Claude Certified Architect Foundation
About This Course
he Claude Certified Architect Foundation course equips learners with the knowledge and practical skills to design, build, and deploy AI applications using Anthropic's Claude ecosystem. Participants will develop a strong foundation in large language models (LLMs), prompt engineering, context engineering, and AI solution architecture for building reliable, scalable, and secure enterprise applications.
Through hands-on labs, learners will explore Claude's core capabilities, including long-context reasoning, structured outputs, artifacts, tool use, Model Context Protocol (MCP), and AI agent workflows. The course covers best practices for integrating external APIs, enterprise systems, and Retrieval-Augmented Generation (RAG) to create intelligent, context-aware applications.
Participants will learn how to design effective prompts, manage context and memory, evaluate AI performance, implement guardrails, reduce hallucinations, and optimize applications for accuracy, reliability, and cost. The course also introduces architecture patterns such as human-in-the-loop workflows, multi-agent collaboration, MCP integrations, security, governance, and responsible AI practices.
By the end of the course, learners will be be able to architect Claude-powered AI solutions, integrate Claude with business systems and external tools, and apply industry best practices to build production-ready AI applications. This course is ideal for solution architects, software developers, AI engineers, technical consultants, and IT professionals seeking a solid foundation in enterprise AI architecture with Claude.
What You'll Learn
LO1:Implement generative AI models using deep learning architectures matched to problem requirements and evaluate model suitability.
LO2: Apply deep learning concepts and optimisation techniques to preprocess generative-model datasets using embeddings and tokenisation, ensuring clean and structured inputs for effective neural network training.
LO3: Identify model training requirements and optimise performance by applying data-preprocessing, de-duplication, embeddings, and tokenisation techniques, as well as assessing training efficiency across parallel and cluster-based environments using benchmarks and metrics.
LO4:Train and refine generative models by evaluating weaknesses and applying targeted fine-tuning strategies.
Course Outline:
Topic 1: Foundations of Claude AI Architecture
Topic 2: Building Claude-Powered AI Applications
Topic 3: AI Agents and Enterprise Integration
Topic 4: Deploying Production-Ready AI Solutions
Entry Requirements
Knowledge and Skills
• Able to operate computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
• Positive Learning Attitude
• Enthusiastic Learner
Experience
• Minimum of 1 year of working experience.
Target Age Group: 21 to 65 years old