
Fetch columns in a pandas dataset using df.info to reveal the dataset's columns, rows, and data types.
Learn to filter the specific numbers of records from a large Pandas dataset using the Ilok function to fetch a range such as 100 to 500.
Import the libraries and load the Titanic dataset from a GitHub URL to begin exploratory data analysis with pandas, then inspect df.info, shape (891, 12), and data types.
Inspect data types with df.dtypes and identify missing values using isnull().sum() in pandas. Generate a numeric summary with describe() and review how to handle missing values for real-world datasets.
Create a Seaborn count plot of the Titanic dataset to show survival by gender, with sex on the x axis and hue by survived (0 or 1).
Append multiple Excel sheets into a single master sheet using Power Query to consolidate datasets from Germany, Canada, the United States, Mexico, France, and India.
Most data analysis courses teach you a tool. This one teaches you a workflow — the exact, repeatable process of turning a messy spreadsheet into decisions a CEO can act on, using Claude AI as your analyst.
By the end, you won't just "know about AI." You'll have personally taken a real, public sales dataset of over 10,000 rows from raw download to a cleaned file, a KPI dashboard, and a one-page executive summary — without writing a single line of code.
This is a do-it-alongside course, not a watch-and-forget course.
Every lesson follows the same proven rhythm: you see the exact prompt to type, you watch Claude produce the real output, and you learn the business decision that output unlocks. You download the same dataset used in the lectures, so every number you produce matches what you see on screen.
What makes this course different
There are plenty of courses on ChatGPT for data, and plenty on Power BI. There are almost none that teach Claude AI specifically for business intelligence — even though Claude is exceptional at exactly this kind of work: reading files, cleaning data, building interactive dashboards, working inside Excel, and writing analysis a manager will actually read.
Instead of toy examples, you'll work the full case study end to end on the famous "Sample Superstore" retail dataset (free and public). Along the way you'll uncover the kind of insights that change how a business operates:
A pricing leak where discounts above 20% quietly destroy profit
An entire product line sold at a loss that category-level reports were hiding
A seasonal pattern showing half the year's revenue lands in just four months
You'll learn to find these in any dataset — including your own company's.
The 10-step workflow you'll master
Get and profile your data — spot duplicates, missing values, and trust problems before you analyze anything
Clean data the right way — fix duplicates, blanks, and inconsistent labels, and quarantine bad rows instead of silently deleting them
Compute the KPIs that matter — revenue, profit, margin, average order value, and loss-making segments
Find trends and seasonality — answer "why did sales spike?" and know when to stock up
Analyze by category and segment — see where revenue is high but profit is weak
Drill down to root causes — go from a vague problem to the exact products and regions responsible
Surface the killer insight — the discount, product, or customer pattern quietly costing the business money
Write executive summaries — turn numbers into recommendations a decision-maker can approve
Build interactive dashboards — KPI cards, trend lines, filters, and drill-downs Claude builds for you
Automate the whole thing — set up a monthly reporting pipeline so a full day of analysis runs in minutes
You'll also learn
How to use Claude inside Excel for formulas, forecasts, and budget-vs-actuals variance analysis
How to research competitors and build market intelligence briefs
How to connect Claude to live data sources (Google Drive, Sheets, email) safely, with the right permissions and governance
A reusable prompting framework you can apply to any business question
Who this course is for
Business analysts and aspiring data analysts who want to work faster and smarter
Managers, founders, and team leads who need answers from data but don't have a data team
Marketing, finance, and operations professionals who live in spreadsheets
Anyone curious about AI who wants a practical, job-ready skill rather than theory
Requirements
No coding, statistics, or prior data experience required
A Claude account (the course shows you how to choose a plan)
A spreadsheet program for some exercises
A willingness to follow along with the hands-on labs — that's where the learning happens
What you'll walk away with
Three capstone tracks (sales, finance, or marketing) let you build a portfolio-ready project on data that matters to you. By the final lesson you'll have a complete, automated business intelligence workflow you can put to work immediately — and the confidence to point Claude at any dataset and come back with answers.
Enroll now and turn raw data into decisions.
"What you'll learn" bullets (the 4-line box at the top of the page)
Take a real dataset from raw file to cleaned data, dashboard, and executive summary using Claude AI
Clean, analyze, and visualize business data without writing any code
Build interactive dashboards and automated monthly reporting pipelines
Find profit leaks, trends, and root-cause insights in any sales dataset