Build Agentic AI Apps with Claude Code & Codex
About This Course
This comprehensive course equips you with essential skills to harness generative AI effectively across diverse professional applications. You will explore the fundamental principles and theories underpinning generative AI models, understand the critical distinction between generative and agentic AI approaches, and discover how to leverage these technologies for content summarization, inference, reasoning, transformation, and augmentation. The program emphasizes practical prompt engineering techniques that directly in-fluence model outputs, while developing your ability to evaluate AI performance metrics and analyze the impact of prompt variations. You will also ex-amine crucial considerations including data quality, preprocessing, model training pipelines, and the ethical implications of AI-generated content, including potential biases and limitations. Ideal for professionals seeking to integrate AI capabilities into their workflows, this course provides real-world use cases, enabling you to make informed decisions about implementing generative & Agentic AI solutions responsibly and effectively in your organization.
What You'll Learn
LO1: Demonstrate applications of generative AI and distinctions between model types across industries.
LO2: Apply prompt engineering techniques and analyse output variations to improve generative AI performance in practical use cases.
LO3: Identify ethical risks and analyse bias in AI-generated content across industries.
Course Outline
LU1: Generative AI Fundamentals
T1: Underlying principles, core concepts and theories governing generative AI
T2: Difference between generative and discriminative models
T3: Demonstrate the use of generation AI in diverse applications (e.g., summarisation, inference, reasoning, transformation of content, augmentation of content)
LU2: Prompt Engineering
T1: Importance of data quality, preprocessing, model pipeline and model training (e.g., impact of data bias from training data)
T2: Impact of prompt engineering on the model outputs of generative AI
T3: Apply understanding of generative AI principles to use cases
T4: Analyse generative AI models' performance metrics and evaluate the influence of prompt variations
LU3: Ethical Considerations
T1: Generative AI model workings, including training data, algorithms, and outputs
T2: Identify the ethical implications and societal impact of AI-generated content
T3: Analyze limitations and potential biases in AI-generated content
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.
• Minimum 18 years old