From Graduate to AI/ML Engineer: Santhosh’s Journey

The demand for Artificial Intelligence and Machine Learning professionals has been rapidly increasing across India, with many aspiring engineers looking to transition into this high-growth field. One such inspiring success story is that of Santhosh Yadav, a B.Tech graduate from Hyderabad, who transformed her career path after completing his Certified Data Scientist course at DataMites Hyderabad. Through consistent learning, practical exposure, and expert mentorship, he landed a job as an AI/ML Engineer at Frandzzo Technologies.

In this interview-based article, we dive deep into Santhosh’s learning journey, his interview experiences, study routine, and the key insights he shares with future data professionals.

Exclusive Q&A: From Graduate to AI/ML Engineer – Santhosh’s Journey

In this exclusive Q&A, Santhosh shares his inspiring transformation from an Electronics and Communication Engineering graduate to an AI/ML Engineer at Frandzzo Technologies. He discusses his learning experience at DataMites, the interview challenges he faced, and the key skills that helped him succeed in the AI field. His story offers valuable guidance and motivation for aspiring AI and Machine Learning professionals aiming to launch successful tech careers.

1. Can you introduce yourself to our readers?

My name is Santhosh Yadav, and I am from Hyderabad. I completed my B.Tech in Electronics and Communication Engineering from CMR College in 2023. Soon after graduation, I joined DataMites Hyderabad for the Certified Data Scientist course in June 2023.

2. What made you choose DataMites for your training?

I chose DataMites because it offered offline classroom sessions, hands-on projects, and industry-level internships, which I believed were essential for building practical machine learning and artificial intelligence skills.

3. How long did your course and internship take to complete?

I joined the course in June 2023, completed my internship in January 2024, and cleared my mock interviews by May 2024. The structure helped me move step-by-step from learning concepts to gaining real-time project exposure.

4. What was the interview process like for your AI/ML Engineer role?

The interview started with basic introductions, followed by conceptual questions on Machine Learning, artificial intelligence and Deep Learning. They also asked logic-based and Python programming questions like the Fibonacci series and gave me a practical problem involving sentiment analysis and visualization using backend code.

5. What kind of technical questions did they focus on?

They mainly focused on NLP (Natural Language Processing), Computer Vision, and general programming skills. They wanted to see if I could apply logic to real-world AI problems.

6. How much time did you dedicate to self-study daily?

I used to study for about 4–5 hours a day. My schedule included morning and evening study sessions. Initially, I preferred studying at the DataMites offline center, as the environment and interaction with peers motivated me.

7. Which subjects did you consider most important during your learning journey?

For anyone aiming to build a strong foundation, I recommend prioritizing Python, SQL, and Statistics. Once you understand these, Machine Learning and Deep Learning concepts become much easier.

8. How important is mathematics for a data science career?

Mathematics is important but not too difficult. The level of math required is usually at an intermediate level mostly statistics and probability concepts. You don’t need to go too deep into complex theories.

9. Did your interviewers ask about mathematical concepts?

Not in depth. They focused more on the logic and working of algorithms rather than detailed mathematical derivations. Understanding the basics of how algorithms work is usually enough.

10. How crucial is SQL for data professionals?

SQL is very important. Even outside data science, SQL plays a major role in backend development and database management. It’s a must-learn skill for Data Analysts, Data Engineers, and Machine Learning Engineers.

11. What about Excel do data scientists really need it?

Excel is useful but not mandatory for data scientists. It’s more commonly used in data analysis roles. For data scientists, tools like Python, Power BI, and Tableau are more relevant.

12. How do you differentiate between Data Analytics, Data Analysis, and Data Science?

These fields overlap but differ in scope. Data Analytics focuses on interpreting trends, Data Analysis emphasizes understanding datasets, and Data Science combines both with AI and ML techniques to create predictive models.

13. How did you prepare your resume for interviews?

I made sure to include only relevant information skills, certifications, and project links. I added my LinkedIn and GitHub profiles, removed unnecessary details, and tailored my resume to match each job description.

14. What projects did you include in your portfolio?

I included my client project, internship project, and two Capstone projects from DataMites. I also added additional work on GitHub so that interviewers could review my live projects.

15. How many interviews did you attend before getting placed?

I attended around 4 to 5 interviews, mostly through DataMites placement support. Most of them focused on fundamental concepts and project understanding rather than advanced theory.

16. How was your experience studying offline at DataMites Hyderabad?

It was amazing. The offline learning environment helped me stay consistent and motivated. I met peers and seniors who guided me throughout my preparation. We discussed AI projects together, which improved my practical understanding.

17. What about the mock interview experience at DataMites?

The mock interviews were realistic and very helpful. I didn’t clear the first one, but after feedback and practice, I passed the second attempt. These sessions built my confidence for real interviews.

18. Any final advice for aspiring data scientists?

Stay consistent, practice coding daily, and make sure to build real projects. Use GitHub to showcase your work and focus on both technical and communication skills for interviews.

Santhosh’s journey highlights the impact of dedicated learning, hands-on practice, and the right guidance. For graduates and professionals aspiring to build a career in artificial intelligence and machine mearning, joining a trusted institute like DataMites can be a game-changer, helping bridge the gap between academic understanding and real-world AI expertise.

Refer to these articles:

• Asharani’s Success Story: From Billing Specialist to AI/ML Engineer
• Amaan’s Journey: Verification Analyst to AI Developer
• From Fresher to AI Developer: Shreya’s Inspiring Journey

Key Findings from Santhosh’s Journey to AI/ML Engineer

Discover Santhosh’s inspiring transition from an Electronics and Communication Engineering graduate to an AI/ML Engineer at Frandzzo Technologies. Through his learning experience and mentorship at DataMites, he built the technical expertise and confidence needed to thrive in the AI industry. 

Here are the key takeaways from his journey, summarized point-wise:

1. Background and Education
   Santhosh Yadav is from Hyderabad and completed his B.Tech in Electronics and Communication Engineering in 2023 from CMR College.
2. Training with DataMites
   He joined DataMites Hyderabad in June 2023 for an offline Certified Data Scientist course.
   Completed his internship by January 2024 and cleared mock interviews by May 2024.
3. Placement Achievement
   Santhosh got placed as an AI/ML Engineer at Frandzzo Technologies.
   His placement process included technical interviews focused on AI, ML, and Python.
4. Interview Process Insights
   Questions covered AI, ML vs Deep Learning differences, logic-based scenarios, and Python coding (e.g., Fibonacci series).
   One task involved sentiment analysis and visualization using backend and frontend integration, testing both NLP and computer vision skills.
5. Daily Study Routine
   Santhosh dedicated 4–5 hours daily for self-study, often splitting time between mornings and evenings.
   He preferred studying at the DataMites Institute for focus and collaboration.
6. Most Important Subjects
   Prioritized Python, SQL, and Statistics as foundational for Data Science, Data Engineering, and Analytics.
   Emphasized that understanding statistics makes Machine Learning easier.
7. Mathematics in Data Science
   Believes mathematics is important but basic to intermediate level knowledge is sufficient.
   In-depth math questions are rarely asked in interviews.
8. Importance of SQL
   Considers SQL mandatory for all data-related roles, including data science, analytics, and even web development.
9. Excel Usage
   Said Excel is useful for Data Analysts, but not very crucial for Data Scientists.
10. Power BI and Visualization Tools
    Mentioned that Power BI and Matplotlib were part of his interview tasks.
    Recommends learning Power BI basics for better job readiness.
11. Resume Preparation Tips
    Focus on ATS-friendly resumes using job description keywords.
    Include LinkedIn and GitHub links and avoid unnecessary sections like hobbies.
    Highlight relevant projects and skills aligned with job requirements.
12. Projects Completed
    Included client projects, internship projects, and capstone projects from DataMites.
    Showcased additional projects via GitHub during interviews.
13. Interview Attempts
    Attended around 4–5 interviews, most through DataMites placement support.
    Faced rejections mainly due to limited vacancies, not lack of technical knowledge.
14. Mock Interview Experience
    Failed the first mock interview but cleared on the second attempt, showing persistence and improvement.
15. Offline Learning Advantage
    Praised DataMites’ offline training environment for providing motivation, peer support, and mentorship from seniors.
    Felt that offline learning helped in collaboration and real-time discussions.

Santhosh’s journey from a B.Tech graduate to a successful AI/ML Engineer is a testament to the power of determination and the right guidance. With a structured approach, focused learning, and mentorship from DataMites Hyderabad, he was able to transition smoothly into the AI field.

Refer to these articles:

• Why Students Prefer Offline Artificial Intelligence Training in Hyderabad?
• How to Choose Best Institute for AI/ML in Chennai?
• Is There Still a High Demand for Artificial Intelligence in Bangalore?

For aspiring professionals, Santhosh’s story is proof that with dedication and the right training partner like DataMites, building a successful career in artificial intelligence is entirely achievable.

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DataMites provides specialized training in Data Science, Data Analytics, Python, and artificial intelligence course in Hyderabad. The institute provides a structured, practical, and industry-focused curriculum designed to equip learners with hands-on experience and real-world skills. Accredited by IABAC and aligned with NASSCOM FutureSkills standards, DataMites offers comprehensive placement support, internship opportunities, and flexible online and offline learning options. Its flagship AI Engineer course covers Python programming, machine learning algorithms, neural network development using frameworks like TensorFlow and Keras, as well as big data technologies, cloud computing, and AI ethics, giving students a competitive edge in the field. Additionally, learners can enhance their expertise through the machine learning course in Hyderabad, gaining the confidence and skills needed to succeed in AI and related domains.