I am a B.Tech CSE-AI/ML student at Indore Institute of Science & Technology (IIST), graduating in 2028, with a current CGPA of 8.09.
I am building my career toward Data Analytics, with a strong interest in using data to understand patterns, measure performance, uncover insights, and support better decisions.
My core analytical toolkit includes Python, SQL, Excel, Pandas, NumPy, Statistics, Power BI, Tableau, Matplotlib, and Scikit-learn. Through academic work, projects, and hands-on learning, I am developing experience across the complete analytical workflow:
Data → Cleaning → Exploration → Analysis → Visualization → Insights
My AI/ML background complements my analytics skills by giving me a foundation in predictive modeling, machine learning algorithms, and data-driven problem solving.
I am currently focused on becoming a well-rounded Data Analyst who can combine technical analysis with business understanding and clear data storytelling.
- Data Analyst Internships
- Data Analytics Opportunities
- Business Intelligence Intern
- AI/ML Internships
- Research Opportunities
- Open Source Contributions
Python • C++ • SQL
MySQL • Relational Databases
Pandas • NumPy • Exploratory Data Analysis • Data Cleaning • KPI Analysis • Feature Engineering
Power BI • DAX • Power Query • Excel • Tableau • Matplotlib • Seaborn
Scikit-learn • Regression • Classification • Clustering • Statistics • Probability
Git • GitHub • VS Code • Jupyter Notebook • Microsoft Excel
| Domain | Proficiency | Details |
|---|---|---|
| Python & Data Analysis | 🟣 Intermediate | Pandas, NumPy, data manipulation, analytical workflows |
| SQL & Databases | 🟣 Intermediate | Queries, joins, filtering, aggregation, relational data |
| Data Cleaning | 🟣 Intermediate | Missing values, duplicates, transformations, data preparation |
| Exploratory Data Analysis | 🟣 Intermediate | Distributions, correlations, patterns, statistical exploration |
| Data Visualization | 🟣 Intermediate | Power BI, Tableau, Matplotlib, Seaborn |
| Business Intelligence | 🟣 Developing | Dashboards, KPIs, Power Query, DAX |
| Statistics & Probability | 🟣 Developing | Descriptive statistics, probability, analytical reasoning |
| Machine Learning | 🟣 Developing | Scikit-learn, regression, classification, clustering |
| Predictive Analytics | 🟣 Developing | Applying ML techniques to structured datasets |
| AI / ML Concepts | 🟣 Developing | Core AI/ML concepts through academic learning and projects |
📊 Indian Job Market Intelligence
A data analytics project focused on understanding the job market, hiring trends, demanded skills, and role patterns through structured job-listing data.
| Category | Details |
|---|---|
| Stack | Python • Pandas • SQL • MySQL |
| Focus | Data Collection • Cleaning • Analysis • Database Management |
| Analysis | Job Roles • Skills • Hiring Trends • Market Patterns |
| Repository | GitHub Project |
- Collected and structured job-market information
- Performed data cleaning and preprocessing
- Stored structured data using MySQL
- Created database views for analytical use
- Analyzed job roles and skill requirements
- Used Python and Pandas for data analysis
- Explored patterns in the evolving job market
- Designed the project around practical data-driven decision making
🤖 AI Bazaar
A hackathon project combining AI, retail operations, data processing, and dashboards to create a technology-driven retail solution.
| Category | Details |
|---|---|
| Stack | Python • Flask • Supabase • HTML • CSS • JavaScript |
| Focus | Retail Analytics • Dashboard • Backend • Database |
| Analysis | Sales Data • Business Insights • Retail Information |
| Repository | GitHub Project |
- Worked on a retail-focused AI solution
- Built backend functionality using Flask
- Integrated structured data using Supabase
- Developed dashboard-based analytical workflows
- Worked with data uploads and business information
- Connected application components into an end-to-end system
- Applied data and AI concepts to a real-world business problem
- Developed the project in a competitive hackathon environment
🎓 Student Placement Predictor
A machine learning project focused on using student-related data to build a predictive model for placement outcome analysis.
| Category | Details |
|---|---|
| Stack | Python • Pandas • NumPy • Scikit-learn |
| Focus | Data Preparation • EDA • Machine Learning |
| Analysis | Student Attributes • Predictive Patterns • Placement Outcomes |
| Repository | GitHub Project |
- Prepared and explored structured student data
- Performed exploratory data analysis
- Cleaned and transformed relevant features
- Applied machine learning techniques
- Studied relationships between student attributes and outcomes
- Evaluated model predictions
- Built an end-to-end predictive analytics workflow
| Certification | Platform |
|---|---|
| Data Science Virtual Experience / Simulation | Deloitte Forage |
| Data Analytics Essentials | Cisco Networking Academy |
