How Kanchi Built Her Career in Artificial Intelligence and Automation

Have you ever wondered how a recent graduate can successfully transition from learning Data Science to securing an AI and Automation Trainee role? Meet Kanchi Gupta, a Computer Science Engineering graduate who transformed her passion for technology into a promising career in Artificial Intelligence through consistent learning, hands-on practice, and determination.

Although Machine Learning was initially challenging, Kanchi stayed committed to regular practice, worked on real-world projects, and continuously expanded her knowledge with the guidance of expert mentors at DataMites. This practical learning approach helped her build the confidence, problem-solving abilities, and technical skills needed to excel in interviews. Her dedication paid off when she secured an AI and Automation Trainee position at ERANEST TECHNOWARE PVT LTD, marking an important milestone in her career journey.

If you're an aspiring AI or Data Science professional, Kanchi Gupta's success story demonstrates how consistent effort, hands-on experience, and the right mentorship can open doors to exciting career opportunities. Her journey reflects how industry-focused training, hands-on learning, and perseverance can help learners confidently launch successful careers in Artificial Intelligence through DataMites.

From Computer Science Graduate to AI and Automation Trainee: Kanchi Gupta’s Success Story 

In this Q&A, Kanchi Gupta shares how her learning journey at DataMites helped her build a strong foundation in Artificial Intelligence and Data Science. She talks about overcoming challenges in Machine Learning through consistent practice, working on real-world projects, receiving valuable mentorship, and preparing for interviews with confidence. Her dedication and industry-focused training ultimately led to her placement as an AI and Automation Trainee at ERANEST TECHNOWARE PVT LTD, marking the beginning of her professional career in AI. 

1. Can you introduce yourself and tell us about your educational background?

I’m Kanchi Gupta recently graduated with a Bachelor of Engineering in Computer Science Engineering from Professor Ram Mega Institute of Technology in 2025. After graduation, I enrolled in the Certified Data Scientist (CDS) course at DataMites to build practical skills in Data Science and Artificial Intelligence.

2. What motivated you to join the Data Science course?

I wanted to build a solid foundation in Data Science and Artificial Intelligence while developing the practical skills needed for a successful career in the field. The course offered comprehensive training in Python, SQL, Machine Learning, Deep Learning, and hands-on projects, making it the right choice for my career goals.

3. What technologies did you learn during the course?

During the training, I learned several important technologies, including:

• Python
• SQL
• Machine Learning
• Deep Learning
• Data Analysis
• Hands-on Project Development

These topics helped me build both theoretical knowledge and practical experience.

4. How did the mentors help throughout your learning journey?

The mentors played an important role in my learning process. Whenever I faced difficulties while working on projects or understanding concepts, they patiently guided me. Their continuous support made it easier to improve my technical skills and confidence.

5. Which topic was the easiest and which was the most challenging?

Since I come from a Computer Science background, Python was relatively easy for me. However, Machine Learning was initially challenging because it involved many new concepts.

With regular practice, project work, and mentor guidance, I gradually became comfortable with Machine Learning and started enjoying topics like data cleaning, model building, and model evaluation.

6. How did you revise the concepts after every class?

Consistency was the key. After every class, I reviewed the concepts, practiced coding, and worked on projects. This regular learning habit helped me understand the topics much better.

7. Did you use any additional learning resources outside the course?

Yes. Along with the course materials, I regularly practiced using:

• Kaggle for Machine Learning projects
• HackerRank for Python programming
• LeetCode for coding practice
• SQL practice platforms

These resources helped me strengthen my practical skills.

8. What projects did you complete during your internship and training?

I worked on several real-world projects, including:

• Customer Churn Prediction
• LSTM-based AI projects
• Multiple Machine Learning applications

These projects became valuable discussion points during my interviews.

9. How did these projects help during your interview?

During the interview, I was asked in-depth questions about the projects I had completed.Since I had personally worked on them, I was able to explain the problem statement, approach, implementation, and results confidently. This significantly improved my interview performance.

10. How did you prepare for your interviews?

I mainly used the interview preparation materials provided during the course. I revised technical concepts, practiced coding regularly, reviewed my projects, and prepared thoroughly on everything mentioned in my resume.

11. Did you study Artificial Intelligence separately?

Although I enrolled in the Certified Data Scientist program, I independently learned AI topics through self-study. I explored AI projects, watched educational videos on YouTube, and continuously practiced to improve my understanding.

12. What role did mock interviews play in your preparation?

Mock interviews were extremely valuable.

Although I did not clear my first mock interview, the feedback helped me improve my communication skills, confidence, and thinking ability. I successfully cleared my second mock interview, which prepared me well for actual interviews.

13. What was your actual interview experience like?

I went through a single round of technical evaluation during the interview. The interviewer asked questions based on my resume, discussed my projects, tested my knowledge of Docker, and presented a few scenario-based questions. Overall, the interview focused more on evaluating my practical knowledge and problem-solving skills than just theoretical concepts.

14. What kind of scenario-based questions were asked?

Some of the questions included:

How would you build a ChatGPT-like application?

How would you design the backend for a metro station management system?

Questions related to AI system design and practical implementation.

These questions tested my analytical thinking and problem-solving skills.

15. Why did the interviewer ask about Docker?

I had mentioned Docker in my resume because I had completed a Docker-based project during my college days. Since it appeared in my resume, the interviewer asked detailed questions to verify my practical understanding.

This taught me an important lesson: only include skills in your resume that you can confidently explain during an interview.

16. Did you receive support in building your resume?

Yes. The Placement Assistance Team (PAT) helped me prepare my resume and guided me on how to present my projects and technical skills effectively.

17. What advice would you give to freshers who want to enter AI and Machine Learning?

My advice to freshers is to stay consistent in learning and never get discouraged if some concepts seem difficult at first. Practice coding regularly, work on as many real-world projects as possible, and continue improving your skills through self-learning. Most importantly, stay confident and persistent throughout your journey, as continuous effort is the key to success in AI and Machine Learning.

18. What was your overall experience with the training and placement support?

My experience at DataMites was excellent. The mentors and Placement Assistance Team provided continuous support with learning, projects, resume building, and interview preparation, which helped me confidently secure an AI and Automation Intern opportunity. 

Refer to these articles:

• Data Scientist vs ML Engineer vs AI Engineer: Which Career Path Is Right for You?
• How Generative AI is Changing the Role of Data Scientists
• Guide to Artificial Intelligence Career

Kanchi Gupta’s Key Takeaways on Building a Career in AI

Kanchi’s journey highlights how consistent learning, practical experience, and continuous self-improvement can help fresh graduates build a successful career in Artificial Intelligence.

• Background: Kanchi Gupta is a Computer Science Engineering graduate who aspired to build a career in Data Science and AI.
• Training Choice: She enrolled in the Certified Data Scientist (CDS) program at DataMites after completing her graduation.
• Learning Focus: The course covered essential technologies such as Python, SQL, Machine Learning, Deep Learning, and Data Science.
• Hands-on Learning: Practical projects and assignments helped her strengthen her understanding of real-world AI and Machine Learning concepts.
• Mentorship Support: DataMites mentors guided her throughout her learning journey, helping her overcome technical challenges and complete projects successfully.
• Self-Learning Approach: Along with the course, she enhanced her AI knowledge through self-study using YouTube and continuous practice.
• Practice Platforms: She regularly used Kaggle for Machine Learning projects and HackerRank and LeetCode to improve her Python and SQL skills.
• Project Experience: She completed multiple real-world projects, including Customer Churn Prediction and LSTM-based AI projects, which strengthened her practical knowledge.
• Interview Preparation: The study materials, resume guidance, and mock interviews provided by DataMites helped her prepare confidently for technical interviews.
• Mock Interview Benefits: Although she didn't clear her first mock interview, the experience improved her communication skills, confidence, and interview performance.
• Technical Interview Success: Her interview focused on resume-based questions, project discussions, Docker, and scenario-based problem-solving, where her practical knowledge helped her perform well.
• Resume Preparation: The Placement Assistance Team (PAT) at DataMites supported her in building a professional resume and preparing for interviews.
• Career Achievement: Her consistent learning and project experience helped her secure an AI and Automation Intern opportunity.
• Learning Mindset: She believes that regular practice, project-based learning, and continuous improvement are essential for success in AI.
• Advice for Freshers: Kanchi encourages aspiring AI professionals to stay consistent, work on real-world projects, practice coding regularly, and never stop learning.
• Outcome Summary: Her journey demonstrates that with structured training, practical experience, mentor guidance, and self-learning, fresh graduates can confidently launch a successful career in Artificial Intelligence.

Refer to these articles:

• Manikanta’s Career Transition into Software Python Developer
• How Dinkar Cracked His First Agentic AI Engineer Job as a Fresher
• Rohini’s Inspiring Journey from Fresher to AI Engineer

If Kanchi Gupta's success story has inspired you to build a career in Artificial Intelligence, taking a structured learning path can be the perfect first step. Kanchi began her journey with DataMites, where she gained practical expertise in Python, SQL, Machine Learning, and Deep Learning through hands-on projects and mentor guidance. If you're looking to follow a similar path, the Artificial Intelligence Course in Pune offered by DataMites provides industry-focused training, practical project experience, and placement support to help learners prepare for rewarding AI careers.

DataMites Institute offers a comprehensive 9-month Artificial Intelligence program designed to equip learners with practical AI skills through real-world projects, hands-on training, and industry-focused learning. The program prepares aspiring professionals for roles such as AI Engineer, Machine Learning Engineer, AI Specialist, and NLP Professional, while also providing globally recognized certifications from IABAC and NASSCOM FutureSkills. In addition to technical training, learners receive dedicated mentorship, resume-building support, mock interviews, and placement assistance to enhance their career readiness.

With a presence in over 30 training locations across India, DataMites brings professional Artificial Intelligence education closer to aspiring learners. Students can access classroom training at major centers, including the Artificial Intelligence Courses in Bangalore, along with locations in Chennai, Pune, Mumbai, Hyderabad, Ahmedabad, and Delhi. Each center emphasizes experiential learning through practical projects, an industry-focused curriculum, and expert mentorship, helping learners build strong foundations for successful careers in Artificial Intelligence.