Data Analysis with Excel

10 Weeks

All levels

25 lessons

1 quiz

0 students

Overview
Curriculum
Instructor

Objective

This beginner-level learning module is designed to introduce participants to the fundamentals of data analysis using Microsoft Excel. Participants will learn how to use Excel for data manipulation, visualization, and basic statistical analysis, equipping them with valuable skills for entry-level data analysis roles.

Curriculum

12 Sections
25 Lessons
10 Weeks

Expand all sectionsCollapse all sections

Module 1: Introduction to Excel for Data Analysis
2
- 1.1
  a. Understanding Excel’s role in data analysis.
- 1.2
  b. Familiarization with Excel’s interface and data structure.
Excel Environment Setup
2
- 2.1
  a. Setting up Excel for data analysis.
- 2.2
  b. Configuring Excel options and preferences for efficient data work.
Data Import and Entry in Excel
2
- 3.1
  a. Importing data into Excel from various sources.
- 3.2
  b. Manual data entry and formatting best practices.
Module 2: Data Cleaning and Transformation
3
Excel Functions for Data Analysis
2
- 5.1
  a. Introduction to essential Excel functions (e.g., SUM, AVERAGE, COUNT, IF).
- 5.2
  b. Using functions to perform basic data calculations.
Data Sorting and Filtering
2
- 6.1
  a. Sorting data for better analysis.
- 6.2
  b. Applying filters to extract specific data subsets.
Module 3: Data Visualization with Excel Charts
2
- 7.1
  a. Creating charts and graphs in Excel.
- 7.2
  b. Choosing the right chart type for data representation.
Pivot Tables for Data Summarization
2
- 8.1
  a. Building PivotTables to summarize and analyze data.
- 8.2
  b. Customizing PivotTables for different reporting needs.
Basic Statistical Analysis
2
- 9.1
  a. Introduction to basic statistical concepts (mean, median, mode).
- 9.2
  b. Using Excel functions for statistical calculations.
Module 4: Data Analysis Tools in Excel
2
- 10.1
  a. Exploring Excel’s Data Analysis ToolPak.
- 10.2
  b. Performing regression analysis, t-tests, and more.
Data Analysis Scenarios
2
- 11.1
  a. Practical data analysis scenarios and case studies.
- 11.2
  b. Applying Excel skills to real-world problems.
Data Presentation and Reporting
3

CHINEDU ODOH

Chinedu is an experienced data analyst with a passion for tech, blockchain, health and fintech. With three years of industry expertise and a talent for community growth. Over the past three years, He had the privilege of working alongside brilliant minds, harnessing the power of data and Low-code, No-code Microsoft tools to drive innovation and transformation in the ever-evolving tech landscape. With extensive experience thriving in collaborative and multidisciplinary environments, leveraging diverse perspectives to tackle complex challenges and drive innovative solutions, He has equipped stakeholders with a deep understanding of industry intricacies to successfully leverage data-driven insights to make a significant impact, optimizing operations and driving strategic decision-making. He's a Deputy city lead at Data scientist network/ Data Science Nigeria (DSN). Beyond analytical skills, He has actively contributed to growing communities and fostering collaboration among tech enthusiasts.

Data Analysis with Excel

Curriculum

CHINEDU ODOH

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