Data Analysis: From Beginner to Advanced

Course Overview

This course equips learners with the essential skills needed to analyze large datasets, draw meaningful insights, and make data-driven decisions. You will learn how to use tools such as Excel, SQL, and Python to perform data analysis, visualize results, and present findings in a professional manner. By the end of the course, students will be able to manage real-world data projects, work with complex datasets, and become proficient in data analysis and visualization techniques used in business and industry.

Skills you'll aquired

Data Cleaning and Preparation
Data Wrangling with Pandas (Python)
Data Analysis and Interpretation
SQL for Data Queries and Management
Data Visualization with Matplotlib and Seaborn
Advanced Excel for Data Analysis (Pivot Tables, Charts, etc.)
Data Reporting and Presentation
Descriptive and Inferential Statistics
Business Intelligence Tools (Optional)

Course Features:

50 Hours

Live Class and Video Suggestions

18 Articles

12 Downloadable Resources

43 Practicals

54 Hands-on Projects

Certificate upon Completion

Live Interactions

Course Compact

Gain a broad understanding of what data analysis is and why it is essential in today’s data-driven world.

Understanding Data and Its Importance
Key Concepts in Data Analysis
Types of Data: Structured vs Unstructured Data
Career Opportunities in Data Analysis

Learn the foundational steps to clean, organize, and prepare datasets for analysis using Excel.

Introduction to Excel for Data Handling
Data Cleaning Techniques (Removing Duplicates, Handling Missing Data)
Sorting, Filtering, and Data Validation
Using Formulas for Data Preparation

Learn how to use SQL to query databases and extract meaningful data for analysis.

SQL Basics: SELECT, WHERE, and JOIN Queries
Filtering and Sorting Data
Aggregating Data with GROUP BY and HAVING
Advanced SQL Queries: Subqueries and Indexing

Dive into Python and use the Pandas library to perform powerful data manipulations and analysis.

Introduction to Python Programming for Data Analysis
Data Structures: Lists, Dictionaries, and DataFrames
Data Wrangling with Pandas: Importing and Exporting Data
Data Cleaning, Filtering, and Aggregating in Python

Master the art of data visualization using Python libraries to create meaningful charts and graphs.

Introduction to Data Visualization Principles
Creating Line Charts, Bar Charts, and Pie Charts with Matplotlib
Using Seaborn for Advanced Statistical Plots (Heatmaps, Box Plots)
Customizing Visualizations and Plotting Styles

Excel remains one of the most popular tools for data analysis. Learn its advanced features to make better decisions.

Using Pivot Tables for Data Summarization
Advanced Formulas and Functions for Data Analysis (LOOKUPs, IF Statements)
Charting and Graphs for Reporting Data
Excel Dashboards for Data Presentation

Learn the essential statistical concepts that power data analysis, making your insights more meaningful.

Introduction to Statistics for Data Analysis
Measures of Central Tendency (Mean, Median, Mode)
Probability and Distributions
Hypothesis Testing and Statistical Significance

Learn how to communicate data findings effectively by creating reports and presentations that resonate with decision-makers.

Creating Data Reports in Excel
Best Practices for Data Presentation
Storytelling with Data: How to Structure a Narrative
Tools for Creating Professional Reports (Tableau/Power BI Overview)

Apply all the concepts learned by working on a real-world data analysis project, preparing you for industry-level work.

Project: Analyzing a Dataset (e.g., Sales Data, Customer Data)
Reporting Findings and Presenting Results
Feedback and Iteration

Requirements

Basic computer knowledge and access to a laptop or PC
No prior data analysis or programming experience required
Willingness to learn and work on projects
Access to Microsoft Excel and Python (via Jupyter Notebook or similar)

Description

The Data Analysis course is designed for anyone who wants to learn how to work with data to make informed decisions. Whether you're a beginner or someone with some prior experience, this course will guide you through the entire process of data analysis. You will learn to clean and manipulate datasets, perform data analysis using Excel, SQL, and Python, and visualize your results using various tools. By the end of this course, you'll be ready to handle real-world data projects, create professional reports, and present your findings effectively.

Course Duration: 10 Weeks

Total Hours: 50 Hours (combining videos, exercises, and live sessions)

Meet the Instructor

Mayomi Odewaye

Software Engineer / Data Analyst / Project Manager

Mayomi Odewaye is a dynamic and accomplished professional who has made significant contributions to the fields of software engineering, data analysis, and project management. With a strong academic background and practical experience in Python programming, Machine Learning, Web Development, and PHP, Mayomi is passionate about teaching and mentoring aspiring developers. As the founder of KrossCheck, Mayomi is dedicated to providing innovative solutions that enhance the educational experience and streamline academic processes.