Applied Data Analytics

Intermediate

This course takes students beyond Python fundamentals into practical data analytics. You will learn how to work with databases and SQL, perform advanced data analysis and exploratory data analysis using Python, apply statistical concepts to real datasets, build interactive dashboards with Power BI, and manage analytical projects using Git and GitHub. The course focuses on hands-on practice, real-world datasets, and end-to-end projects that turn raw data into actionable insights.

Weeks

Modules

Registration open

Prerequisites

Python fundamentals, basic programming concepts, and familiarity with basic mathematics. Students should be comfortable with variables, functions, loops, lists, dictionaries, and basic Python syntax.

Hands-on Projects

Build real-world skills

Expert Mentors

Guidance throughout

Certificate

Upon completion

Curriculum

Statistics for Data Analysis

Build a strong statistical foundation for data analysis. Learn descriptive statistics, probability, distributions, sampling, confidence intervals, hypothesis testing, correlation, and regression concepts, with a focus on interpreting statistical results in real-world datasets.

Databases & SQL

Learn how data is stored, structured, and queried in relational databases. Work with SQL to retrieve, filter, aggregate, join, and transform data, progressing to advanced queries using CTEs, subqueries, CASE statements, and window functions.

Advanced Data Analysis with Python

Apply Python to real-world data analysis using NumPy and Pandas. Learn data loading, cleaning, transformation, aggregation, merging, missing-value handling, and advanced DataFrame operations to prepare datasets for deeper analysis.

Exploratory Data Analysis & Visualization

Discover patterns, relationships, trends, and anomalies within datasets through systematic exploratory data analysis. Use Matplotlib, Seaborn, and Plotly to create informative visualizations and communicate analytical findings effectively.

Power BI & Business Intelligence

Transform analyzed data into interactive business intelligence dashboards using Power BI. Learn Power Query, data modeling, relationships, DAX, measures, KPIs, filters, and dashboard design to communicate insights and support data-driven decisions.

Git & GitHub for Data Analytics

Learn professional version control and project management workflows for data analytics. Use Git and GitHub to track changes, manage branches, document projects, collaborate with others, and build a professional data analytics portfolio.

End-to-End Data Analytics Projects

Apply the complete data analytics workflow to real-world datasets. Combine statistics, SQL, Python, exploratory analysis, visualization, Power BI, and GitHub to transform raw data into actionable insights and present professional analytical projects.