How Abhijeet Started His ML Engineer Career as a Fresher

Have you ever wondered how a fresher can build a career in AI and Machine Learning? Meet Abhijeet, who turned his interest in technology into a successful career and secured a role as a Machine Learning Engineer at Trinity with the right learning and mentorship.

His journey included challenges, from learning Python, SQL, statistics, and AI concepts to working on real-world projects. With regular practice, mentor guidance, and hands-on training at DataMites Institute, he gradually built his skills and confidence.

If you’re aspiring to start a career in AI or Data Science, Abhijeet’s journey shows how consistent learning and practical experience can help you become industry-ready. Let’s explore how his experience at DataMites helped him achieve his career goal.

Abhijeet’s Journey from Learner to Machine Learning Engineer: Complete Q&A

This Q&A session explores Abhijeet’s journey from learning AI and Data Science to building a career in AI/ML, covering his training, projects, preparation, interview experience, and career transition.

Q1: Could you introduce yourself and tell us about your educational background?

Hello everyone, my name is Abhijeet. I completed my Bachelor of Engineering in Computer Science in 2025. After graduation, I decided to build my skills in Data Science and joined DataMites Training Institute, where I learned Python, SQL, statistics, Machine Learning, Deep Learning, and other essential concepts. This learning journey helped me strengthen my technical foundation and progress toward my current role as an Associate ML Engineer at Trinity Mobility Private Ltd.

Q2: What did you learn during your Data Science course?

During the course, I learned Python, SQL, statistics, Machine Learning, and Deep Learning. I also worked on multiple projects, which helped me apply these concepts practically, improve my problem-solving skills, and gain confidence.

Q3: Was learning ML easy for you because you had a Computer Science background?

Python was easier because of my programming background, but Machine Learning was challenging initially. With regular practice, projects, and guidance from mentors, I gradually understood the concepts and became more confident.

Q4: How was your overall learning experience at DataMites?

My learning experience at DataMites Training Institute was very good. Some topics like SQL, statistics, data cleaning, and Machine Learning were challenging initially, but regular practice, projects, and mentor guidance helped me understand them better and gain practical experience.

Q5: Did you attend online or classroom sessions during your course?

I attended both online and offline sessions in Bangalore, but mostly preferred offline classes. During college exams and activities, I attended online sessions, which helped me balance both.

Q6: How did the recorded sessions and study materials help you?

The recorded videos and handwritten notes were very helpful for revision. I could revisit missed or difficult topics at my own pace, and they also helped me prepare for interviews.

Q7: How many projects did you complete during your AI and Data Science journey?

During my Data Science and Artificial Intelligence journey, I worked on five projects in total. Four of them were capstone projects, and one was a client project. Working on these projects helped me understand the concepts much better because I could apply Python, SQL, statistics, and Machine Learning to practical problems.

Q8: How did the client project help you understand real-world Data Science work?

The client project was valuable because I worked with real-world data and understood how projects are handled in an industry environment. It helped me apply Data Science concepts practically, improving my hands-on skills, problem-solving ability, and confidence.

Q9: How did mock interviews improve your confidence?

Before mock interviews, I lacked confidence and felt nervous while speaking with interviewers. The mock sessions gave me real interview practice and helped me communicate more clearly. After several sessions, I became more comfortable answering questions, which helped during my actual interviews.

Q10: How many interviews did you attend before getting the opportunity at Trinity Mobility?

Before getting the opportunity at Trinity Mobility, I had attended around two to three interviews. At that time, I lacked confidence and found it difficult to communicate clearly with interviewers. I also experienced nervousness during interviews. After going through mock interviews and improving my preparation, I became more confident and better prepared to handle the interview process.

Q11: Were questions about your projects asked during the Trinity Mobility interview?

Yes, my projects were important during the interview. The interviewer asked about my project approach, technologies, and techniques. For my diabetes prediction project, I was asked why I selected a particular Machine Learning model and then faced follow-up questions based on my answer.

Q12: How did the placement team help you prepare for your career?

The placement team supported me with resume building, communication sessions, interview preparation, and mock interviews. They also shared job opportunities and helped me understand company expectations, which improved my interview performance.

Q13: How long did it take to receive a client interview after clearing the mock interview?

After clearing the mock interview, I received a client interview opportunity within one to two weeks. The opportunity was based on my mock interview performance and helped me move from practice sessions to a real interview.

Q14: What advice would you give to freshers who are starting their Data Science journey?

My advice to freshers is to stay consistent and practice every day. Python, SQL, statistics, and Machine Learning may seem difficult at first, but regular practice, projects, and asking questions can make learning easier. Be patient, learn step by step, and trust the process.

Refer to these articles:

• How is Artificial Intelligence Changing the World?
• What is the Difference Between AI Engineer and AI Expert Course?
• What is the Significance of AI in Education?

Key Takeaways from Abhijeet’s Journey to Becoming an AI/ML Engineer: Complete Insights

Discover how Abhijeet, a 2025 Computer Science graduate, built his skills in Data Science and Artificial Intelligence and progressed toward an Associate ML Engineer role. This summary highlights his learning journey, practical experience, interview preparation, and career growth.

• Educational Background: Completed his Bachelor of Engineering in Computer Science in 2025.
• Technical Learning: Learned Python, SQL, statistics, Machine Learning, Deep Learning, and AI concepts at DataMites Institute.
• Practical Experience: Worked on multiple projects to apply technical concepts to real-world problems.
• Learning Approach: Strengthened his skills through regular practice, recorded sessions, hand notes, and mentor guidance.
• Project Experience: Gained practical exposure through a client project involving real-world data.
• Interview Preparation: Improved his communication and confidence through multiple mock interview sessions.
• Project-Based Interviews: Answered questions on project approaches, technologies, techniques, and Machine Learning model selection.
• ML Project: Worked on a diabetes prediction project and explained his choice of Machine Learning model during interviews.
• Placement Support: Received guidance in resume building, communication, interview preparation, and job opportunities.
• Interview Opportunity: Received a client interview opportunity within one to two weeks after clearing the mock interview.
• Career Development: Built technical knowledge, practical skills, and interview confidence through consistent learning.
• Career Achievement: Progressed into his current role as an Associate ML Engineer at Trinity Mobility Private Ltd.

Refer to these articles:

• How Andal Cracked Her First ML Engineer Job as a Fresher
• How Rakghitha Started Her AI Developer Career as a Fresher
• How Jayaram Transitioned from Mechanical Engineering to an AI Engineer

If you’re inspired by Abhijeet’s journey and looking to build a career in AI and Machine Learning, DataMites Institute offers structured, industry-focused learning with practical projects and expert mentorship. Its training approach helps learners strengthen their skills in Python, SQL, Data Science, Machine Learning, and Artificial Intelligence while gaining hands-on experience with real-world projects.

DataMites Training Institute offers practical, industry-focused Artificial Intelligence and Machine Learning programs. Its 9-month Artificial Intelligence course covers Python, Machine Learning, neural networks, TensorFlow, Keras, and hands-on projects, while the 5-month Machine Learning course focuses on core ML skills and applications. Accredited by IABAC and NASSCOM FutureSkills, DataMites Institute provides expert training, internship opportunities, and career guidance across 50+ offline centers, including Artificial Intelligence courses in Coimbatore, Chennai, Ahmedabad, Delhi, Mumbai, Hyderabad, and Pune.

Students and professionals across Hyderabad and Telangana can explore DataMites Artificial Intelligence courses in Hyderabad, designed with practical training, industry-focused projects, expert mentorship, and career guidance. With two convenient centers in Madhapur and Kukatpally, DataMites makes it easier for learners to access hands-on, career-oriented Artificial Intelligence training.