AI
Don’t just learn about AI. Learn to use it.
ENGNEXIS teaches practical AI: how to understand it, create with it, automate with it and apply it to real work, with human judgment kept in the loop.
The journey
Understand. Create. Automate. Apply.
Four stages that take people from using AI casually to using it well.
Core ideas
The concepts behind practical AI.
A short, plain-language map of the ideas the workshop builds on.
AI in practice
- 01Generative AI
- Creates and transforms content, such as text, images and code, from natural-language instructions.
- 02LLMs
- Large language models process and generate language based on patterns learned from large amounts of text.
- 03Prompting
- Structured instructions and context that make AI output more relevant and reliable.
- 04AI workflows
- Connect AI reasoning with repeatable tasks and information sources.
- 05Automation
- Moves repetitive actions from manual execution into systems and workflows.
- 06AI agents
- Combine reasoning, tools and actions to work through multi-step tasks, with human oversight.
Workflow
From a single prompt to a repeatable workflow.
From prompt to workflow7 steps
- 01PromptA clear instruction
- 02ContextBackground and constraints
- 03AI reasoningThe model generates a response
- 04Tools & dataDocuments, files, systems
- 05OutputA draft, analysis or action
- 06Human verificationYou check and decide
- 07Repeatable workflowSaved and reused
AI evolution
- 1SearchFind existing information
- 2Generative AICreate and transform content
- 3AI workflowsConnect AI to repeatable tasks
- 4AgentsPlan and act across steps
- 5Assisted executionPeople direct, AI carries out
What is changing
Trends worth understanding.
Established directions in AI, explained without hype.
01
Multimodal AI
Models that work across text, images, audio and documents together.
02
Reasoning-capable models
Models that work through multi-step problems before answering.
03
Domain-specific AI
AI adapted to the data and language of a particular field.
04
AI + automation
AI reasoning combined with systems that carry out the work.
Build practical AI capability.
Workshops and programs for students, engineers and campuses.