Data Analyst & ML Enthusiast
I am currently pursuing a B.Tech in Computer Science and Engineering with Specialization in Big Data Analytics at SRM Institute of Science and Technology, Chennai, maintaining a strong academic record with a GPA of 9.59/10. My coursework in Database Management Systems (DBMS), Python, Data Science, Business Intelligence and Analytics, Data Mining and Analytics, and Data Warehousing has provided me with a solid foundation in data analysis and problem-solving, equipping me to tackle complex challenges effectively.
Driven by a passion for data, I have developed expertise in key tools and technologies, including Python (Pandas, NumPy, Matplotlib, Seaborn), SQL, Power BI (including DAX), Tableau, and Microsoft Excel. I am proficient in data preprocessing, machine learning, and statistical analysis, enabling me to extract valuable insights from data. Eager to continuously expand my skill set, I embrace challenges that push me to innovate and refine my analytical approach.
Python
SQL
Power BI
Machine Learning
Tableau
Excel
Jupyter Notebook
Developed a binary classification model to predict fraudulent credit card transactions using machine learning techniques. The project utilized data preprocessing, class imbalance handling, and model evaluation to achieve high accuracy and low false positive rates.
Designed an interactive Power BI dashboard for Maven Market to analyze 1997–1998 sales data, uncovering key KPIs such as sales trends, customer demographics, and regional performance. Delivered actionable insights to optimize sales strategies and product performance.
Performed an in-depth exploratory data analysis on the Global Terrorism Database, analyzing over 7,000 worldwide incidents. The project involved data cleaning, visualization, and trend identification to uncover patterns in terrorism events across different regions and time periods.
Analyzed Netflix's movie and TV show data using Tableau, focusing on trends in genres, ratings, and release dates. The project involved data cleaning, visualization, and uncovering insights into viewing patterns, popular genres, and user preferences.
Microsoft Learn
Issue Date: May 29, 2024
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