IBM: Analyzing Data with Excel course Syllabus

Full curriculum breakdown — modules, lessons, estimated time, and outcomes.

This course is designed for beginners and provides a practical introduction to analyzing data using Microsoft Excel. Over approximately 8–11 weeks, learners will build foundational skills in data cleaning, analysis, and visualization using real-world datasets. With a hands-on approach, each module combines guided exercises and practical applications to help learners turn raw data into meaningful insights. The course requires no prior experience with data analysis, making it ideal for those starting a career in analytics or business intelligence.

Module 1: Introduction to Data Analysis with Excel

Estimated time: 6 hours

Overview of Excel as a data analysis tool
Understanding datasets and data types
Basic spreadsheet navigation and operations
Setting up Excel for efficient analysis workflows

Module 2: Data Cleaning and Preparation

Estimated time: 10 hours

Cleaning and formatting raw data
Handling missing values and duplicates
Identifying and correcting data inconsistencies
Using sorting, filtering, and conditional formatting

Module 3: Data Analysis with Functions and PivotTables

Estimated time: 12 hours

Applying essential functions: SUMIFS, COUNTIFS, IF
Using VLOOKUP and XLOOKUP for data matching
Building and customizing PivotTables
Exploring data relationships and comparisons

Module 4: Data Visualization and Reporting

Estimated time: 10 hours

Creating charts to visualize data trends
Designing visual summaries with best practices
Building simple dashboards and reports
Communicating insights clearly to stakeholders

Module 5: Descriptive Analysis and Insight Generation

Estimated time: 8 hours

Performing descriptive analysis on datasets
Identifying trends, patterns, and outliers
Using Excel tools to support data-driven decisions
Practicing analytical thinking with real-world examples

Module 6: Final Project