Karthikeyan’s Journey from B.Com Fresher to AI Engineer

Have you ever wondered how a student from a non-technical background can step into the world of Artificial Intelligence and build a career as an AI Engineer? Meet Karthikeyan, a BCom Computer Education graduate who turned his curiosity about coding and AI into a professional journey by taking the right learning path, consistent practice, and guided mentorship.

His journey was not easy. From initially struggling to understand coding concepts to gradually learning machine learning, Python, and real-world AI applications, Karthikeyan showed how continuous effort and practical exposure can overcome any academic limitation. The real turning point came when he joined a structured, hands-on learning program at DataMites Training, where he gained industry-relevant skills through projects and internship experience.

If you are someone aspiring to enter the AI field from a non-technical background, Karthikeyan’s journey shows how discipline, curiosity, and the right training environment can transform ambition into a real AI career.

How DataMites Helped Karthikeyan Start His AI Career in Artificial Intelligence

Karthikeyan’s journey highlights how a BCom Computer Education graduate developed a strong interest in Artificial Intelligence, built practical skills through hands-on learning at DataMites Training, and successfully began his career in Artificial Intelligence as an AI Engineer.

1. Tell us about your background before entering the AI field.

I come from a B.Com Computer Education background. During my college final year, especially in my third year, I realized I didn’t have clarity about technical skills like coding. I was interested in building something in technology, so I decided to explore that direction.

2. What made you choose Data Science and AI?

At that time, Data Science and AI were booming in the industry. I was curious about coding and technical work, so I decided to join DataMites Training in Data Science and AI Engineering. With continuous learning and hands-on project exposure, I moved into an industry role and now work as an AI Engineer at XRTRAFIN.

3. Did you have any prior programming knowledge?

Honestly, no. I only knew very basic things. I learned Python only at a basic level during the training. Most of my advanced learning started later during the internship and company exposure.

4. How was the training structure at DataMites Training?

The training was around six months of classroom sessions and one month of online learning. After that, the internship is still ongoing, where real project work is happening.

5. How did you manage your daily study and travel routine?

My class timing was 11 to 1. I used to travel almost two hours one way. After coming back home, I studied again at night using YouTube videos and online tutorials.

6. What kind of projects are you working on in your internship?

There are around four projects in total, where I have completed two projects and the remaining two are still ongoing, focusing on real-time machine learning and AI-based projects. These projects are helping me gain strong practical exposure in types of machine learning and their real-world applications.

7. Can you explain your interview or selection process?

There was no traditional interview with aptitude questions. I got a job link, applied through it, and within a day, I got a call. They asked me to come prepared in two to three days. In the interview, they mainly checked my project work.

8. What exactly did they evaluate in your interview?

They focused on how I built my project. I showed a machine learning project, hosted it using a Flask server, and also uploaded it to GitHub. They were interested in how I implemented the idea, not in theoretical questions.

9. What tools and technologies are you using currently?

I am working with Python, Java, JavaScript, and also learning full-stack development. For AI, I am working with YOLO models, OpenCV, and tools like Roboflow for dataset labeling.

10. What database are you using in your work?

We are using MongoDB in the company. I had learned SQL earlier, but MongoDB is more flexible and easier to handle data in our projects.

11. Are you also involved in frontend and backend development?

Yes, I am learning both frontend and backend. We also use some agent-based tools that automatically help generate frontend and backend structures.

12. What was the biggest learning shift for you?

The biggest shift was moving from zero coding knowledge to understanding machine learning models. Initially, I only knew Python basics, but later I learned how YOLO models and OpenCV work in real projects.

13. How important is data collection and research in AI, according to you?

It is very important. Before building any model, we need to collect datasets properly and do research. Without proper data, model training will not work effectively.

14. What challenges did you face during this transition?

The main challenge was a lack of technical background. Coming from commerce, everything was new. But consistent practice and internship exposure helped me improve.

15. What skills are most important for AI and Data Science learners?

Machine learning concepts are the most important. Along with that, understanding data handling, model building, and practical implementation is necessary.

16. Do you think AI tools can fully replace human effort?

No. Artificial Intelligence tools can help in automation and coding assistance, but model training, research, and decision-making still need human intelligence.

17. What advice would you give to beginners from non-technical backgrounds?

Start with basic Python, build interest in coding, and focus more on practical projects. Learning through real implementation is more useful than only theory.

Refer to these articles:

• The Future of Coding: Can AI Replace Software Engineers?
• What is the Difference Between AI Engineer and AI Expert Course?
• Learn about the Types of Machine Learning Algorithms

Key AI Career Insights from Karthikeyan’s Journey at DataMites

Karthikeyan’s journey offers important insights for anyone aspiring to build a career in Artificial Intelligence and Data Science:

• Karthikeyan’s experience shows that maintaining consistency in daily learning and practice, even for limited hours, can gradually build strong technical understanding and confidence.
• His journey highlights that struggling initially with programming concepts like Python is completely normal, and improvement comes through continuous practice and patience.
• Karthikeyan focused on strengthening core skills such as Python, Machine Learning, and AI fundamentals, aligning his preparation with industry expectations.
• Working on real-time projects and internship assignments at DataMites helped him gain practical exposure and improve his problem-solving abilities in Artificial Intelligence applications.
• Continuous guidance from mentors and trainers supported him in understanding complex topics step by step and improving his technical clarity.
• The structured support system at DataMites played a key role in helping him stay focused and aligned with career preparation goals.
• Regular feedback and timely assistance helped him stay consistent and maintain steady progress throughout his learning journey.
• Participation in mock interview sessions helped him build confidence and become comfortable with real interview environments.
• Resume-building guidance helped him effectively present his technical skills and project experience in a professional format.
• Karthikeyan remained open to learning across multiple domains like Data Science and AI, which strengthened his overall understanding of the field.
• Collaborative learning and peer interaction helped him stay motivated and made the learning process more engaging and consistent.
• Overall, Karthikeyan’s journey demonstrates that with structured training, disciplined practice, and the right mentorship, freshers can successfully build a strong career in Artificial Intelligence.

Refer to these articles:

• How Venuprasath Secured His First AI Engineer Job as a Fresher from Tamil Nadu
• How Shubham Cracked Two AI Engineer Job Offers as a Fresher
• How Nakshatra Secured Her First AI Engineer Job as a Fresher

Karthikeyan’s journey clearly reflects how the right combination of structured learning, consistent practice, and real-world exposure can shape a successful career in Artificial Intelligence. From building a strong foundation in Python, machine learning, and AI concepts through DataMites Training to gaining hands-on experience through internship projects, he steadily developed both technical understanding and practical confidence.

DataMites Training Institute delivers a structured 9-month Artificial Intelligence program designed to build strong job-ready skills through practical tools, live projects, and industry-focused ethical AI practices. Recognized among the Top IT courses, this program helps learners gain real-world exposure in AI and machine learning while developing hands-on expertise. It offers multiple career paths, such as AI Engineer, AI Specialist, AI Foundation, and NLP, allowing learners to select a direction based on their goals. With globally recognized certifications from IABAC and NASSCOM FutureSkills, the program is designed to prepare learners for real industry roles in the evolving AI domain.

DataMites Training Institute provides strong career support through mock interviews, resume building, and career guidance to help learners become job-ready. In Karthikeyan’s journey, this structured support helped him strengthen technical skills and build confidence through practical learning and mentorship. For learners across regions, including Gujarat, DataMites also offers an Artificial Intelligence Course in Ahmedabad, ensuring quality AI education with hands-on experience and strong career support.

DataMites has a strong offline network across 30+ cities in India, making quality AI education easily accessible to learners across the country. Along with Ahmedabad, DataMites Institute provides training programs in leading tech hubs such as Artificial Intelligence Courses in Delhi, Hyderabad, Bangalore, Pune, Chennai, Mumbai, and Coimbatore, enabling learners to select convenient locations while still receiving standardized, industry-focused training with practical, hands-on learning exposure.