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This Data Analysis course is designed to help students, business professionals, and analysts gain the skills needed to make data-driven decisions. Learners will master the entire data analysis pipeline — from data collection and cleaning to analysis, visualization, and interpretation — using industry-standard tools.

The course is beginner-friendly, project-based, and focuses on real-world datasets to build confidence and prepare learners for careers in business analysis, research, reporting, or freelancing.

Module 1: Introduction to Data Analysis

  • What is Data Analysis?

  • Types of Data & Data Sources

  • The Data Analysis Lifecycle

  • Tools for Data Analysis: Excel, SQL, Power BI

  • Understanding KPIs, Metrics, and Dashboards

Module 2: Microsoft Excel for Data Analysis

  • Excel Interface & Essential Functions

  • Data Cleaning Techniques

  • Working with Tables, Filters, and Conditional Formatting

  • Lookup Functions (VLOOKUP, INDEX/MATCH, XLOOKUP)

  • Pivot Tables & Pivot Charts

  • Descriptive Statistics in Excel

  • Real-World Project: Analyzing Sales or Survey Data

Module 3: Power BI – Data Visualization & Dashboards

  • Introduction to Power BI Interface

  • Connecting & Importing Data

  • Data Modeling and Relationships

  • DAX Basics (Calculated Columns, Measures)

  • Creating Reports and Interactive Dashboards

  • Publishing and Sharing Dashboards

  • Real-World Project: Interactive Sales or HR Dashboard

Module 4: SQL for Data Retrieval

  • Introduction to Relational Databases

  • Basic SQL Syntax: SELECT, WHERE, ORDER BY

  • Filtering and Aggregating Data (GROUP BY, COUNT, SUM)

  • JOINS (INNER, LEFT, RIGHT, FULL)

  • Subqueries and Aliases

  • Real-World Project: Querying a Business Database

Module 5: Data Cleaning & Preparation Techniques

  • Identifying and Handling Missing Data

  • Dealing with Outliers and Duplicates

  • Data Transformation and Normalization

  • Date, Time, and Text Processing

  • Combining Data from Multiple Sources

Module 6: Interpreting and Communicating Insights

  • Data Storytelling Principles

  • Charts Selection (When to use what)

  • Creating Insightful Reports

  • Making Recommendations from Data

  • Presenting Data Analysis Projects

Module 7: Capstone Project

  • Choose a Dataset (Business, Healthcare, Education, etc.)

  • Apply Excel, Power BI, and SQL for full analysis

  • Create a professional dashboard

  • Write an executive summary of insights

  • Present and Defend Your Work

Additional Features:

    • Real-world datasets for practice

    • Assignments and quizzes for each module

    • Peer review and feedback on final project

    • Certificate of Completion

    • Tips for getting freelance or remote jobs in data

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    Amoo Sunday

     Data Analyst
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    Course Preview
    • Price N5000
    • Mode scholarship
    • Instructor Amoo Sunday
    • Duration 20 days
    • Attendance Online (Remote)
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