IBM Data Analyst Capstone Project Course Syllabus

Overview: This capstone course is the final step in IBM's Data Analyst Professional Certificate, designed to validate your end-to-end data analysis skills. Over approximately 5 weeks with a flexible schedule, you'll work through a real-world dataset to complete a comprehensive analytics project. Each module guides you through a key phase of the data analysis pipeline—problem definition, data cleaning, exploration, visualization, and reporting—culminating in a peer-reviewed final submission. Expect to spend roughly 3–5 hours per module, combining hands-on coding in Jupyter Notebook, Python, Pandas, SQL, and Excel with practical decision-making and storytelling. This project is ideal for building a professional portfolio and demonstrating job-ready competencies.

Module 1: Introduction and Project Scenario

Estimated time: 4 hours

• Understanding the business problem
• Project overview and goals
• Reviewing the real-world dataset
• Defining project objectives and success criteria

Module 2: Data Wrangling and Preprocessing

Estimated time: 5 hours

• Cleaning and formatting data
• Handling missing values and duplicates
• Data validation techniques
• Using Python and Pandas for data preparation

Module 3: Exploratory Data Analysis (EDA)

Estimated time: 5 hours

• Identifying patterns and trends in data
• Detecting outliers and anomalies
• Applying descriptive statistics
• Performing EDA using Matplotlib and Seaborn

Module 4: Data Visualization and Reporting

Estimated time: 5 hours

• Creating effective data visualizations
• Practicing visual storytelling techniques
• Building insights dashboards
• Writing a comprehensive project report in Jupyter Notebook

Module 5: Final Project Submission

Estimated time: 4 hours

• Compiling analysis results
• Documenting insights and recommendations
• Preparing peer-reviewed assignment

Module 6: Final Project

Estimated time: 3 hours

• Deliverable 1: Complete Jupyter Notebook with cleaned data and code
• Deliverable 2: Data visualization dashboard and charts
• Deliverable 3: Final project report with actionable insights

Prerequisites

• Familiarity with Python, Pandas, and Jupyter Notebooks
• Experience with SQL and Excel for data manipulation
• Completion of prior courses in the IBM Data Analyst Professional Certificate

What You'll Be Able to Do After

• Apply the full data analysis process to real-world datasets
• Perform data wrangling and cleaning using Python and Pandas
• Conduct exploratory data analysis with statistical and visualization tools
• Create compelling data visualizations and dashboards
• Produce a professional analytics report for portfolio or employment