12 WEEKS
VIRTUAL &
PHYSICAL
PROJECTS/
ASSIGNMENTS
CERTIFICATION
What You’ll Learn
By the end of this course, you will:
- Master the art of data cleaning, manipulation, and visualization.
- Develop expertise in Excel, SQL, Python, and Power BI.
- Understand foundational statistics and machine learning concepts.
- Solve real-world data problems using integrated tools.
- Present actionable insights through compelling data visualizations.
₦220,000
Why Enroll?
In today’s data-driven world, understanding and effectively analyzing data is no longer optional—it’s a necessity. At Ibadan Digital Academy, our 12-week Data Analysis Curriculum is tailored to equip you with the essential tools, techniques, and knowledge to thrive in roles like data analyst, business analyst, or data scientist. This course combines hands-on learning with industry-standard tools like Microsoft Excel, SQL, Python, and Power BI to prepare you for real-world challenges.
Localized Relevance:
Work on datasets and projects related to Nigerian industries like finance, agriculture, and logistics.
Hands-On Learning:
Weekly projects provide practical experience with real-world applications.
Global Competitiveness:
Prepare for certifications like Microsoft Data Analyst Associate and learn industry-standard tools.
Expert Guidance
Learn from experienced instructors and mentors.
Capstone Project:
Showcase your expertise with a final project that solves real-world challenges.
Data Analysis Course Outline
Week 1: Introduction to Data Analysis and Tools
- Understand the importance and applications of data analysis.
- Explore data ethics and key tools like Excel, SQL, Python, and Power BI.
Week 2: Fundamentals of Excel
- Learn data cleaning, advanced formulas, pivot tables, and visualization basics.
Weeks 3–4: SQL for Data Analysis
- Develop skills in querying, joining tables, and using advanced SQL techniques.
Weeks 5–6: Python for Data Analysis and Visualization
- Master data manipulation with Pandas and visualization with Matplotlib and Seaborn.
Weeks 7–8: Power BI
- Build interactive dashboards and perform advanced calculations with DAX.
Week 9: Statistics for Data Analysis
- Analyze data using descriptive statistics, probability, and regression analysis.
Weeks 10–11: Machine Learning and Integrated Tools
- Learn basics of regression and classification, and combine SQL, Python, and Power BI.
Week 12: Capstone Project
- Solve a real-world problem and present your analysis using all the tools you’ve learned.
Tools Covered
