From Fresher to Data Engineer: Arpitha's Inspiring Journey

Breaking into the tech industry as a fresher can be challenging, but with the right learning approach, consistent practice, and determination, success is within reach. Arpitha's journey is a great example of how building strong technical foundations, gaining hands-on project experience, and preparing through mock interviews can lead to rewarding career opportunities.

After completing her Computer Science and Engineering degree, Arpitha enhanced her skills in Data Science and Artificial Intelligence through continuous learning and practical experience. Her dedication helped her secure a Data Engineer role at NAM Info. In this DataMites Success Story, she shares her learning journey, interview experience, project work, career aspirations, and valuable advice for aspiring Data Science professionals.

Arpitha's Data Science and AI Journey with DataMites

Arpita’s journey with DataMites highlights how continuous learning, hands-on projects, and interview preparation helped her build skills in Data Science and Artificial Intelligence.

Q1. Could you please introduce yourself?

I completed my Bachelor's degree in Computer Science and Engineering from Mysore Royal Institute of Technology. After graduation, I joined DataMites in the June 2025 batch to build my career in Data Science and Artificial Intelligence.

Q2. What inspired you to join a Data Science course?

During my college, I worked on an academic machine learning project. That project sparked my curiosity about Data Science and AI. I wanted to gain practical knowledge and industry-relevant skills, which motivated me to enroll in the course.

Q3. What was your learning experience like at DataMites?

The learning journey was excellent. We started with Python from the basics and gradually moved into Machine Learning, Statistics, SQL, and other core Data Science concepts. Later, I also enrolled in the Artificial Intelligence course, where I learned Computer Vision, Natural Language Processing (NLP), and Generative AI. The trainers explained every concept clearly, making even advanced topics easy to understand.

Q4. Why did you choose AI after Data Science? 

After completing Data Science, I wanted to expand my knowledge in AI. Since AI is transforming many industries, I felt learning topics like Computer Vision, NLP, and Generative AI would help me stay ahead and build a stronger career.

Q5. What projects have you worked on?

I completed all my Data Science projects successfully. Currently, I am working on AI projects to gain more hands-on experience and improve my practical skills.

Q6. Can you explain the interview process?

The interview started with an online MCQ round that focused mainly on SQL and Python. After clearing that round, I attended an in-person technical interview. The interviewers asked questions on Python, SQL, Machine Learning, Statistics, NLP, Large Language Models (LLMs), and AI concepts. Finally, there was an HR interview covering my background, career goals, and why I was interested in the role.

Q7. What kind of questions were asked in the HR interview?

The HR interview included questions about my family background, career aspirations, why I chose Data Science and AI, and why the company should hire me.

Q8. How did the mock interviews help you?

The mock interviews were very helpful. The interviewers asked questions on Python, SQL, Machine Learning, and practical problem-solving. I couldn't clear the first mock interview, so I prepared further, attended another mock interview, improved my performance, and then became eligible for placement opportunities.

Q9. How was your experience with the Placement Assistance Team (PAT)?

The PAT team was very supportive throughout the placement journey. They guided me, encouraged me to improve, and helped me prepare for the interview process.

Q10. What challenges did you face during your learning journey?

Initially, I only had basic knowledge of Python from college. Learning advanced concepts in Data Science and AI required consistent effort and practice. The projects, assignments, and mock interviews helped me overcome those challenges.

Q11. What are your future career goals?

My goal is to become an AI Engineer. I want to continue learning advanced AI technologies, especially Generative AI, and work on more real-world AI projects.

Q12. What advice do you have for aspiring Data Scientists?

Build strong fundamentals in Python, SQL, Statistics, and Machine Learning. Practice regularly through projects, participate in mock interviews, and never stop learning. Continuous practice and confidence are the keys to success.

Q13. How do you feel after receiving your first job offer?

I am very happy and grateful. Receiving my first job offer has boosted my confidence and motivated me to continue learning and growing in the field of AI and Data Science.

Refer to these articles : 

• Venkata’s Journey from Fresher to Successful Data Engineer
• Harish's Journey From Fresher to Data Science Professional
• Abhinay's Journey from Fresher to Successful Data Engineer

Key Learnings from Arpitha’s Journey to Becoming a Data Engineer

Arpitha’s success story highlights how continuous learning, practical projects, and interview preparation can help aspiring professionals build careers in Data Science, Data Engineering, and Artificial Intelligence.

• Arpitha is a Computer Science and Engineering graduate with a basic foundation in Python and Java.
• Her academic machine learning project sparked her interest in Data Science.
• She joined DataMites in 2025 to strengthen her skills in Python, machine learning, and Data Science.
• She progressed from Python fundamentals to machine learning and advanced AI concepts.
• Her AI learning included computer vision, NLP, LLMs, and generative AI.
• She gained practical experience by working on independent AI projects after completing her AI course.
• Her first mock interview helped her identify areas for improvement and prepare further.
• The recruitment process included MCQs, a technical interview, and an HR round.
• The technical interview covered Python, SQL, statistics, machine learning, AI, NLP, and LLM concepts.
• She secured an opportunity as a Data Engineer and plans to continue developing her skills toward a future career in AI Engineering.

Refer to these articles : 

• Networking Strategies for Aspiring Data Scientists
• Introduction to Data Visualization in Data Science: Tools and Techniques
• Data Science Pitfalls and How to Avoid Them

Arpitha’s journey highlights how consistent learning, practical projects, and perseverance can help freshers progress toward their career goals. Starting with basic Python knowledge as a Computer Science graduate, she expanded her skills in Data Science, machine learning, and AI before securing an opportunity as a Data Engineer. Her experience encourages aspiring professionals to keep learning, gain hands-on experience, prepare for interviews, and confidently explore careers in Data Science, Data Engineering, and Artificial Intelligence.

Starting a career in Data Science requires strong technical skills, practical experience, and continuous learning. Arpitha's journey shows how structured training and hands-on projects can help launch a successful career. According to Fortune Business Insights, the global data science platform market was valued at USD 171.16 billion in 2025 and is projected to reach USD 975 billion by 2034, registering a CAGR of 20.40%. As demand for data professionals continues to rise, enrolling in top IT courses such as Data Science, Artificial Intelligence, Machine Learning, and Data Analytics can help learners build in-demand skills and advance their careers.

Arpitha's journey from a Computer Science graduate to a Data Engineer highlights the importance of structured learning, hands-on projects, and continuous upskilling. Through DataMites' industry-focused training, she built expertise in Python, SQL, Machine Learning, Artificial Intelligence, and real-world project implementation. With mock interviews, internships, IABAC® and NASSCOM® FutureSkills certifications, and dedicated placement support, DataMites helps learners become industry-ready. Enrolling in a data science course in Hyderabad at DataMites can help aspiring professionals develop in-demand skills and explore rewarding career opportunities in the growing IT industry.

Whether you’re a fresher or an aspiring data professional like Arpitha, DataMites Institute offers structured learning opportunities designed to help learners develop practical, industry-relevant skills. With 50+ offline centres and online learning options, DataMites provides data science courses in Delhi along with learning opportunities in Chennai, Hyderabad, Pune, Mumbai, Coimbatore, Ahmedabad, Kolkata, Noida, Indore, Jaipur, Chandigarh, Kochi, Nagpur, and Bhubaneswar. DataMites has also received the Best Skill Development EdTech award, recognising its contribution to skill development and career-focused learning. Through hands-on projects, expert mentorship, internship opportunities, and interview preparation, learners can build relevant knowledge and practical skills for careers in data and technology.