Data Analysis BootCamp

In this lecture, we dive into Excel as a foundational tool for data analysis. You'll learn how to navigate the interface, organize your data efficiently, and use basic to intermediate features like conditional formatting, filtering, and formulas. This lecture sets the stage for transforming raw data into clear, structured insights.

In this lecture, you’ll learn the fundamentals of Power BI — a powerful business intelligence tool used to connect, transform, and visualize data. We’ll cover how to import datasets, clean data using Power Query, and build interactive visualizations and dashboards. You’ll also get introduced to DAX (Data Analysis Expressions) to create calculated columns and measures. By the end of this lecture, you’ll be able to build and publish your first Power BI report.

In this lecture, you’ll learn the core concepts of SQL — the standard language for querying databases. We’ll start by understanding database structure, then move to writing basic SQL statements such as SELECT, WHERE, ORDER BY, and JOIN. You’ll practice extracting, filtering, and combining data from multiple tables. By the end of this lecture, you’ll be able to write queries to retrieve meaningful insights from real-world datasets.

In this lecture, you’ll be introduced to Python as a powerful tool for data analysis. We’ll cover the basics of Python syntax, variables, data types, and working with Jupyter Notebook. Then, we’ll dive into using essential libraries like Pandas for data manipulation and Matplotlib for data visualization. By the end of this lecture, you’ll be able to load datasets, clean them, and generate visual insights using Python.