▪ Foundational Python Programming – From syntax and loops to file handling, tailored for data tasks.

▪ Data Manipulation with Pandas – Real-world case studies using Series, DataFrames, merging, cleaning, filtering, groupby, etc.

▪ Numerical Operations with NumPy – Efficient handling of arrays, reshaping, broadcasting, and statistical operations.

▪ Data Visualization – Master charts, dashboards, and storytelling using Matplotlib, Seaborn, and Power BI.

▪ SQL for Analysts – Writing complex queries, joins, subqueries, aggregates, views, and stored procedures.

▪ Advanced Excel for Analytics – Lookup functions, pivot tables, Power Query, What-if Analysis for dynamic insights.

▪ Google Data Studio – Create visually appealing dashboards with filters and interactive elements.

▪ Statistics & Probability – Learn concepts like mean, median, standard deviation, distributions, and hypothesis testing.

▪ Product & Business Analysis – Retention metrics, cohort analysis, user behavior and funnel analysis.

▪ Basic Machine Learning – Classification, regression, model evaluation using scikit-learn.

▪ GenAI for Data Analysts – Automate report generation, smart dashboards, AI-powered insights & prompt engineering.

▪ Capstone Project – Full-scale real-world project combining tools and techniques learned.

▪ Placement Support – 1-on-1 interview prep, resume & LinkedIn optimization, mock interviews, and job referrals.