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Advanced AI Literacy: Practical Enterprise AI Capability Building
The next-level capability program for professionals who have basic AI awareness and want to move from using AI tools to designing effective AI-enabled ways of working. It covers advanced Prompt Engineering, Context Engineering, AI workflow design, AI agents, knowledge systems, decision intelligence, Responsible AI and human-AI collaboration.
Six capabilities this program is built to give professionals moving from using AI tools to designing AI enabled work.
Match LLMs, RAG, copilots and agents to the specific business problem you're solving.
Build multi step, reusable prompt systems with decomposition, constraints and quality checks.
Design structured context packs and knowledge systems that make AI outputs consistently reliable.
Identify where AI agents can safely handle multi step tasks, with human checkpoints built in.
Use AI for complex research, scenario analysis and evidence based recommendations.
Apply risk controls, human oversight and governance by design to advanced AI workflows.
How the program moves you from advanced AI concepts to a workflow you can present as a capstone.
Business level grounding in LLMs, multimodal AI, RAG, agents and AI orchestration.
Build and stress test multi step prompts and structured context packs.
Work with organizational documents to design a grounded knowledge assistant.
Explore how AI agents handle multi step tasks within human approval boundaries.
Apply AI to realistic research, analysis and decision intelligence scenarios.
Design and present an end to end AI enabled workflow for a real business problem.
Business level grounding in LLMs, multimodal AI, RAG, agents and AI orchestration.
Build and stress test multi step prompts and structured context packs.
Work with organizational documents to design a grounded knowledge assistant.
Explore how AI agents handle multi step tasks within human approval boundaries.
Apply AI to realistic research, analysis and decision intelligence scenarios.
Design and present an end to end AI enabled workflow for a real business problem.
The real business scenarios you'll practice, pulled directly from the program's applied curriculum.
Design and present a complete AI enabled workflow: the business problem, AI architecture, prompt and context strategy, governance controls and an adoption roadmap.
The program focuses on selecting and combining the right AI capability, not memorizing a list of tools.
ChatGPT Enterprise · Microsoft 365 Copilot · Gemini · Claude
Multimodal AI · Reasoning models · RAG · Embeddings · Orchestration
NotebookLM · Enterprise Search · Document intelligence tools
Agent frameworks · Copilot Studio · Power Automate · n8n · Zapier
Excel with AI · Power BI · Tableau
A preview of the ten modules inside the program. See the full breakdown in the detailed curriculum.
AI maturity, capability levels, AI-enabled work, augmentation vs automation and AI operating models.
LLMs, multimodal AI, reasoning models, AI assistants, copilots, agents, RAG, embeddings and AI orchestration.
Prompt architecture, decomposition, few-shot, structured outputs, constraints, iterative prompting and prompt chaining.
Context architecture, business rules, reference material, data definitions, examples and context prioritization.
Enterprise knowledge, document intelligence, retrieval, semantic search, RAG and knowledge assistants.
AI agents, tools, multi-step workflows, orchestration, agent boundaries, human approval and agent risks.
Research decomposition, multi-source synthesis, hypothesis generation, comparison and evidence evaluation.
Data interpretation, pattern discovery, scenario analysis, decision frameworks and recommendations.
Process mapping, task decomposition, human checkpoints, automation and governance-by-design.
AI assistants, reusable prompts, knowledge systems, workflow automation and measurable AI value.
A practical introduction to AI and generative AI for all employees to understand core concepts, recognize useful applications, and use AI responsibly.
Hands-on foundation for generative AI tools, prompt principles, and everyday workplace assistance.
Essential training on confidentiality, data privacy, hallucination verification, and safe enterprise AI usage.
Generic AI training is failing the enterprise. A finance director, an HR manager, and a software engineer require fundamentally different AI capabilities. Discover why role-based enablement—anchored in actual workflows, decisions, and domain expertise—is the only sustainable path to enterprise AI value.
Most enterprises conflate AI literacy (knowing what AI is) with AI capability (knowing how to use AI effectively in your role). This confusion leads to generic training that fails to change behaviour or drive ROI. Discover how to build true AI capability.
Enterprise AI initiatives are failing at scale not due to technological flaws, but because traditional IT training models are entirely unsuited for probabilistic AI tools. Discover why a human-centred capability building approach is essential.
Every module, topic, activity and practical application, laid out in the detailed curriculum.