From Fresher to AI Engineer – Darshan’s Success Story

Breaking into the world of Artificial Intelligence can feel like climbing a mountain especially for fresh graduates with little to no industry experience. Yet, some stories prove that with the right mindset, skills, and guidance, the climb is not only possible but rewarding. This is exactly what happened with Darshan, a BCA graduate who transformed his career path from a fresher with big dreams to a successful AI Engineer. His journey is a testament to how determination, continuous learning, and the right training can turn ambition into achievement.

Q&A with Darshan – Insights, Struggles, and Guidance for Aspiring Data Experts

In this exclusive Q&A, Darshan opens up about his journey, the hurdles he faced, the lessons he learned, and the skills that shaped his career. His story offers practical guidance and inspiration for aspiring data experts aiming to break into the field.

Q1: Can you tell us about your background and how you entered data science?

I graduated with a Bachelor of Computer Applications (BCA). After my graduation, I enrolled in a certified data scientist course. During the course, I gained expertise in Python, SQL, statistics, machine learning, deep learning, and Natural Language Processing (NLP). Along with the training, I completed four capstone projects and one client-based project, which gave me real-time experience.

Q2: Did your programming background help in your learning journey?

Yes, I already knew the basics of Python before starting. That made the programming part easier. However, I spent more time understanding statistics and machine learning. Initially, I struggled with implementing ML algorithms in code, but with consistent practice, I became confident.

Q3: How much time did you dedicate daily for learning and practice?

On average, I spent 4 hours daily—1.5 to 2 hours attending classes and 2 additional hours revising concepts and practicing projects. Regular practice was key to building confidence.

Q4: Could you share more about the projects you worked on?

Yes, I worked on:

• Flight Price Prediction
• Rice Leaf Disease Detection using CNN
• River Flow Prediction
• House Price Prediction
• Sales Effectiveness (client-based project)

These projects exposed me to both machine learning and deep learning techniques. Working with SQL was also crucial, as the client project required extracting and analyzing data from databases.

Q5: How was your experience with placement services and interviews?

The placement support was very responsive. I attended three interviews in total. My first interview didn’t go well due to personal reasons, the second was for a Python Developer role, and finally, I succeeded in the third one, securing a position with Data Spark AI in Chennai.

Q6: As a fresher, did you believe it was possible to land a job in data science?

Yes, I always believed in hard work. Many people said it’s difficult for freshers, but I didn’t pay attention to negative comments. Instead, I focused on projects, continuous learning, and upgrading my skills. Eventually, that hard work paid off.

Q7: Are there really opportunities for freshers in data science?

Absolutely. In fact, a large portion of data science jobs are open to freshers. Industry experts often mention that around 50% of opportunities are for entry-level candidates. The demand for skilled professionals is huge, and as long as you can showcase your skills, you can grab these opportunities.

Q8: Did you face failures in interviews? How did you handle them?

Yes, I failed in my first two interviews. But I didn’t give up. Failures are part of the process. After each rejection, I analyzed my mistakes, worked on my weaknesses, and prepared better for the next opportunity. My family also supported me a lot during this time, which kept me motivated.

Q9: What was the most important lesson you learned during your preparation?

The most important lesson was:

• Master the basics first – Python, SQL, and statistics.
• After that, keep learning new and trending skills like NLP, computer vision, and deep learning.
• Always showcase your work on GitHub and LinkedIn through projects and portfolios.
• This approach helps you stay relevant and confident during interviews.

Q10: Can you share an AI project you worked on?

Yes, I worked on multiple AI projects including NLP-based solutions. For example, I followed tutorials to build a simple chatbot and learned about implementing NLP models. I also practiced through datasets on platforms like Kaggle, though I preferred working in Jupyter Notebook for hands-on implementation.

Q11. How many interview attempts does it usually take to land a job?

There’s no fixed number. Some people clear interviews on their first attempt, while others may need five or more tries. Interestingly, someone who succeeded after several attempts often ends up with a better job offer than someone who cleared on the first try. What matters most is how well your skills match the job requirements and how effectively you can present them in interviews.

Q12. How was the experience with DataMites training and placement support?

Without DataMites, as a BCA student, I might not have broken into this field. The trainers were very friendly, patient, and supportive. The placement team constantly followed up, provided transparent mock tests with scoring, and helped until I got placed.

Q13. What’s the most important mindset for aspiring data scientists?

Just put in your efforts and stay consistent. Hope for the best but focus on daily learning.

Refer these below articles:

• Junaid’s Path to MLOps Excellence: Data Meets Deployment
• Marketing Analyst to Generative AI Engineer: Keerthan’s Inspiring Journey
• From Learner to Leader: Chandan’s Inspiring Journey as an AI Lead

Key Findings from Darshan’s Journey

• Educational Background – Transitioned from a BCA degree to data science by pursuing a certified data scientist course.
• Skill Development – Build expertise in Python, SQL, statistics, machine learning, deep learning, and NLP through structured learning and hands-on projects.
• Project Experience – Completed multiple projects, including Flight Price Prediction, Rice Leaf Disease Detection (CNN), River Flow Prediction, House Price Prediction, and a client-based Sales Effectiveness project.
• Learning Discipline – Dedicated ~4 hours daily to learning (classes + self-practice), emphasizing consistent practice for confidence.
• Interview Journey – Faced failures in early interviews but stayed persistent, eventually landing a data science role at Data Spark AI, Chennai.

Read these below articles:

• How to Choose Best Institute for AI/ML in Chennai?
• How to Choose the Right AI/ML Institute in Hyderabad?
• What is a Convolutional Neural Network?

Darshan’s story proves that a fresher can crack a data science job with persistence, continuous learning, and confidence. His journey highlights the importance of mastering basics, building projects, and staying motivated even after failures. For anyone aspiring to start a career in data science and AI, his success story is a perfect example of how determination leads to results.

DataMites offers a comprehensive Artificial Intelligence training that is both career-oriented and beginner-friendly, catering to freshers as well as working professionals. For learners in areas like Kudlu Gate, BTM Layout, Marathahalli, and nearby regions, the Artificial Intelligence Institute in Bangalore provides accessible training options with flexible schedules, expert guidance, and dedicated placement support making it easier to start or advance a career in AI.

Artificial Intelligence is rapidly transforming industries, and Chennai stands as a growing hub for this innovation. Whether you are a student eager to explore AI, a tech enthusiast, or a professional aiming to enhance your skills, this is the ideal time to step into the AI domain. Selecting the right artificial intelligence institute in Chennai can unlock promising career paths and equip you with the knowledge and tools to succeed in today’s data-driven world.