MONTH 2 · 10 SEP

AI for Tech Professionals

Apply AI across software development, product, design, and data, and build the foundation for AI engineering.

Apply for this course AI Academy Overview

Who it's for

Aspiring and junior developers
UI/UX designers
Product managers
Business analysts
QA engineers
DevOps engineers
Data analysts
Solutions architects
Anyone entering tech

What you'll achieve

By the end of this course you will use AI as a daily engineering and product tool across the software development lifecycle, and understand the foundations needed to move into advanced AI engineering.

Course format

12 modules · beginner-to-intermediate · light coding in some modules (a code editor and a free API key are useful). The first three modules build on the shared AI Foundation with a technical lens.

Modules

12 live sessions with hands-on practice

Module 1

AI Foundations for Tech

Get the vocabulary and the map: what these models are, what they're called, and where they fit in your stack.

You'll cover:

Generative AI for a technical audienceKey terms: tokens, context windows, temperature, embeddingsThe model landscape: OpenAI, Anthropic, Google, and open-weight models like LlamaWhere AI fits into the modern technology stack

By the end: Speak the language of AI and understand the tool landscape.

Module 2

Advanced Prompt Engineering

Move past casual prompting to designing prompts that behave reliably in real systems.

You'll cover:

System vs user prompts, roles, and structureFew-shot examples and step-by-step reasoningStructured output (JSON, tables, markdown) for downstream usePrompt iteration, testing, and versioning

By the end: Design dependable prompts for technical tasks.

Module 3

AI-Assisted Coding

Use AI to write, explain, and improve code faster while staying firmly in control of quality.

You'll cover:

Coding assistants: GitHub Copilot, Claude Code, Cursor, WindsurfGenerating, explaining, and refactoring codeWriting tests and debugging with AIReviewing AI-written code for correctness and security

By the end: Ship code faster without losing rigour.

Module 4

AI for Product Management

Accelerate the thinking and documentation that keep products moving.

You'll cover:

Drafting PRDs, user stories, and acceptance criteriaSynthesising user research and feedbackRoadmap brainstorming and prioritisation supportCompetitive and market analysis

By the end: Speed up product discovery and documentation.

Module 5

AI for UI/UX Design

Get from idea to mockup faster with AI woven into your design workflow.

You'll cover:

Generating wireframes and design directionsAI inside Figma and FigJamInterface copywriting: microcopy, empty states, errorsGenerating images and icons for mockups

By the end: Move from concept to a working mockup quickly.

Module 6

AI for Data Analysis

Analyse data without getting blocked by syntax.

You'll cover:

Cleaning and exploring datasets with AI helpWriting SQL and spreadsheet formulas from plain EnglishGenerating charts and explaining the resultsTools: ChatGPT data analysis, notebooks, and BI assistants

By the end: Turn raw data into insight, faster.

Module 7

AI APIs

Make the leap from using AI in a chat box to calling it from your own code.

You'll cover:

What an API is and how AI APIs work (request and response)Keys, authentication, and token-based cost basicsMaking your first call to an LLM API with a simple exampleReading the docs and understanding rate limits

By the end: Call an AI model programmatically.

Module 8

Building Simple AI Apps

Put the pieces together and ship a small, working AI-powered prototype.

You'll cover:

No-code and low-code builders for chatbots and automationsConnecting an AI model to a simple interfaceAdding your own data (an intro to retrieval)Shipping and sharing a small prototype

By the end: Build and share a simple AI-powered app.

Module 9

Introduction to LLMs

Go one level deeper so you can make sound architecture choices later.

You'll cover:

How LLMs are trained: pretraining, fine-tuning, RLHF (the intuition)Context windows, embeddings, and what RAG isOpen vs closed models and when to use eachReal limitations: hallucination, cost, and latency

By the end: Understand LLMs well enough to make design decisions.

Module 10

AI Automation

Wire your tools together so routine work runs itself.

You'll cover:

Connecting tools with n8n, Zapier, and MakeTriggers, actions, and AI steps inside a workflowAutomating reports, notifications, and data entryPractical automations for a tech team

By the end: Automate real workflows end to end.

Module 11

AI Agents

Understand what separates an agent from a chatbot, and prototype a basic one.

You'll cover:

What an agent is, versus a simple chatbotTools, memory, and the reason-and-act loopSimple agent frameworks and real use casesRisks, guardrails, and keeping agents safe

By the end: Understand and prototype a basic AI agent.

Module 12

Career Development with AI

Position yourself for the roles that the AI era is creating.

You'll cover:

Building a standout CV and portfolio with AIPreparing for technical interviewsPersonal branding and a strong LinkedIn presenceStaying current as the field moves

By the end: Stand out for AI-era technology roles.

Capstone project

Build and present a small AI-powered tool or automation that solves a real problem in your role, from idea to prototype to a short demo for the cohort.

Where this leads next

Progress into the advanced engineering tracks: AI Builder, AI Agent Engineering, AI Engineering, and Enterprise AI Architecture.

Ready to apply AI in tech?

Applications open for AI Academy Month 2. 10 Sep – 10 Oct 2026.

Apply for AI for Tech