From Mechanical Engineer to AI Professional: Nagasai’s Inspiring Success Story

Can a mechanical engineer truly make a mark in the world of Artificial Intelligence? For many, the idea of switching from machines and design to data and algorithms might sound impossible  but not for Nagasai. With determination, the right mentorship, and hands-on learning through the DataMites Artificial Intelligence course, he transformed his career from mechanical engineering to AI mastery.

Q&A with Nagasai: Insights, Strategies, and Motivation for Aspiring AI Professionals

In this exclusive Q&A session, Nagasai shares his incredible journey from a mechanical engineering background to becoming an AI professional.

Q1: Can you start by introducing yourself?

My name is Nagasai, and I completed my graduation in Mechanical Engineering After my graduation, I was looking for a course in Data Science or AI, and that’s when I discovered DataMites in Hyderabad. I joined their Certified Data Scientist course, which helped me understand machine learning and build hands-on projects. Later, I also pursued their AI course, as I realized the future is moving towards Artificial Intelligence.

Q2: What inspired you to move from mechanical engineering to data science and AI?

During my final year of engineering, I worked on a project that involved machine learning concepts, even though I didn’t fully understand them at the time. That project sparked my curiosity. I began researching “What is machine learning?” and “How can I learn it from scratch?” That’s when I came across DataMites, which offered structured and practical data science training  the perfect opportunity to start my AI journey.

Q3: How was your learning experience with DataMites?

It was excellent! I joined offline classes at the Hyderabad branch, where my trainer was Mr. Nikhil Sir. The sessions were detailed and interactive, covering everything from Python programming to Machine Learning, Deep Learning, and Statistics.

Initially, I was new to programming. I had only used basic print functions in Python. But through DataMites, I learned Python from scratch, progressing from beginner to advanced levels. The practical sessions made it easier to understand real-world applications.

Q4: How did you manage your study routine and practice schedule?

My class timings were from 12 PM to 2 PM. After class, I stayed back at the institute to practice coding and revise concepts. I also used external resources like W3Schools and GeeksforGeeks to improve my problem-solving skills.

This routine helped me strengthen my understanding of Python, data analysis, machine learning algorithms, and AI concepts. Consistent practice was the key to improving both my technical and logical skills.

Q5: Were you already familiar with statistics before joining the course?

Yes, to some extent. During my engineering studies, I had subjects that involved applied statistics. So, when DataMites started teaching statistical concepts for data science, it was easier for me to connect the dots. Concepts like probability distributions, correlation, and hypothesis testing became clearer as I applied them in machine learning models.

Q6: Did you apply machine learning concepts in your mechanical projects?

Yes, definitely. During my earlier days, I tried to integrate machine learning techniques into mechanical or production-related projects. For example, while performing material testing or production-level analysis, I realized how machine learning could help predict results faster and more accurately. It helps reduce manual testing time and speeds up decision-making in manufacturing.

Q7: What was your experience like during mock interviews at DataMites?

The mock interviews conducted by DataMites were extremely useful. I attended multiple rounds  and each one helped me identify new areas to improve.

In my first mock interview, I wasn’t fully prepared, and I struggled a bit with Python, SQL, and coding questions. But after that, I focused on those weak points, practiced consistently, and by the next round, my confidence improved a lot.

By the time I faced real client interviews, I was already familiar with the question patterns, as some questions in the actual interviews were similar to those from the mock rounds.

Q8: How many client interviews did you attend before getting selected?

I attended around five to six client interviews. Each interview was a learning experience for me.

After every round, I analyzed where I got stuck and made notes of areas that needed improvement  whether it was in AI concepts, programming logic, or project explanation. Gradually, I became more confident and performed better with each opportunity.

This consistent preparation and feedback helped me crack my final interview successfully.

Q9: Can you share your real interview experience?

In the interview where I got selected, the process started with a technical round. They first asked me to explain my AI and data science projects including how I approached problem-solving, how the model worked, and what results I achieved.

Then they gave me a few scenario-based questions for example, they’d describe a business problem and ask how I would handle it using AI or machine learning. They wanted to see my logical thinking and analytical skills.

After the technical round, there was an HR interview. It focused on personality-based questions, such as my strengths, weaknesses, and overall career goals. The HR round tested how well I would fit into their team environment.

Q10: How did the DataMites training prepare you for machine learning interviews?

The DataMites training program gave me a strong foundation in machine learning concepts. We learned to identify input and output data, perform feature engineering, and build models efficiently.

I realized that while the theory behind algorithms like Linear Regression or SVM is important, the real power lies in understanding how they work behind the scenes. This helps in improving model accuracy and debugging issues effectively.

I also learned that coding in machine learning is actually simple once you understand the logic. Sometimes just 3–4 lines of Python can make a working model.

Q11: What were some challenges you faced, and how did you overcome them?

My biggest challenge was programming, as I came from a mechanical background. Initially, I struggled to write and understand code. But through consistent practice, mentor guidance, and solving exercises daily, I gradually became confident.

Another challenge was understanding deep learning and large language models (LLMs). To overcome that, I requested additional classes, and the DataMites team arranged extra learning sessions to help me fill in the gaps.

Q12: How did DataMites support you during your learning journey?

DataMites provided comprehensive training, mentorship, and project support throughout my journey. The trainers were approachable, and the course structure was very practical.

They also offered placement guidance, mock interviews, and career counseling, which boosted my confidence. Thanks to their support, I was able to secure my first job in the AI field, something I’m very proud of!

Q13: How did it feel to land your first job after completing the course?

It felt amazing! Yes, this is my first job, and it’s directly in the field I wanted to pursue  AI and Data Science. I attended a few interviews before getting selected, and every attempt improved my confidence and technical skills.

 Getting my first job offer felt like the best birthday gift ever! It was the result of consistent effort, guidance from DataMites, and a lot of practice.

Q14: What advice would you give to students from non-IT backgrounds who want to learn AI or Data Science?

My advice is simple, don't be afraid of programming or math. With the right guidance and consistent effort, anyone can learn AI and data science.

Practice every day, work on projects, and stay curious. Join a structured artificial intelligence course like the one offered by DataMites, which covers everything from the basics to advanced topics. Believe in yourself and keep learning  your hard work will definitely pay off!

Refer these below articles:

• How Abhishek Landed a Career as an AI/ML Engineer ?
• From Software Developer to AI Expert: Ashish Nayak’s Journey to Success
• From Graduate to AI/ML Engineer: Santhosh’s Journey

Key Takeaways from Nagasai’s AI/ML Journey

• Career Transformation: Nagasai transitioned from a Mechanical Engineering background to a thriving career in Artificial Intelligence and Data Science through structured learning and dedication.
• Right Training Partner: He chose DataMites Hyderabad for its Certified Data Scientist and AI courses, which offered a clear, practical path to mastering machine learning and AI concepts.
• Strong Foundation in Programming: Initially unfamiliar with coding, Nagasai learned Python from scratch through DataMites’ beginner-friendly and hands-on sessions, eventually mastering advanced concepts.
• Consistent Practice Routine: He maintained a strict study routine, attending classes from 12 PM to 2 PM and staying afterward to practice coding and revise concepts daily.
• Leveraging Online Resources: Supplemented his learning with external websites like W3Schools and GeeksforGeeks to strengthen problem-solving and logical thinking skills.

Read these below articles:

• What is Lemmatization in NLP?
• What is Retrieval-Augmented Generation (RAG)?
• Small Language Models are the Future of Agentic AI

Nagasai’s journey from a mechanical engineering graduate to a ML and AI professional is a powerful example of how passion, discipline, and the right mentorship can transform careers. His story is proof that with the right guidance, even those from non-programming backgrounds can thrive in the world of artificial intelligence.

Step into the dynamic world of Artificial Intelligence and develop the in-demand skills that leading employers value most. Enrolling in an Artificial Intelligence course in India empowers you with hands-on learning, real-world project experience, and expert career mentorship. As the need for skilled AI professionals grows rapidly, the right training can open doors to diverse, high-paying, and future-focused career opportunities.

Pursuing an Artificial Intelligence course in Hyderabad can prepare you for exciting roles such as AI Engineer, Machine Learning Specialist, Data Scientist, and AI Researcher. Whether you’re a beginner exploring new possibilities or a working professional aiming to enhance your expertise, learning AI in Hyderabad builds a solid foundation for success in today’s data-driven industry.

The DataMites Artificial Intelligence Course in Bangalore is thoughtfully designed to cater to both beginners and experienced professionals. The program focuses on hands-on, project-based learning, enabling participants to apply theoretical AI concepts to real-world business challenges. With expert mentorship and robust placement support, this course empowers learners to excel in Bangalore’s dynamic and innovation-driven tech ecosystem. Upon completion, participants earn globally recognized certifications from IABAC and NASSCOM FutureSkills, enhancing their professional credibility and unlocking exciting career opportunities in the field of Artificial Intelligence.