Data Analysis is one of the most essential skills in the digital era. This masterclass trains students to transform raw, unorganized datasets into meaningful insights through statistics, Python programming, visualization, and analytical reasoning. The course emphasizes real-world problem solving using tools such as Pandas, NumPy, and Matplotlib. Students learn how to clean data, identify patterns, build dashboards, and present insights effectively.
What you'll learn
MODULE 1: Data Analysis Basics (4 Hours)
- What data analysis is
- Types of data & data sources
- Data collection methods
- Data lifecycle overview
MODULE 2: Data Cleaning & EDA (4 Hours)
- Handling missing data & outliers
- Data formatting & standardization
- Basics of descriptive statistics
- Visual EDA (histograms, boxplots, trends)
MODULE 3: Data Manipulation (4 Hours)
- Working with Excel/Pandas
- Filtering, sorting & merging data
- GroupBy & pivot tables
- Creating new features/columns
MODULE 4: Data Visualization (4 Hours)
- Principles of good visualization
- Charts for trends, comparisons & distributions
- Dashboards using Power BI/Tableau
- Visual storytelling
MODULE 5: Insights & Mini Project (4 Hours)
- Turning analysis into insights
- Writing & presenting reports
End-to-end data analysis mini project
- Understand the complete workflow of transforming raw data into meaningful insights.
- Use Python libraries (Pandas, NumPy, Matplotlib) for data manipulation and visualization.
- Clean, preprocess, and analyze datasets using industry-relevant techniques.
- Perform Exploratory Data Analysis (EDA) to identify patterns and trends.
- Create compelling visualizations and dashboards for decision- making.
Develop and present a complete data analysis project based on real-world datasets.
