Core Programme

Generative AI in Prompt Engineering

From AI fundamentals through to advanced prompt engineering and real-world application. Participants leave with a personal prompt library, tested workflows, and the C.L.E.A.R. framework mastered on their own work scenarios.

  • 9 Modules
  • 60%+ Hands-On
  • 1-2 Days
  • All Levels
  • STOA Certified
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“You have given me a different perspective on what AI is”.

Ali Razza, Data Manager at Volkswagen Group

Next Session
April 14-15, 2026
8 seats remaining
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$1,299
per participant · includes all materials + certificate​
Advanced Programme

Build AI Agents That Do Real Work

A hands-on programme that takes your team from understanding AI agents to building live, working automations. No-code first, then low-code, then full-code. Every participant leaves with something deployable.

9 Modules · 70%+ Hands-On · 3-5 Days · Live Build Included · STOA Certified

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Programme Overview

What This Programme Covers

This advanced programme takes professionals from understanding AI agents through to building live, working automations. It follows a progressive path: no-code tools first, then low-code integration, then full-code agents.

Participants at every technical level can follow along. Day 1 is about thinking and process design. Day 2 is about building with no-code tools. Day 3 is about coding agents and completing a capstone project. Optional lab days (Days 4-5) provide extended guided build time for participants who want production-ready solutions.

Every module follows the TEA delivery framework: Theory (20%), Examples (20%), Application (60%). By the end, every participant has built a working automation on their own workflow, not a generic demo.

Who Should Attend

  • Business professionals across all functions
  • Operations and process improvement specialists
  • Analysts, project managers, and team leads
  • L&D and HR professionals building AI capability
  • IT teams evaluating automation platforms
  • Anyone automating repetitive day-to-day work

Learning Outcomes

  • Understand AI agents, when and how to use them
  • Map and redesign processes for automation
  • Build no-code automations with real platforms
  • Create code-based agents in GitHub Codespaces
  • Deploy, test, and maintain AI workflows
  • Leave with a live, working automation
Programme Overview
9 Modules. 70%+ Hands-On.

MODULE 01

Generative AI Rapid Foundations
LLM essentials, how models think and respond. The C.L.E.A.R. prompt engineering framework. When you need prompting vs when you need agents.

MODULE 02

Understanding AI Agents & Automation
What AI agents are and how they differ from prompts. Agent types: simple reflex, model-based, goal-based. The automation spectrum from no-code to full-code.

MODULE 03

Process Thinking for Automation
Mapping workflows step by step. Identifying automation candidates. Probabilistic vs deterministic processes. Workshop: map a real-world workflow.

MODULE 04

Designing Your Automation Use Case
Selecting your personal automation project. Defining inputs, processing steps, and outputs. Scoping a realistic 3-5 step automation. Peer review and refinement.

MODULE 05

Building No-Code Automations
Introduction to no-code automation platforms. Guided template build: meeting follow-up agent. Triggers, AI nodes, and document generation.

MODULE 06

Intermediate Automation Patterns
Conditional logic and branching workflows. Error handling and retry mechanisms. Connecting to APIs and external services. Multi-step automation.

MODULE 07

Coding Agents with Claude Code
When code beats no-code: the decision framework. Introduction to GitHub Codespaces (zero setup). Building your first code-based AI agent step by step.

MODULE 08

Integration, Testing & Deployment
Connecting automations to real-world tools. Testing strategies for AI-powered workflows. Security considerations and access controls.

MODULE 09

Capstone: Build Your Own Agent
Apply everything learned to your own use case. Choose your track: no-code, low-code, or full-code. Peer showcase and feedback session.
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Learning Path
Think. Build. Code. Deploy.
Our signature framework taught across all programmes. A structured approach to crafting effective prompts that work across any AI platform.
Day 1
Think
Understand & Design
GenAI foundations, agent concepts, process mapping. Identify and design your automation use case.
Day 2
Build
No-Code Automation
Guided template build. Create a working automation that generates documents and updates spreadsheets.

Day 3

Code
Full-Code Agents
GitHub Codespaces, Claude Code, API integrations. Build code-based agents and complete your capstone.

Day 4-5

Lab
Debrief and Build Days
Extended guided sessions. Build your own bespoke automation end-to-end with expert support.
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Upcoming Sessions
Choose Your Date​
Live Online · 5 Days
May 5-7

$3,999 

per delegate
Register
10 seats available
Live Online · 3 Days
June 16-18

$2,599

No-Code Automation
Guided template build. Create a working automation that generates documents and updates spreadsheets.
Live Online · 5 Days
July 14-18

$3,999

Full-Code Agents
GitHub Codespaces, Claude Code, API integrations. Build code-based agents and complete your capstone.

3 – 5 Days

Custom
Debrief and Build Days
Extended guided sessions. Build your own bespoke automation end-to-end with expert support.
Our signature framework taught across all programmes. A structured approach to crafting effective prompts that work across any AI platform.

C

Command
Set the stage with background, role, and situational information

L

Layer
Use precise, specific terminology and clear instructions

E

Examples
Define the desired output format, length, and style

A

Asses
Specify exactly what the AI should do step by step

R

Refine
Iterate systematically to improve and perfect outputs

MODULE 04

Asses
Multi-step prompting, tree of thought, meta prompting, multi-modal prompting, agentic prompting.

MODULE 05

Asses
Bias detection, privacy considerations, governance frameworks, responsible use guidelines, regulatory landscape.

MODULE 06

Evaluating AI Outputs
Critical evaluation methods, identifying hallucinations, interpretability, quality benchmarks, building confidence.

MODULE 04

Asses
Multi-step prompting, tree of thought, meta prompting, multi-modal prompting, agentic prompting.

MODULE 05

Asses
Bias detection, privacy considerations, governance frameworks, responsible use guidelines, regulatory landscape.

MODULE 06

Evaluating AI Outputs
Critical evaluation methods, identifying hallucinations, interpretability, quality benchmarks, building confidence.
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Schedule TNA Call
Upcoming Sessions
Choose Your Date
Live Online ● 2 Days
April 14-15, 2026
8 seats remaining

per participant​

$1,299

MODULE 02

April 14-15, 2026​
Live Online · 2 Days
8 seats remaining
$1,299
8 seats remaining

April 14-15, 2026​

Live Online · 2 Days

$1,299
per delegate
Register

MODULE 06

Evaluating AI Outputs
Critical evaluation methods, identifying hallucinations, interpretability, quality benchmarks, building confidence.

MODULE 07

Use Cases & Applications
AI for productivity, writing, data analysis, tables, notes, IT support, vibe coding, vibe flowcharting.
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MODULE 08

Scaling Generative AI
Team adoption strategies, organisational prompt libraries, integration planning, ROI measurement, change management.

MODULE 09

Operationalising & Future-Proofing
Personal AI toolkit, maintaining prompt libraries, staying current, AI agents introduction, action planning.
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What Every Participant Gets
You Keep Everything

Working Automation

A live, deployable automation built on your own workflow during the programme

GitHub Codespaces Lab

Pre-configured development environment with all tools, templates, and code ready to use

Process Mapping Templates

Frameworks for identifying and designing automation candidates in any department

Learning Materials

Full soft copy of all materials, automation blueprints, handouts, and reference guides

STOA Certificate

Certificate of Completion plus guided step-by-step pathway to Google Agentic AI certificate

30-Day Support

Post-programme Q&A availability and implementation guidance for your automation
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Delivery Options
Choose How Your Team Learns
In-Person
Instructor-Led On-Site

Delivered at your offices or venue. Maximum engagement for teams of 8-20 participants. All exercises use your team’s actual work scenarios.

Live Online
Virtual Instructor-Led

Real-time delivery via Zoom, Meet or Teams. Interactive breakout rooms, same content depth as in-person. Ideal for distributed teams.

Hybrid
Blended Approach

Combine in-person and virtual sessions. Flexible scheduling across time zones. Pre-work materials and follow-up resources included.

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Schedule TNA Call
Ready to Build
Stop Talking About AI. Start Building With It.

Join the next open session or book a private programme for your team. Custom proposal within 48 hours. Delivery in as little as 3 weeks.

Discuss Your Training Needs
Ready to Build
Stop Talking About AI. Start Building With It.

Join the next open session or book a private programme for your team. Custom proposal within 48 hours. Delivery in as little as 3 weeks.

Discuss Your Training Needs

C

Command
Set the stage with background, role, and situational information

L

Layer
Use precise, specific terminology and clear instructions

E

Examples
Define the desired output format, length, and style

A

Asses
Specify exactly what the AI should do step by step

R

Refine
Iterate systematically to improve and perfect outputs

MODULE 04

Asses
Multi-step prompting, tree of thought, meta prompting, multi-modal prompting, agentic prompting.

MODULE 05

Asses
Bias detection, privacy considerations, governance frameworks, responsible use guidelines, regulatory landscape.

MODULE 06

Evaluating AI Outputs
Critical evaluation methods, identifying hallucinations, interpretability, quality benchmarks, building confidence.

MODULE 04

Asses
Multi-step prompting, tree of thought, meta prompting, multi-modal prompting, agentic prompting.

MODULE 05

Asses
Bias detection, privacy considerations, governance frameworks, responsible use guidelines, regulatory landscape.

MODULE 06

Evaluating AI Outputs
Critical evaluation methods, identifying hallucinations, interpretability, quality benchmarks, building confidence.
Schedule TNA Call