Data Science | Machine Learning | Python Developer
Data Science undergraduate at R.V.R & J.C. College of Engineering (CGPA: 7.82) with expertise in Python, SQL, and Machine Learning. Experienced in building practical AI applications and data-driven solutions.
R.V.R & J.C. College of Engineering
Data Science undergraduate & software developer
I am a Data Science undergraduate at R.V.R & J.C. College of Engineering pursuing a Bachelor of Technology in Computer Science and Engineering (Data Science), currently maintaining a CGPA of 7.82.
My academic and technical trajectory is anchored in a solid foundation of Python, SQL, and Machine Learning. I possess hands-on experience developing web applications, analyzing structured and unstructured data, and architecting practical software solutions to tackle complex real-world challenges.
I am actively seeking software development and data-driven roles where I can leverage my analytical capabilities, machine learning expertise, and programming foundation to build scalable, high-impact systems.
Data analysis, exploratory processing, and structured problem solving.
Practical ML, CNN image classification, NLP, and model evaluation.
Building functional web and data applications with Python, Flask, and Streamlit.
Academic qualifications & achievements
Comprehensive curriculum covering Data Science, Machine Learning, Deep Learning, Database Management Systems, and Software Application Development.
Rigorous coursework with a focus on Mathematics, Physics, and Chemistry, cultivating quantitative and analytical foundations.
Completed secondary education with an exemplary 100% academic record, establishing a strong academic foundation.
Technologies, frameworks, and core competencies
Industry training & practical technical programs
Completed an 8-week Data Analytics Virtual Internship under AICTE EduSkills, gaining practical exposure to industry-oriented data analytics concepts.
Worked on data analysis, machine learning, and model implementation using real-world datasets. Applied data preprocessing and problem-solving techniques in practical scenarios.
Completed a 4-week virtual internship focused on Artificial Intelligence and Microsoft Azure cloud technologies. Gained practical exposure to AI concepts, Azure services, and cloud-based AI solution development.
Learned machine learning concepts, cloud-based AI services, and practical implementation of AI/ML solutions using AWS technologies.
Data science, machine learning, and application development
Verified professional credentials & learning programs
Specialized certification in AI Vector Search architectures, semantic similarity search, and high-dimensional vector embeddings within enterprise data platforms.
Core certification validating fundamental knowledge of Artificial Intelligence, Machine Learning concepts, and AI services deployed on Oracle Cloud Infrastructure.
Hands-on job simulation covering business data interpretation, executive presentation of insights, and interactive data visualization for decision-makers.
Comprehensive learning program covering Artificial Intelligence fundamentals, machine learning models, and modern algorithmic paradigms.
Interested in data-driven roles and software engineering opportunities