From Graduate to AI/Data Engineer : Sachin’s Journey into the AI

Imagine stepping out of college with a degree in hand, a head full of dreams, and a passion for artificial intelligence but no clear roadmap to turn that passion into a career. That was Sachin. Today, he’s a thriving AI/Data Engineer, contributing to cutting-edge projects at a fast-growing AI company. How did he bridge the gap between ambition and achievement? In this blog, we explore Sachin’s inspiring journey from a fresh graduate navigating uncertainty to becoming a confident professional in the AI industry. Whether you’re a student, a career-switcher, or simply curious about what it takes to break into AI, Sachin’s story offers practical insights, real challenges, and actionable advice you won’t want to miss.

Career Switch to AI/Data Engineer: Q&A with Sachin on His Successful Journey

Let’s explore the inspiring journey of Sachin Awati, a B.Tech graduate from Karnataka, who transitioned into the AI field after completing an artificial intelligence course. 

Q1: Can you tell us about yourself and your academic background?

Yes, my name is Sachin Awati. I’m from Vijayapura District, Karnataka. I graduated with a degree in Information Technology from BLD Engineering College in 2023. Soon after my graduation, I enrolled in Datamites for Certified Data Scientist Course in Bangalore. This course helped me build my technical foundation and eventually land a job in the AI field.

Q2: What was your motivation to pursue a career in data science?

During my engineering, I developed a deep interest in data and how algorithms work. In my final year, I worked on a project using machine learning, which really sparked my passion. That’s what motivated me to pursue a data science course and dive deeper into this domain.

Q3: Can you share more about your learning experience in the course?

Absolutely. I joined the Certified Data Scientist (CDS) offline batch in Bangalore. The major topics I studied were Python, machine learning, and statistics. I had excellent mentors Mr. Nikhil for machine learning, Kalpana Ma’am for Python, and Priyanshu Sir for statistics. The explanations were smooth, and the training materials, including the hard copy books, were extremely helpful.

Q4: What kind of projects did you work on during the course?

We completed four capstone projects:

• House Price Prediction
• Rice Leaf Disease Detection
• Skin Disorder Classification
• Customer Churn Prediction (Client Project)

These projects gave me practical, hands-on experience with real-world datasets. I worked with a team of two other learners, and we received an A+ grade for our performance.

Q5: How many hours did you study daily, and what resources did you use?

On average, I studied for 2 hours a day, sometimes up to 4. I did full-time learning and regularly attended sessions at the training center. Apart from the course materials, I explored trending topics like LLMs (Large Language Models), LangChain, and Generative AI using online platforms like YouTube.

Q6: How did you prepare for your job interviews?

Before cracking the final interview, I attended two offline interviews where I faced technical and real-world problem-solving questions. I learned from each experience and focused on improving my knowledge of ChatGPT, chatbot development, NLP applications, and project execution.

Most questions were project-related: how I handled real-world problems, implemented machine learning models, and worked as a team. One company asked for a basic data visualization coding task during the interview.

Q7: What was the learning journey like during the DataMites capstone project?

The capstone project helped me understand the end-to-end process of building a machine learning project. I started by learning essential steps like data preprocessing, visualization, and implementing ML algorithms. Finally, we deployed the project on the AWS EC2 platform, which gave us hands-on experience with cloud deployment.

Q8: How many mock interviews did you attend before landing the job?

I attended just one mock interview. I cleared the actual interview in my first attempt and received a package of ₹5.9 LPA.

Q9: What tools and platforms are used for practicing data science projects?

Common platforms include Jupyter Notebook and VS Code for coding. For datasets, Kaggle is a popular and resource-rich platform. It’s also advisable to study different approaches used by top performers on the Kaggle leaderboard to gain new perspectives.

Q10: What was your job readiness score and placement experience?

I had a job readiness score of 5.9, just under 6, which is considered a good benchmark for placements. The placement support team helped me throughout the process, and their mock interview sessions gave me the confidence to perform better in actual interviews.

Q11: What tips do you have for aspiring data science professionals?

• Focus on Projects: Hands-on experience is key. Work on capstone projects and understand every step from data preprocessing to model deployment.
• Strengthen Fundamentals: Make sure your basics in Python, machine learning, and statistics are strong.
• Stay Updated: Learn about current trends like Generative AI, LangChain, and LLMs through YouTube or extra classes.
• Practice Interviews: Attend mock interviews and be ready to explain your projects clearly.

Refer these below articles:

• Aswathi’s Journey: From Electrical Engineer to AI/ML Engineer
• From Mechanical Engineer to AI/ML Engineer: Uday Bhaskar’s Journey
• From PhD to NLP Data Scientist: Samir’s Career Reinvention Journey

Highlights from Sachin’s Inspiring Journey into AI/Data Engineer

Sachin’s passion for data led him from college projects to completing an AI course and landing a role at DataSpark AI Solutions. His journey offers valuable insights for aspiring tech professionals.

Academic Background

• Sachin Awati is an IT graduate (2023) from BLD Engineering College, Karnataka.

Career Motivation

• A final-year machine learning project sparked his interest in data science and AI.

Training Experience

• Enrolled in the Certified Data Scientist (CDS) offline program in Bangalore.
• Learned Python, Machine Learning, and Statistics from expert mentors.

Daily Study Habits & Learning Resources

• Studied 2–4 hours daily.
• Follow online content on LLMs, LangChain, and Generative AI via YouTube.

Interview Preparation

• I attended two offline interviews before securing a job.
• Focused on project execution, NLP, and chatbot technologies.
• Faced coding and data visualization tasks during interviews.

Read these below articles:

• The Demand for Artificial Intelligence in Vizag
• The Rising Demand for Artificial Intelligence in Ghaziabad
• Why Artificial Intelligence is in High Demand in Kanpur

Sachin's journey from a small town in Karnataka to becoming a Data Engineer in the competitive AI industry shows that with determination, guidance, and consistent effort, a career in AI is achievable. His story highlights how curiosity can lead to capability and ambition to success. According to ABI Research, Generative AI is set to be the fastest-growing AI framework, with a 34.5% CAGR, driven by foundation models, optimization tools, and deployment software.

Hyderabad is home to numerous IT giants, research labs, and tech startups, making it a thriving ecosystem for AI innovation. Artificial Intelligence course in Hyderabad is designed to equip learners with both theoretical knowledge and practical skills in artificial intelligence. From the basics of machine learning to advanced topics like deep learning and natural language processing (NLP), a well-structured course covers it all.

Datamites Artificial Intelligence Institute in Hyderabad offers comprehensive training in core AI technologies, tailored to industry needs. Ideal for graduates, professionals, and career switchers, the program includes hands-on learning and leads to globally recognized certifications from IABAC and NASSCOM FutureSkills, enhancing career opportunities.