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Data, automation, and AI. At your pace.
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Where will you begin?
Your next skill starts here.
AI essentials: useful, responsible workflows
Use generative AI more thoughtfully: understand its limits, write clear prompts, check outputs, and protect private information with hands-on examples.
Power Automate: your first reliable workflow
Design a reliable first workflow: map a repeatable process, connect a trigger to actions, add safe conditions, and handle failures without duplicate work.
Excel: from first cell to confident analysis
Learn Excel tables, formulas, lookups, and PivotTables with guided examples and a small sales-analysis project. No spreadsheet experience needed.
Machine learning: build your first mental model
Build a beginner’s mental model of machine learning: define features and labels, make a baseline, evaluate carefully, and avoid data leakage.
Pandas: explore real-world data
Explore tabular data with pandas: load a CSV, inspect its columns, filter and group records, and make a careful plan for missing values.
Power BI: turn data into decisions
Build your first useful Power BI report: prepare a small dataset, connect a simple model, create clear measures, and explain what the visuals mean.
Stay curious. Keep exploring.
Excel: build a spreadsheet you can trust
Keep one record per row and one field per column. Convert a range to a table, name it Sales, and check that dates and amounts have consistent types. Practice: build a five-row sales table with Date, Region and Revenue.
SQL joins: why your row count changed
SELECT chooses columns, FROM chooses a table, and WHERE filters rows. Practice: SELECT name, revenue FROM sales WHERE revenue > 100; Explain which rows remain.
Power Query: stop repeating the cleanup
Inspect nulls, duplicates and data types before making changes. Keep a copy of the source and define what one row represents.