Data Analysis & Data Visualization

What Data Analysis Is and Why It Matters

Explain the purpose of data analysis in simple business situations.

Understanding Data, Information, and Business Questions

Distinguish between raw data, useful information, and a clear business question.

Types of Data and Common File Formats

Identify basic data types and file formats used in analysis.

Setting Up Your Workspace for Analysis

Install and open the core tools used in the course.

Getting Started with Excel for Data Work

Open a dataset in Excel and inspect its rows and columns.

Reading and Saving Data in Jupyter Notebooks

Launch Jupyter Notebook and load a simple dataset with Python.

Your First Look at Pandas DataFrames

Use Pandas to display basic dataset structure and summary information.

PROJECT: Explore a Simple Business Dataset

Create a short notebook and spreadsheet summary of one dataset using basic inspection steps.

What Databases Are and How SQL Works

Describe how databases store business data and how SQL retrieves it.

Writing Simple SQL Queries

Write basic SQL queries to select columns and filter rows.

Sorting, Limiting, and Grouping Data in SQL

Use SQL to sort results, limit output, and summarize data by category.

Cleaning Basics: Missing Values, Duplicates, and Wrong Types

Identify common data quality problems in a dataset.

Cleaning Data with Pandas

Apply simple Pandas methods to fix missing values, duplicates, and data types.

Using Excel for Quick Data Cleaning

Use Excel tools to correct small data issues in a table.

PROJECT: Clean and Organize a Business Dataset

Prepare a messy dataset for analysis using Excel, SQL, or Pandas.

Exploratory Data Analysis with Questions

Ask and answer basic analysis questions from a cleaned dataset.

Descriptive Statistics for Beginners

Calculate and interpret simple summary statistics in Python or Excel.

Visualizing Data with Matplotlib and Seaborn

Create simple charts that show patterns in business data.

Choosing the Right Chart for the Message

Match common business questions to appropriate chart types.

Building a Simple Dashboard in Power BI

Create a basic dashboard with one dataset and a few visuals.

PROJECT: Build an End-to-End Mini Analysis

Analyze, clean, visualize, and present findings for a small business dataset.

Telling a Clear Story with Data

Write a short data story that explains findings and recommendations.

Getting Started with Microsoft Excel

Identify the Excel interface and open, save, and close a workbook.

Workbooks, Worksheets, and Cells

Explain the difference between a workbook, a worksheet, and a cell.

Entering and Editing Data

Enter, edit, and delete data in a worksheet.

Formatting Cells for Clarity

Format text, numbers, and dates to make a spreadsheet easier to read.

Using Basic Formulas

Create simple formulas with addition, subtraction, multiplication, and division.

Essential Functions: SUM, AVERAGE, MIN, and MAX

Use basic Excel functions to calculate common summary values.

Copying Formulas with Relative References

Copy formulas across cells and observe how cell references change.

Project: Build a Personal Expense Tracker

Create a simple expense tracker spreadsheet that records spending and calculates totals.

Sorting and Filtering Data

Sort and filter a table to find specific records.

Working with Excel Tables

Convert a data range into a table and use table features to manage data.

Cleaning Data with Find, Replace, and Remove Duplicates

Clean a dataset by fixing repeated values and inconsistent text entries.

Using IF to Make Simple Decisions

Write an IF formula to return different results based on a condition.

Counting and Summarizing with COUNT, COUNTA, and AVERAGEIF

Use counting and conditional summary functions to analyze data.

Introduction to Charts in Excel

Create a basic chart from spreadsheet data.

Choosing the Right Chart for the Data

Match common data questions to suitable chart types.

Project: Sales Summary Dashboard in Excel

Build a small Excel dashboard that summarizes sales data with tables, formulas, and charts.

Preparing Excel Data for Analysis in Python and SQL

Export a cleaned Excel dataset for use in pandas and SQL workflows.

Capstone Project: Business Report from Excel Data

Create a complete Excel-based analysis report with cleaned data, summary calculations, and visuals.

What Power BI Is and Why Analysts Use It

Explain the purpose of Power BI and identify the kinds of business questions it helps answer.

Installing Power BI Desktop and Signing In

Install Power BI Desktop and open a signed-in workspace successfully.

Getting to Know the Power BI Interface

Navigate the main Power BI screens and locate the report, data, and model views.

Importing Data from Excel and CSV Files

Load a simple dataset into Power BI from Excel or CSV.

Understanding Tables, Columns, and Data Types

Identify tables, columns, and data types in a Power BI dataset.

Cleaning Data in Power Query

Remove basic data problems such as blank rows, unwanted columns, and incorrect formats in Power Query.

Creating Simple Relationships Between Tables

Connect two related tables using a basic relationship in the data model.

Building Your First Visuals

Create bar charts, line charts, and tables from a dataset in a report.

Hands-On Project: Build a Simple Sales Report

Create a basic Power BI report that shows sales by product, month, and region.

Choosing the Right Visual for the Question

Match common business questions with the most suitable chart type.

Using Filters and Slicers

Add filters and slicers to let users explore report data interactively.

Formatting Reports for Clarity

Improve a report by adjusting titles, colors, labels, and layout.

Creating Basic Measures with DAX

Write simple DAX measures for totals, averages, and counts.

Understanding Basic Dashboard Design

Organize visuals on a page to make a clear and readable dashboard.

Publishing Reports to Power BI Service

Publish a finished report from Power BI Desktop to Power BI Service.

Sharing and Presenting a Power BI Dashboard

Share a published report and present key findings to a business audience.

Capstone Project: Create a Business Dashboard from Raw Data

Build and present a complete Power BI dashboard that answers a real business question using cleaned data, visuals, filters, and measures.

What Data Analysis Is and How Python Helps

Explain how Python is used in data analysis and identify the main tools in this course.

Setting Up Python, Jupyter Notebooks, and Anaconda

Install and open the Python learning environment used for the module.

Working in Jupyter Notebooks

Create and save a Jupyter Notebook and run simple code cells.

Python Basics: Variables and Simple Calculations

Use variables to store values and perform basic arithmetic in Python.

Python Data Types and Printing Results

Identify common Python data types and display output with print statements.

Lists and Dictionaries for Storing Data

Create lists and dictionaries to organize small data sets in Python.

Importing Pandas and Loading a CSV File

Import Pandas and load a CSV file into a DataFrame.

Inspecting DataFrames with Rows, Columns, and Basic Summary

Examine the shape, column names, and first rows of a DataFrame.

PROJECT: Build a Mini Data Cleaning Notebook

Create a notebook that loads a CSV file, inspects the data, and identifies basic data issues.

Selecting Columns and Filtering Rows in Pandas

Extract specific columns and filter rows using simple conditions.

Handling Missing Values and Duplicate Rows

Detect and clean missing values and duplicate records in a DataFrame.

Creating New Columns with Basic Transformations

Add new columns to a DataFrame using simple calculations and text changes.

Group By and Basic Data Summary

Use group by operations to calculate totals and averages by category.

Exploring Data with Matplotlib and Seaborn

Create basic charts to compare values and show patterns in data.

Reading Data from Excel and Connecting Python to Spreadsheets

Load an Excel file into Pandas and work with spreadsheet-style data in Python.

PROJECT: Exploratory Analysis of a Business Dataset

Analyze a business dataset in Python and present key findings with cleaned data and charts.

Writing SQL Queries to Support Python Analysis

Use SQL to extract a small dataset that can be analyzed in Python.

Combining SQL Results and Python for Analysis

Import SQL query results into Pandas and continue analysis in Python.

PROJECT: Capstone Data Analysis Notebook

Build a complete analysis notebook that loads data, cleans it, explores it, and communicates findings with charts.

What SQL Is and How Data Is Stored in Tables

Explain how SQL is used to read data from tables in a database.

Setting Up a SQL Practice Environment

Install and open a SQL tool for writing and running queries.

Understanding Databases, Tables, Rows, and Columns

Identify databases, tables, rows, and columns in a sample dataset.

Writing Your First SELECT Query

Write a simple SELECT query to display all data from a table.

Choosing Columns with SELECT

Write queries that return only specific columns from a table.

Filtering Rows with WHERE

Write queries that return rows matching a condition.

Sorting Results with ORDER BY

Write queries that sort data in ascending or descending order.

Project 1: Explore a Sales Dataset with Basic SQL

Build a set of SQL queries that answer simple business questions from a sample sales table.

Counting and Summarizing Data with COUNT, SUM, AVG, MIN, and MAX

Write aggregate queries that summarize numeric data.

Grouping Data with GROUP BY

Write queries that summarize data by category using GROUP BY.

Filtering Groups with HAVING

Write queries that filter grouped results using HAVING.

Joining Two Tables with INNER JOIN

Write a query that combines related data from two tables.

Joining Tables for Analysis with LEFT JOIN

Write a query that keeps all rows from one table while adding matching data from another.

Working with NULLs and Missing Data

Write queries that detect and handle missing values.

Using Simple SQL Logic with AND, OR, and CASE

Write queries that apply multiple conditions and create basic category labels.

Capstone Project: Analyze a Business Dataset with SQL

Create a complete SQL analysis that uses filtering, sorting, aggregation, grouping, and joins to answer business questions.

What NumPy Is and Why Data Analysts Use It

Identify how NumPy helps store and process numerical data faster than plain Python lists.

Setting Up Python, Jupyter Notebook, and NumPy

Install and open the tools needed to run NumPy code in Jupyter Notebook.

Creating Your First NumPy Arrays

Create one-dimensional NumPy arrays from Python lists and inspect their values.

Understanding Array Shape, Size, and Data Type

Check the shape, size, and data type of a NumPy array.

Selecting Values from Arrays

Use indexing and slicing to select specific elements from a NumPy array.

Changing Array Values and Creating Copies

Modify values in a NumPy array and create a separate copy when needed.

Working with Two-Dimensional Arrays

Create and read a two-dimensional NumPy array like a simple table.

Performing Basic Calculations with Arrays

Use NumPy to add, subtract, multiply, and divide array values.

PROJECT: Mini Sales Analysis with NumPy

Build a small notebook that uses NumPy arrays to calculate sales totals, averages, and simple comparisons.

Using Array Methods to Summarize Data

Calculate totals, averages, minimums, and maximums with NumPy methods.

Filtering Data with Conditions

Select array values that meet a rule using comparison operators.

Working with Missing or Invalid Values

Identify and handle missing values in a NumPy array using simple replacement methods.

Reshaping and Flattening Arrays

Change the layout of an array without changing its data.

Combining and Splitting Arrays

Join arrays together and separate them into smaller parts.

Using NumPy with Random Numbers

Generate random data with NumPy for practice and simple simulations.

PROJECT: Customer Data Practice Notebook

Create a notebook that cleans, reshapes, filters, and summarizes customer-like data using NumPy.

Connecting NumPy with Pandas DataFrames

Move data between NumPy arrays and Pandas DataFrames for analysis.

Using NumPy Results in Charts and Business Insights

Use NumPy-calculated values to support simple visual analysis in Matplotlib or Seaborn.

CAPSTONE: End-to-End NumPy Analysis Workflow

Complete a full beginner-friendly analysis in Jupyter Notebook using NumPy from raw data to insight.

Getting Started with Jupyter Notebook and Python

Open Jupyter Notebook and run basic Python code cells.

Understanding Pandas DataFrames and Series

Create a DataFrame and a Series from simple sample data.

Loading Data into Pandas

Import a CSV file into Pandas and inspect the first rows.

Exploring Columns, Rows, and Data Types

Identify columns, row counts, and data types in a DataFrame.

Selecting Data with loc and iloc

Extract specific rows and columns using loc and iloc.

Filtering Data with Conditions

Filter rows in a DataFrame using simple logical conditions.

Sorting and Organizing Data

Sort a DataFrame by one or more columns.

Adding and Updating Columns

Create new columns and update existing values in a DataFrame.

PROJECT: Sales Data Exploration in Pandas

Analyze a small business sales dataset by loading, filtering, sorting, and summarizing key fields.

Handling Missing Values

Find missing values and apply a simple method to handle them.

Cleaning Text and Standardizing Values

Clean text fields by trimming spaces and making values consistent.

Changing Data Types

Convert columns to the correct data type for analysis.

Combining DataFrames with Merge and Join

Combine two related DataFrames into one dataset.

Grouping Data and Calculating Summary Statistics

Use groupby to calculate totals, averages, and counts.

Basic Pandas Visualisation with Matplotlib and Seaborn

Create simple charts from a Pandas DataFrame using Matplotlib and Seaborn.

PROJECT: Cleaning and Summarizing a Business Dataset

Prepare a messy business dataset, combine related tables, and produce a clean summary for analysis.

Using Pandas with SQL and Excel Files

Import data from Excel and connect Pandas outputs to SQL-ready tables.

Building a Reusable Analysis Workflow

Organize a Pandas analysis into clear, repeatable notebook steps.

CAPSTONE: End-to-End Data Analysis in Pandas

Complete a full analysis from raw data to insight-ready summary and visual output.

What Data Visualization Is and Why It Matters

Explain the purpose of data visualization and identify when to use charts instead of tables.

Getting Ready: Installing and Opening the Tools

Set up Jupyter Notebooks, Python libraries, Excel, and Power BI for the module.

Reading Data for Charts

Load a simple dataset into Python and Excel for visualization practice.

Choosing the Right Chart for the Question

Match common business questions to the most suitable chart type.

Building Your First Bar and Column Charts in Excel

Create basic bar and column charts from a small dataset in Excel.

Line Charts for Change Over Time

Build a line chart that shows how a value changes across time.

Pie Charts, Donuts, and Simple Proportions

Create proportion charts and explain when they are helpful or misleading.

Project 1: Make a Simple Business Report in Excel

Create a short set of charts in Excel that answers one business question clearly.

Introducing Matplotlib in Python

Generate a basic chart in Jupyter Notebook using Matplotlib.

Improving Charts with Titles, Labels, and Colors

Add clear titles, axis labels, and simple formatting to a Python chart.

Exploring Patterns with Seaborn

Create cleaner charts in Seaborn to compare categories and distributions.

Making Visuals Easier to Read

Apply basic design choices that improve readability and reduce clutter.

Using SQL Data for Visualization

Write a simple SQL query that prepares data for charting.

Project 2: Build a Python Chart Set from Real Data

Create a small chart dashboard in Python using a cleaned dataset and multiple chart types.

Building Interactive Visuals in Power BI

Load data into Power BI and create a basic interactive report page.

Adding Filters, Slicers, and Drill-Down Views

Add simple interactive controls to help users explore a report.

Telling a Business Story with Charts

Arrange visuals and write a short narrative that explains the main insight.

Capstone: Create and Present a Data Visualization Dashboard

Build a complete dashboard and present the key findings in a clear business story.

Final Project

Final project for Data Analysis course

Setup your portfolio

How to setup your data analysis portfolio

Preparing for Job interview

Best Practices to prepare yourself for Data analysis role job interviews

Certification

Request for your certificate