Applied AI Skills & Workflow Hands-on Labs
Format
Hands-on Labs
Price
£199
About the course
Applied AI Skills & Workflow is a hands-on course focused on applying AI to practical research, analysis, communication, decision-making, and software development workflows.
Rather than focusing on AI theory alone, learners work through realistic scenarios and labs that demonstrate how AI can augment professional tasks from initial research and data analysis through to technical implementation and testing.
Across the labs, participants will learn how to use AI as a research analyst, data storytelling partner, communication assistant, decision-making support tool, workflow orchestrator, and coding assistant.
They will also explore how to integrate AI into development practices such as Test-Driven Development (TDD).
Hands-on Labs
AI Research Analyst Lab — Use AI to accelerate research, synthesize information, evaluate sources, and turn findings into actionable insights.
Data Storytelling Lab: Turning Messy Data into Insights with AI — Transform unstructured or messy data into meaningful patterns, insights, and compelling narratives.
Audience-Aware Communication: Tailoring Technical Messages with AI — Adapt complex technical information for different audiences, contexts, and communication goals.
Decision-Making with AI: Scenario Planning and Risk Tradeoffs — Use AI to explore scenarios, surface assumptions, evaluate risks, and support informed decisions.
Prompt Chaining & Workflow Design — Build multi-step AI workflows that break complex tasks into manageable, repeatable stages.
AI-Powered Code Assistant — Apply AI coding assistants to generate, explain, refactor, debug, and improve code while maintaining developer oversight.
AI in Test-Driven Development (TDD) — Explore how AI can support test creation, implementation, debugging, and iterative software development using TDD principles.
Rather than focusing on AI theory alone, learners work through realistic scenarios and labs that demonstrate how AI can augment professional tasks from initial research and data analysis through to technical implementation and testing.
Across the labs, participants will learn how to use AI as a research analyst, data storytelling partner, communication assistant, decision-making support tool, workflow orchestrator, and coding assistant.
They will also explore how to integrate AI into development practices such as Test-Driven Development (TDD).
Hands-on Labs
AI Research Analyst Lab — Use AI to accelerate research, synthesize information, evaluate sources, and turn findings into actionable insights.
Data Storytelling Lab: Turning Messy Data into Insights with AI — Transform unstructured or messy data into meaningful patterns, insights, and compelling narratives.
Audience-Aware Communication: Tailoring Technical Messages with AI — Adapt complex technical information for different audiences, contexts, and communication goals.
Decision-Making with AI: Scenario Planning and Risk Tradeoffs — Use AI to explore scenarios, surface assumptions, evaluate risks, and support informed decisions.
Prompt Chaining & Workflow Design — Build multi-step AI workflows that break complex tasks into manageable, repeatable stages.
AI-Powered Code Assistant — Apply AI coding assistants to generate, explain, refactor, debug, and improve code while maintaining developer oversight.
AI in Test-Driven Development (TDD) — Explore how AI can support test creation, implementation, debugging, and iterative software development using TDD principles.
Course Lessons
