
Artificial Intelligence is rapidly transforming the way applications are designed, developed, and automated. Modern AI coding assistants such as Claude Code and Codex now enable users to generate code, automate workflows, create intelligent assistants, and accelerate software development using natural language instructions.
This highly practical and beginner-friendly course introduces learners to the fundamentals of Agentic AI application development using Claude Code and Codex. Participants will explore how AI-powered coding tools can assist in generating applications, improving productivity, automating repetitive tasks, and supporting intelligent business workflows.

The course covers key concepts including generative AI, agentic AI, prompt engineering, AI-assisted coding, workflow automation, and responsible AI practices. Learners will also gain hands-on exposure to creating simple AI-powered applications, generating and refining code, building AI workflows, and evaluating AI-generated outputs.
Designed for both technical and non-technical professionals, this course focuses on practical use cases and real-world demonstrations to help learners confidently begin their journey into AI-powered application development and automation.

LU1: AI Fundamentals
T1: Underlying Principles, Core Concepts and Theories Governing Generative AI
- Introduction to Generative AI and Agentic AI
- Understanding LLMs and AI coding assistants
- Introduction to Claude Code and Codex
- AI reasoning, workflows, and automation concepts
- Fundamentals of AI-powered app development
T2: Difference Between Generative and Discriminative Models
- Generative vs discriminative AI models
- AI chatbots vs AI agents
- Single-agent and multi-agent systems
- AI copilots and autonomous workflows
- Comparing Claude, Codex, ChatGPT, and Gemini
T3: Demonstrate the Use of AI in Diverse Applications
- AI for coding, summarisation, and automation
- Building simple AI-powered applications
- Creating AI workflows and assistants
- Business use cases for Agentic AI
- Hands-on AI app demonstrations
LU2: Prompt Engineering for Agentic Coding
T1: Importance of Data Quality, Preprocessing, Model Pipeline and Model Training
- Importance of data quality and context
- Understanding prompts and model pipelines
- Managing hallucinations and AI limitations
- AI-assisted development workflows
- Testing and refining AI-generated outputs
T2: Impact of Prompt Engineering on Model Outputs of Generative AI
- Fundamentals of prompt engineering
- Structuring effective prompts
- Multi-step and chain-of-thought prompting
- Prompt engineering for Claude Code and Codex
- Generating and refining AI-generated code
T3: Apply Understanding of Generative AI Principles to Use Cases
- Creating AI assistants and chatbots
- Building simple AI productivity tools
- Automating business workflows
- AI-assisted coding and debugging
- Beginner-friendly AI app exercises
T4: Analyse Generative AI Models’ Performance Metrics and Evaluate the Influence of Prompt Variations
- Evaluating AI-generated outputs
- Measuring accuracy and relevance
- Comparing prompt variations
- Improving consistency and reliability
- Validating AI-generated code and content
LU3: Ethical Considerations
T1: Generative AI Model Workings, Including Training Data, Algorithms, and Outputs
- How AI models are trained
- Data privacy and governance considerations
- AI security and responsible AI usage
- Risks of exposing confidential information
T2: Identify the Ethical Implications and Societal Impact of AI-Generated Content
- Ethical use of AI-generated content
- Human-AI collaboration
- Workplace impact of AI adoption
- Responsible AI implementation
T3: Analyze Limitations and Potential Biases in AI-Generated Content
- Biases and hallucinations in AI systems
- Risks of inaccurate AI-generated outputs
- Human validation and review practices
- Best practices for trustworthy AI usage
By the end of this course, learners will be able to:
- Understand the core concepts of Generative AI and Agentic AI
- Differentiate between generative AI systems, AI agents, and traditional automation approaches
- Understand how Claude Code and Codex can be used for AI-assisted application development
- Apply prompt engineering techniques to improve AI-generated outputs
- Generate and refine code using AI coding assistants
- Build simple AI-powered applications and workflows
- Evaluate AI-generated content and code for accuracy, quality, and reliability
- Understand the limitations, risks, and ethical considerations associated with AI-generated outputs
- Identify practical workplace and business use cases for Agentic AI technologies
Participants are not required to have prior programming or AI development experience.
However, learners should ideally have:
- Basic computer literacy
- Familiarity with using web applications and online tools
- Basic understanding of business processes or workflows
- Interest in AI, automation, or application development
Prior exposure to coding, scripting, or generative AI tools such as ChatGPT or Claude would be beneficial but is not mandatory.
-
This course is suitable for:
- Business professionals exploring AI tools and automation
- Executives and managers interested in AI transformation initiatives
- Data analysts and power users
- IT professionals and system administrators
- Beginner developers and aspiring AI developers
- Process improvement and operations teams
- Innovation and digital transformation teams
- Educators, trainers, and consultants
- Anyone interested in learning how AI coding assistants can help build intelligent applications and workflows
Post-Course Support
- We provide free consultation related to the subject matter after the course.
- Please email your queries to training@intellisoft.com.sg and we will forward your queries to the subject matter experts.
Venue:
All courses are conducted at Intellisoft Training Rooms at 190 Middle Road, 10-08 Fortune Centre, Singapore 188979.
Short walk from Bencoolen MRT, Bugis, Rochor, Bras Basah MRT stations. The venue is disabled-friendly. For directions, click Contact Us.
By the end of this course, learners will be able to:
- Understand the core concepts of Generative AI and Agentic AI
- Differentiate between generative AI systems, AI agents, and traditional automation approaches
- Understand how Claude Code and Codex can be used for AI-assisted application development
- Apply prompt engineering techniques to improve AI-generated outputs
- Generate and refine code using AI coding assistants
- Build simple AI-powered applications and workflows
- Evaluate AI-generated content and code for accuracy, quality, and reliability
- Understand the limitations, risks, and ethical considerations associated with AI-generated outputs
- Identify practical workplace and business use cases for Agentic AI technologies
-
This course is suitable for:
- Business professionals exploring AI tools and automation
- Executives and managers interested in AI transformation initiatives
- Data analysts and power users
- IT professionals and system administrators
- Beginner developers and aspiring AI developers
- Process improvement and operations teams
- Innovation and digital transformation teams
- Educators, trainers, and consultants
- Anyone interested in learning how AI coding assistants can help build intelligent applications and workflows
LU1: AI Fundamentals
T1: Underlying Principles, Core Concepts and Theories Governing Generative AI
- Introduction to Generative AI and Agentic AI
- Understanding LLMs and AI coding assistants
- Introduction to Claude Code and Codex
- AI reasoning, workflows, and automation concepts
- Fundamentals of AI-powered app development
T2: Difference Between Generative and Discriminative Models
- Generative vs discriminative AI models
- AI chatbots vs AI agents
- Single-agent and multi-agent systems
- AI copilots and autonomous workflows
- Comparing Claude, Codex, ChatGPT, and Gemini
T3: Demonstrate the Use of AI in Diverse Applications
- AI for coding, summarisation, and automation
- Building simple AI-powered applications
- Creating AI workflows and assistants
- Business use cases for Agentic AI
- Hands-on AI app demonstrations
LU2: Prompt Engineering for Agentic Coding
T1: Importance of Data Quality, Preprocessing, Model Pipeline and Model Training
- Importance of data quality and context
- Understanding prompts and model pipelines
- Managing hallucinations and AI limitations
- AI-assisted development workflows
- Testing and refining AI-generated outputs
T2: Impact of Prompt Engineering on Model Outputs of Generative AI
- Fundamentals of prompt engineering
- Structuring effective prompts
- Multi-step and chain-of-thought prompting
- Prompt engineering for Claude Code and Codex
- Generating and refining AI-generated code
T3: Apply Understanding of Generative AI Principles to Use Cases
- Creating AI assistants and chatbots
- Building simple AI productivity tools
- Automating business workflows
- AI-assisted coding and debugging
- Beginner-friendly AI app exercises
T4: Analyse Generative AI Models’ Performance Metrics and Evaluate the Influence of Prompt Variations
- Evaluating AI-generated outputs
- Measuring accuracy and relevance
- Comparing prompt variations
- Improving consistency and reliability
- Validating AI-generated code and content
LU3: Ethical Considerations
T1: Generative AI Model Workings, Including Training Data, Algorithms, and Outputs
- How AI models are trained
- Data privacy and governance considerations
- AI security and responsible AI usage
- Risks of exposing confidential information
T2: Identify the Ethical Implications and Societal Impact of AI-Generated Content
- Ethical use of AI-generated content
- Human-AI collaboration
- Workplace impact of AI adoption
- Responsible AI implementation
T3: Analyze Limitations and Potential Biases in AI-Generated Content
- Biases and hallucinations in AI systems
- Risks of inaccurate AI-generated outputs
- Human validation and review practices
- Best practices for trustworthy AI usage
Participants are not required to have prior programming or AI development experience.
However, learners should ideally have:
- Basic computer literacy
- Familiarity with using web applications and online tools
- Basic understanding of business processes or workflows
- Interest in AI, automation, or application development
Prior exposure to coding, scripting, or generative AI tools such as ChatGPT or Claude would be beneficial but is not mandatory.
Post-Course Support
- We provide free consultation related to the subject matter after the course.
- Please email your queries to training@intellisoft.com.sg and we will forward your queries to the subject matter experts.

SkillsFuture Ready
Singaporeans can use $500 SkillsFuture Credits for this training to offset the course fees.
Contact us for advise on how to go about claiming your SkillsFuture.
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How To Register
Register for the 2 Days Build Agentic AI Apps with Claude Code & Codex course in Singapore today.

Click on the chosen course date for Building Agentic AI Apps with Claude Code & Codex. Training course dates are available at the top of this page.
Need Help in Registering for Claude Code Course in Singapore?
Call us at +65 6252-5033, WhatsApp: +65 9066-9991
Build Agentic AI Apps with Claude Code & Codex Corporate Training Program in Singapore (Physical Class or Virtual Classroom using Zoom or Microsoft Teams)
Request a Course Brochure here or enquire about any questions regarding Agentic AI Coding training. We offer Corporate Training for your company too.
UTAP: In addition, NTUC members can utilize UTAP to offset 50% of the remaining fees (capped at $250 per year).
If you are looking to train your entire team, we can arrange to conduct the Claude Code training at your office location too. Just contact us for the quotation and suitable dates for the training.




























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