First Steps in Data Science: Shreenidhi’s Journey to Success

Breaking into data science can be challenging, especially for those coming from a non-technical background. However, with the right guidance and perseverance, success is achievable. Meet Shreenidhi, a determined professional who transitioned from mechanical engineering to data science. His story with DataMites is a testament to how structured learning and persistence can pave the way to a rewarding career in AI and machine learning.

His comprehensive Data Science training at Datamites provided hands-on experience in Python, statistics, and real-world projects. Shreenidhi’s story offers valuable insights and practical advice for aspiring data scientists looking to make a successful career transition.

Shreenidhi’s Journey into Data Science with DataMites

Let’s explore the key insights from his journey.

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

Good afternoon. I’m Shreenidhi from Shivamoga, Karnataka. I completed my engineering at Dayananda Sagar College of Engineering in Bangalore with a degree in mechanical engineering. After graduation, I worked as a Computer-Aided Engineer (CAE) in a small company for two years, but the salary growth wasn’t promising. My parents and I decided that it was time to explore new opportunities.

Q2: What led you to pursue a career in data science?

After working as a mechanical engineer, I realized that my field wasn’t offering the growth or financial rewards I hoped for. I began exploring various IT courses—like software development, testing, and web or app development but then someone suggested that I look into AI and machine learning. Initially, I thought AI/ML was only for computer scientists, but after researching online, I discovered DataMites, which opened up a whole new world for me.

Q3: How did you decide to join DataMites, and what was your experience like?

I visited the DataMites office, spoke with the team, and was impressed by the opportunities and support they offered for placements. I joined DataMites data science course at the end of December 2023, started my course in January 2024, and completed it by August 2024. During the program, I learned programming with Python, AI, machine learning, and deep learning. We even engaged in internships, capstone projects, and group projects with teams of five to six people. It was an immersive, hands-on learning experience that transformed my perspective.

Q4: How was your experience with DataMites’ training program?

My experience at DataMites was fantastic. I enrolled in January 2024 and completed the program by August 2024. The course covered essential topics such as:

• Python Programming: Strengthening my coding skills and learning object-oriented programming.
• Machine Learning & AI: Understanding different ML algorithms, deep learning, and NLP.
• Hands-On Projects: Working on real-world datasets, which helped me build my portfolio.
• Placement Support: The mock interviews and resume-building sessions played a crucial role in my job search.

The structured approach made it easier for me to grasp complex concepts and apply them in practical scenarios.

Q5: How did you handle the transition from a mechanical engineering background to learning programming and data science?

While I had some exposure to programming during my engineering—using C and C++ I found Python relatively simple once I started the course. DataMites focused on teaching the basics: learning Python data structures and even some object-oriented programming. For someone coming from a non-IT background, the emphasis was on understanding the fundamentals rather than advanced coding techniques.

Q6: Do you think extensive mathematics knowledge is required for Data Science?

Not at all. A strong grasp of basic math concepts—such as calculus and differentiation—is more than enough. Employers are more interested in how well you can apply these concepts to solve real-world problems rather than deep theoretical knowledge.

Q7: Can you share details about your interview process and the challenges you faced?

After completing the course, I cleared my mock interviews with support from the DataMites team. The interview process was rigorous. I faced several rounds, including questions on Python programming, statistics, and details about my projects like explaining my work on machine learning projects and discussing topics in NLP and generative AI. Although I encountered multiple rejections, each experience helped me improve my skills and prepare better for the next opportunity. 

Q8: What strategies helped you improve your coding and problem-solving skills?

I focused on:

• Consistent Practice: I dedicated 3-4 hours daily to coding exercises and projects.
• Strengthening Fundamentals: I ensured that my understanding of Python basics, data structures, and object-oriented programming was strong.
• Using AI Tools: I leveraged ChatGPT and other online resources for quick clarifications.
• Engaging in Peer Learning: Participating in discussions, hackathons, and study groups helped me stay motivated.

Q9: How did DataMites help you with resume building and networking?

Initially, I struggled with presenting my skills effectively on my resume. The DataMites placement team helped me refine my resume with a structured format, emphasizing my projects and technical skills. They also guided me on optimizing my LinkedIn profile, which increased my visibility to recruiters. Additionally, attending career fairs organized by DataMites helped me connect with potential employers.

Q10: What role have you secured, and what are your future plans?

I’m thrilled to announce that I have landed a role as a Data Scientist with Shyena Tech Yarns. Although the company is primarily based in Pune, I will be transitioning from Bangalore. My goal is to continuously grow and eventually advance to a more strategic role in data science, where I can combine my domain expertise with cutting-edge AI techniques.

Q11: What advice do you have for aspiring data scientists, especially those coming from non-technical backgrounds?

Don’t be discouraged by your background. Focus on building a strong foundation in programming and data analytics, learn Python basics, practice coding consistently, and don’t shy away from working on projects. Also, make sure to build a compelling resume; the support from DataMites in this area was invaluable. Remember, the field of data science is constantly evolving, so continuous learning is key. Even if you come from a non-technical field, your unique domain knowledge can add significant value.

Refer to this article: Mohammed Imran’s Data Science Career Success Story

Key Takeaways from Shreenidhi’s Journey

Shreenidhi’s transition from mechanical engineering to data science is a testament to the power of structured learning and persistence. Here are the key lessons from his inspiring journey:

• Career Transition: Shreenidhi moved from a mechanical engineering background to data science after realizing the limited financial growth in his field.
• Motivation to Switch: The low salary growth in mechanical engineering, combined with family guidance, motivated him to explore new opportunities in IT.
• Discovery of DataMites: After researching various IT courses, he found DataMites and was impressed with its training and placement support.
• Intensive Training: He joined DataMites at the end of December 2023, completed the course by August 2024, and gained hands-on experience with projects, internships, and group collaborations.
• Learning Fundamentals: The program focused on Python, machine learning, AI, and deep learning, making the transition smoother despite his non-technical background.
• Overcoming Challenges: Despite facing multiple interview rejections, he improved his technical and conceptual understanding, particularly in NLP, generative AI, and statistical concepts.
• Successful Placement: His perseverance paid off as he secured a Data Scientist role at Shyena Tech Yarns, marking a significant career milestone.
• Practical Advice: He emphasizes consistent practice, strong resume preparation, and continuous learning, proving that even non-technical professionals can succeed in data science.

Shreenidhi’s inspiring journey from mechanical engineering to data science highlights the power of structured learning, dedication, and perseverance. His success story proves that transitioning into data science is achievable for professionals from non-technical backgrounds with the right guidance and resources.

Refer to these articles:

• Why Data Scientist Career in Bangalore
• Why Data Scientist Career in Chennai
• Why Data Scientist Career in Hyderabad

If you want to seize opportunities in the rapidly growing field of data science, enroll in the best data science courses in Chennai, Hyderabad, Bangalore, Pune, Mumbai, Delhi, Ahmedabad, and other major cities. According to a 2024 NASSCOM report, India’s demand for data science professionals is expected to grow by 45% annually, with over 11 million job openings by 2026. Ensure the institute provides hands-on projects, internship opportunities, and placement support to stay ahead in this competitive industry.

DataMites Institute is a leading institute offering specialized data science courses in AI, Machine Learning, Python Development, Data Analytics, and Certified Data Scientist programs. Accredited by IABAC and NASSCOM FutureSkills, it delivers high-quality education led by industry experts.

The institute provides hands-on training, placement assistance, and internship opportunities, ensuring students gain real-world experience and stay updated with industry advancements. DataMites offers offline data science courses in Bangalore, Hyderabad, Chennai, Pune, Ahmedabad, Coimbatore, and Mumbai.

With expert mentors, industry-driven training, and a strong placement record, DataMites empowers aspiring data scientists. Whether you're a fresh graduate, working professional, or career changer, it offers a structured pathway into the world of Data Science, AI, and Machine Learning.