Learn Data Analysis and Turn Raw Data into Meaningful Insights
Learn how to collect, clean, and analyze data to uncover useful insights and support better decision-making. This course introduces you to key tools and techniques used in data analysis, helping you turn raw data into meaningful information.
Course Overview
This course teaches you how to collect, clean, analyse, and visualise data using industry-standard tools. You will learn to extract meaningful insights from complex datasets and communicate them effectively to stakeholders.
What You Will Learn
Analyse real-world datasets confidently
Build clear and insightful visualisations
Communicate findings to stakeholders
Use Excel and Python for analysis
Learning Modules
Module 1: Introduction to Data and Data Analysis
Understand data concepts and data preparation workflow.
- Concept of data and data analysis
- Data collection and data sources
- Data cleaning and preparation
Module 2: Basic Statistical Concepts for Data Analysis
Apply statistics to real-world data problems.
- Importance of statistics in data analysis
- Descriptive and inferential statistics
- Real-world applications of statistics
- Levels of measurement
- Data collection methods
- Population vs sample
- Data organization and presentation
- Data visualization basics and best practices
- Measures of central tendency
- Measures of dispersion
- Correlation and relationships
- Regression
- Hypothesis testing
- Probability basics
Module 3: Microsoft Excel for Data Analysis
Use Excel tools for cleaning, analysis, and reporting.
- Introduction to Excel
- Essential Excel operations
- Basic formulas and functions
- Data cleaning and preparation in Excel
- Lookup and reference functions
- Data analysis techniques
- PivotTables and PivotCharts
- Data visualization in Excel
- Dashboards and reporting
Module 4: Structured Query Language (Database Querying)
Query and analyze relational databases using SQL.
- Introduction to databases and SQL
- Understanding tables and data types
- Basic SQL queries
- Working with text, numbers and dates
- Aggregations and grouping
- Joins and combining data
- Subqueries and nested queries
- Data cleaning with SQL
- Analytical functions (window functions)
- Creating views and stored queries
- Data modeling basics
Module 5: Microsoft Power BI
Build models, dashboards, and reports in Power BI.
- Introduction to Power BI
- Getting and connecting data
- Power Query Editor
- Data modeling
- DAX (Data Analysis Expressions)
- Data visualization and reporting
- Power BI service (online workspace)
- Power BI automation and advanced tools
Module 6: Data Analysis with Python
Analyze and visualize data with Python libraries.
- Introduction to Python
- Python fundamentals
- Control flow
- Functions and modules
- Introduction to NumPy
- Data analysis with Pandas
- Data cleaning and preparation
- Data visualization with matplotlib and seaborn
- Exploratory Data Analysis (EDA)
- Real-world data analysis projects
Tools you will use
Skills You Will Gain
Critical thinking- Statistical reasoning
- Data storytelling
- Problem-solving
Career Opportunities
Taking this course can lead to careers in various industries, including healthcare, business, and technology.
