role, he proved that with the right mindset, practical training, and support from platforms like DataMites, anything is possible.

In today’s digital world, where data science is considered one of the top IT courses, his story offers a clear message to aspiring professionals: with focus, dedication, and the courage to learn, you can break into this exciting field too.

If you're inspired by Kariyappanavar’s remarkable journey from mechanical engineering to data science, now is the perfect time to upskill and transition into this dynamic field. According to the IMARC Group, the global data science platform market is projected to grow from USD 15.2 billion in 2024 to USD 144.9 billion by 2033, at a CAGR of 27.08%. With industries producing vast volumes of digital data, the demand for skilled data professionals is rapidly increasing.

Choosing a quality training institute that offers hands-on learning, real-time projects, and placement support is essential for success. Enrolling in a trusted data science training in Mumbai, Bangalore, Hyderabad, Chennai, or Delhi could be your launchpad into a high-growth tech career.  

DataMites Institute was instrumental in Kariyappanavar’s career transformation. With industry-recognized training in Data Science, AI, Machine Learning, Python, and Data Analytics, and backed by IABAC and NASSCOM FutureSkills accreditation, DataMites provides expert mentorship, practical exposure, and job assistance to help learners break into tech roles.

With online and offline data science courses in Mumbai, Pune, Bangalore, Hyderabad, Chennai, Ahmedabad, and Coimbatore, DataMites makes it easy for professionals, freshers, and career changers to gain the skills needed to thrive in data-driven industries — just like it did for Kariyappanavar.