Anjali Vishwari

I am currently pursuing my MCA with a specialization in Data Science and AI. My interest lies at the intersection of Data Engineering and Data Science. I enjoy building scalable data pipelines and also extracting meaningful insights from data through analytics and machine learning.

I have experience working with Python, SQL, PySpark, Databricks, AWS S3, and Delta Lake. I have built ETL pipelines using Medallion Architecture and have developed machine learning models involving data preprocessing, feature engineering, and evaluation.

My strength lies in understanding the complete data lifecycle — from raw data ingestion and transformation to model development and insight generation. I am analytical, adaptable, and continuously learning to stay updated with evolving data technologies.

I am an MCA student specializing in Data Science and Artificial Intelligence, with hands-on experience in Data Engineering and Machine Learning. I have worked on building end-to-end ETL pipelines using Python, SQL, and PySpark, implementing Medallion Architecture (Bronze, Silver, Gold layers) for structured data processing. I have experience working with Databricks, Delta Lake, and AWS S3 for scalable data storage and transformation.

On the Data Science side, I have developed machine learning models involving data preprocessing, feature engineering, model training, and evaluation using libraries such as Pandas, NumPy, and Scikit-learn. I am comfortable working with both structured and semi-structured datasets and applying statistical and analytical techniques to extract meaningful insights.

I have a strong understanding of data warehousing concepts, distributed data processing, and performance optimization. I am detail-oriented, analytical, and passionate about solving real-world problems using data-driven approaches. I continuously strive to enhance my technical skills and stay updated with emerging tools and technologies in the data ecosystem.

I am currently pursuing a Master of Computer Applications (MCA) with a specialization in Data Science and Artificial Intelligence. My coursework has provided me with a strong foundation in Machine Learning, Statistics, Data Structures, Database Management Systems, and Big Data technologies.

During my academic journey, I have gained practical experience in Python, SQL, PySpark, and data analysis tools through various academic projects and hands-on implementations. I have worked on building ETL pipelines, implementing Medallion Architecture, and developing machine learning models involving data preprocessing, feature engineering, and model evaluation.

My education has helped me develop strong analytical thinking, problem-solving skills, and a deep understanding of the complete data lifecycle — from data ingestion and transformation to analytics and predictive modeling.