AI Architect: The Master Course in Prompt Engineering
Definitive masterclass in advanced prompt design and AI application development
Master advanced prompt engineering from foundational principles to multi-modal design, API-level instruction, prompt chaining, and building production-grade prompt-based applications.
At a Glance
Who it's for
- Developers building AI-powered applications
- AI Specialists and Machine Learning Engineers
- Data Scientists working with LLMs
- Content Strategists designing AI workflows
- IT Professionals architecting AI solutions
Course Details
Course Overview
This definitive 120-hour masterclass takes technical and creative professionals from foundational prompt engineering principles to advanced, production-grade AI application development. You'll master multi-modal prompt design, API-level instructions, sophisticated prompt chaining architectures, function calling patterns, and the complete lifecycle of building, testing, and deploying prompt-based systems. Through intensive hands-on projects, you'll work with leading LLM platforms including OpenAI GPT-4, Claude, Gemini, and Azure OpenAI Service. The course culminates in an expert-reviewed capstone project where you'll architect and build a complete AI-powered application. Perfect for developers, AI specialists, data scientists, and IT professionals architecting next-generation intelligent systems for Australian enterprises.
What You'll Learn
Course Curriculum
Module 1: Foundations of Prompt Engineering
15 hours- Understanding large language model architecture and behaviour
- Core prompting principles: clarity, context, constraints
- Zero-shot, one-shot, and few-shot learning patterns
- Prompt structure, delimiters, and formatting best practices
- Temperature, top-p, and other generation parameters
- Common failure modes and debugging techniques
Module 2: Advanced Prompting Techniques
18 hours- Chain-of-thought (CoT) reasoning and step-by-step decomposition
- Tree-of-thought and self-consistency methods
- ReAct (Reasoning + Acting) patterns
- Self-critique, reflection, and iterative refinement
- Prompt compression and token optimisation
- Contextual embeddings and retrieval-augmented generation (RAG)
- Multi-turn conversation design and memory management
Module 3: Multi-Modal Prompt Design
16 hours- Vision-language models and image-based prompting
- Audio transcription and audio-to-text prompt patterns
- Text-to-image generation with DALL-E, Midjourney, Stable Diffusion
- Cross-modal reasoning and unified prompt architectures
- Video understanding and temporal reasoning
- Structured data integration (CSV, JSON, databases)
- Document analysis and multimodal RAG systems
Module 4: API-Level Prompt Engineering
18 hours- OpenAI API, Anthropic Claude API, Google Gemini API deep dives
- Function calling and tool use patterns
- Structured outputs with JSON mode and schema enforcement
- System messages, role-based prompting, and instruction hierarchies
- Streaming responses and async processing
- Batch processing and cost optimisation strategies
- Fine-tuning custom models for specialised prompting
Module 5: Prompt Chaining and Agent Architectures
20 hours- Sequential prompt chains for complex workflows
- Conditional branching and dynamic routing
- Agent frameworks: LangChain, AutoGPT, BabyAGI
- Tool-augmented agents with function calling
- Multi-agent collaboration and orchestration
- State management and conversation persistence
- Error handling, retries, and fallback strategies
- Autonomous task decomposition and planning
Module 6: Testing, Evaluation, and Security
13 hours- Quantitative evaluation metrics for prompt quality
- A/B testing and statistical significance
- Human evaluation frameworks and feedback loops
- Adversarial testing and red-teaming prompts
- Prompt injection defences and input sanitisation
- Data leakage prevention and privacy controls
- Bias detection and fairness evaluation
- Compliance with Australian Privacy Principles in prompt design
Module 7: Production Deployment and Monitoring
10 hours- Prompt versioning and template management
- Observability: logging, tracing, and debugging
- Performance monitoring and latency optimisation
- Cost tracking and budget controls
- Scaling strategies for high-volume applications
- CI/CD pipelines for prompt-based systems
- Incident response and prompt rollback procedures
- Australian regulatory compliance in production AI systems
Module 8: Capstone Project
10 hours (+ independent work)- Capstone project scope and requirements definition
- Building a complete prompt-based application end-to-end
- Applying advanced techniques in real-world scenarios
- Expert review and personalised feedback sessions
- Presentation and documentation of final project
- Portfolio development for AI engineering roles
Who Should Attend
- Software developers building AI-powered applications
- AI specialists and machine learning engineers
- Data scientists working with large language models
- Content strategists designing conversational AI workflows
- IT professionals architecting enterprise AI solutions
- Product managers overseeing AI feature development
- Technical architects evaluating LLM integration strategies
Prerequisites
Before enrolling, please ensure you meet these requirements:
- • Strong programming skills in Python, JavaScript, or similar languages
- • Experience with REST APIs and software development
- • Understanding of fundamental AI/ML concepts
- • Familiarity with JSON, data structures, and software architecture
- • Access to LLM API services (OpenAI, Anthropic, or similar)
Delivery, Format and Logistics
Delivery Mode
Self-paced with expert capstone review and live masterclasses
Maximum 20 participants for personalised capstone feedback
What You'll Need
- Strong programming experience (Python, JavaScript, or similar)
- Understanding of APIs and software architecture
- Familiarity with AI/ML concepts and terminology
- Development environment with API access capabilities
- Commitment to completing hands-on projects and capstone
What You'll Receive
- 120 hours of comprehensive video instruction
- Hands-on coding projects and prompt design exercises
- API access credits for OpenAI, Anthropic, and Google AI
- Expert 1-on-1 review of your capstone project
- Monthly live masterclasses with industry practitioners
- Access to private prompt engineering community
- Case studies from Australian enterprise AI implementations
- Prompt template library and reusable code frameworks
- Certificate of completion with capstone showcase
- 18 months access to all course materials and updates
- Lifetime access to alumni network and job board
Frequently Asked Questions
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Next Intake
September 2026 — register your interest at educ4te.com
Format
Self-paced with expert capstone review and live masterclasses
Group & Enterprise Options
Discounted rates available for teams of 3+ delegates. Contact us for in-house delivery options.
What's Included
- 120 hours of comprehensive video instruction
- Hands-on coding projects and prompt design exercises
- API access credits for OpenAI, Anthropic, and Google AI
- Expert 1-on-1 review of your capstone project
- Monthly live masterclasses with industry practitioners
- Access to private prompt engineering community
- Case studies from Australian enterprise AI implementations
- Prompt template library and reusable code frameworks
- Certificate of completion with capstone showcase
- 18 months access to all course materials and updates
- Lifetime access to alumni network and job board
Have questions about this course?