Applied AI & Automation

Identify where AI and automation can genuinely improve the way work gets done — and deliver solutions that are responsible, practical, and valuable.

Apply now

To the programme

Duration

~18 months

Standard

Level 4 AI & Automation Practitioner

Funding Band

£18,000

What you’ll be able to do

Work hands-on with leading AI tools

Use Claude, Gemini, ChatGPT, or Copilot with confidence; picking the right model for the job, writing effective prompts, and managing hallucinations. Apply everyday AI tools like Grammarly and meeting assistants to automate routine work.

Spot and validate automation opportunities

Analyse real workflows to find where AI and automation can cut cost, effort, or risk. Validate problems through observation, surveys, and user interviews before building; so you solve what actually matters.

Build working low-code and no-code automations

Configure and adapt tools to solve real operational problems and ship automations that improve speed, accuracy, and consistency. Build with n8n, Hostinger Horizons, and AI coding assistants.

Apply AI responsibly

Put ethics, security, and privacy principles into practice across every AI use case. Stay informed about EU and UK AI policies while supporting governance, explainability, auditability, and the clear documentation of automated decisions.

Lead change and drive adoption

Bring teams along by addressing concerns, building confidence, and tailoring your message to each stakeholder. Embed new ways of working that stick and support sustainable behavioural change.

Tools you'll learn

ClaudeGoogle GeminiChatGPTMS CopilotPerplexityFirefliesGrammarlyn8nHostinger HorizonsCodexGithub CopilotPython

Curriculum

4 Modules · 13 Sprints

01AI Literacy3 sprints

Understand what AI is, how it works, and how to approach it critically and responsibly while learning to communicate AI-driven changes effectively.

Sprint 1: Introduction to AI

Explore the history, different types of AI, and the most popular tools. Learn how modern AI works, living in the AI era, security considerations, and mindful approaches to AI.

Introduction to AI: History, types, and popular tools (ChatGPT, Perplexity, Gemini, Claude, Cohere AI, Llama)
Living in the AI Era: AI subscriptions, hype vs reality, and key concepts
Inner Workings of AI: How LLMs are built, closed vs open models, and why AI makes mistakes
Don't Let AI Overwhelm You: Distinguishing AI-generated content from human work
Security First: Using AI responsibly at work, compliance, privacy, and relevant laws
Mindful Approach to AI: Healthy AI use for work and learning, psychological impact, wellbeing, and bias awareness

Sprint 2: Prompting for Best Outcomes

Learn how to write prompts that get better, more accurate, and more creative results from AI.

AI Model Landscape: Overview of today's AI models, who builds them, and where each excels
Prompt Engineering: Writing clear, effective prompts to achieve intended outcomes
Context Engineering: How context shapes AI output, hallucinations, and how to reduce them
Advanced AI Concepts: Key terminology, deeper model concepts, and designing reusable prompt workflows

Sprint 3: Responsible AI Adoption & Stakeholder Enablement

Learn to communicate AI-driven changes clearly and apply ethical, secure AI principles aligned with organisational policies.

Stakeholder Communication: Communicating AI-driven changes to diverse stakeholders
Supporting Adoption: Enabling adoption through training, documentation, and ongoing guidance
Responsible AI Practices: Applying ethical, secure, and responsible AI principles
Policy Alignment & Governance: Learn about the EU AI Act and UK AI policies while aligning AI usage with organisational policies, risk management, and compliance.

02No Code AI Applications4 sprints

Explore practical AI tools that boost productivity, help you build without coding, and automate everyday tasks.

Sprint 1: AI for Productivity

Discover how AI shows up in everyday tools and how to leverage AI assistants for meetings, writing, and workflow improvements.

AI Products Are Everywhere: AI in existing tools and judging whether AI features add value
AI Productivity Tools: AI assistants for meetings, writing support, grammar checking, and workflow boosts
Agentic AI & Search: How agent-style AI works and AI-driven search engines

Sprint 2: Automations with No-Code Tools

Build automated workflows using n8n and other no-code automation platforms.

Getting Started with n8n: Introduction, use cases, and navigating the interface
AI-powered Automation with n8n: Build an automated email workflow step-by-step using AI
Advanced n8n Features: Complex automations and comparison with alternatives like Zapier

Sprint 3: Building AI-Native Apps

Create simple web apps using no-code platforms and learn to evaluate automation performance.

No-Code Productivity Web Apps: Create web apps using Hostinger Horizons and Lovable
Enhancing Your Productivity Web App: Add functionality with integrations and backend features
Designing Useful AI Apps: Create processes that leverage the newest AI developments
Evaluate Performance: Evaluate automation performance and improve using data and feedback

Sprint 4: Problem-Solution Discovery and Alignment

Learn to identify problems worth solving and develop valuable solutions across different team sizes and organisational contexts.

From a Problem to Solution: Improve your process of developing personal projects
Rapid Solution Development in Small Teams: How problem-solution discovery changes with small teams
Developing Solutions in Larger Organisations: Apply methodologies in large organizations with complex stakeholder management
Practicing Creating Useful Solutions: Identify a problem at work and create a valuable solution

03Low Code AI Applications3 sprints

Develop coding skills with AI assistance and learn to evaluate the consistency, scalability, and security of AI solutions.

Sprint 1: Python Programming with AI

Get comfortable working with notebooks, APIs, and AI coding assistants while understanding their limitations.

Familiarising with Coding Environments: Working with notebooks, basics of APIs, and recognising AI overuse in coding
AI as a Coding Assistant: Key AI coding assistants and 'vibe-coding' as a development approach
Limitations of AI-Generated Code: Where AI-written code falls short and why human oversight matters
Reviewing Your Code: Deepening coding knowledge, assessing code quality, and evaluating security using AI

Sprint 2: AI-Assisted Development

Explore modern AI coding tools and learn to express intent clearly to guide AI toward reliable implementations.

AI Coding Tools in Practice: Claude Code, Codex, Copilot, Cursor - strengths, limitations, and use cases
Designing Clear Intent & Implementation: Express intent through prompts, specifications, and constraints
Critical Approaches to Vibe Coding: When vibe coding accelerates delivery vs introduces risk
Reviewing & Stress-Testing AI Output: Validating AI-generated code through testing, edge-case analysis, and security review

Sprint 3: Evaluating Consistency, Scalability and Security

Develop techniques for ensuring AI solutions remain consistent, maintainable, and secure over time.

Ensuring Consistency in AI Results: Validating AI-generated code through testing and edge-case analysis
Ensuring Scalability in AI: Approaches to keep AI solutions maintainable long-term
Ensuring Security in AI-generated Solutions: Common security issues and how to mitigate them
Iterative Techniques for AI Development: Solve problems with AI in an iterative, step-by-step approach

04Optional ModulesOptional · 3 sprints

The optional module lets learners deepen their skills in AI-driven creative production — from generating images and audio to developing polished content and presentations. By building these capabilities internally, organisations can move faster, reduce outsourcing costs, and create professional-grade media at scale. Completing any of these modules also means the learner will automatically qualify for a reduction in off-the-job training (OTJ) hours for the Level 4 Data Analyst Apprenticeship, making future progression more efficient.

Image Generation

Create images using AI, understand how visual models interpret prompts, and learn the limitations and ethical considerations in AI-generated artwork.

Multi-modal AI Tools

Explore voice control, audio generation, and introductory video creation using modern multimodal models.

AI for Communication & Presentation

Use LLMs to draft written content, improve clarity and tone, and build AI-supported presentations that communicate ideas more effectively.