Course Details
Course Details
What You'll Learn
Topic 1: Prompting and Task Execution
Topic 2: Output Evaluation and Validation
Topic 3: Product and Model Selection
Topic 4: Workflow Integration and Solution Design
Topic 5: Configuration and Knowledge Management
Topic 6: Governance, Risk, and Responsible Use
Topic 7: Troubleshooting and Optimization
Course Info
Minimum Entry Requirement
Knowledge and Skills
- Able to operate using computer functions
- 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: 18-65 years old
Minimum Software/Hardware Requirement
Software:
You will need the following for this course:
- A Claude Pro (or higher) subscription – required
- Claude desktop app – free download (optional, the web app also works)
Hardware: Windows PC or Mac laptop
How to Apply HRD Corp Funding
This course is HRD Corp claimable for employers registered with HRD Corp, under the HRD Corp Claimable Courses scheme (SBL-Khas). Your company applies for the grant before the class; we submit the training provider claim after it.
- Check your levy balance - your company must be registered with HRD Corp and have enough levy balance to cover the course fee.
- Request a quotation - contact us for the quotation, course content and trainer profile; you attach these to the grant application.
- Apply for the grant in eTRiS before the class - log in to your employer eTRiS account, go to Application > Grant > Apply Grant, choose the scheme HRD Corp Claimable Courses (SBL-Khas), select us as the training provider and this course, add your trainees, attach the quotation, course content and trainer profile, and submit.
- Submit in time - for public classes, submit at least 3 calendar days before the class (15 June to 31 December 2026) and at least 14 days before from 1 January 2027; in-house classes need 14 days. The training must start within 90 days of that advance submission period.
- Send us the grant approval - once HRD Corp approves the application, email us the grant ID so we can confirm your seats.
- Attend the class - trainees sign the daily attendance (T3) form.
- Claim after the class - we submit the training provider claim in eTRiS with the attendance and invoice; you then complete the employer claim and sign the JD/14 form (manager level or above). Claims must be submitted within 6 months of the training.
More details: our HRD Corp Claimable Courses page and the HRD Corp employer guidelines.
Job Roles
Job Roles
- Operations Manager
- Operations Executive
- Marketing Manager
- Marketing Executive
- Project Manager
- Business Analyst
- Management Consultant
- Corporate Communications Executive
- Communications Specialist
- Educator
- Corporate Trainer
- Human Resource Executive
- Administrative Executive
- Content Specialist
- Customer Service Manager
- Knowledge Management Specialist
- Digital Transformation Lead
- AI Adoption Champion
Trainers
Trainers
Shipping agentic AI applications that real users can try in a browser is central to the work of Dr. Alfred Ang, a full-stack AI developer, Agentic AI solution architect and corporate trainer who serves as CTO of Tertiary Infotech Academy Pte Ltd, the Singapore training organisation behind Tertiary Courses. Streamlit features prominently in Dr. Ang's portfolio: a courseware generation platform built with the Claude Agent SDK and Streamlit that automates the creation of training documents, a course-proposal generator powered by Claude, a document-generation app for training-partner procedures, and data-mining-ml-labs, a set of interactive Streamlit labs for machine learning. Dr. Ang has also built RAG systems, from n8n-ragdemo, in which a Gemini-powered Telegram agent answers questions over uploaded PDFs, to n8n-ragdemo2, a customer-service chatbot over a library of course brochures. Guardrails and alignment are treated as first-class concerns, as in n8n-hrportal, whose HR chatbot is protected by input and output guardrails and human-in-the-loop approvals. Multi-agent orchestration appears in an ERP prototype that coordinates AI agents for procurement, invoicing and replenishment, and in AI-LMS-TMS, a training management system with built-in agent automation. More than 300 public repositories at github.com/alfredang demonstrate the full journey from framework experiment to deployed, guarded application. Dr. Ang has also compared several agent frameworks in practice, learning where each one shines, where it struggles and how to keep code portable as the ecosystem evolves. That comparative, hands-on perspective shapes the structure of the whole course. Lessons from failed experiments are shared as openly as the successes.
Build Multi Agent Systems with ADK, Streamlit, Autogen and CrewAI gives learners a practical tour of today's leading agent frameworks. The first topic, agentic AI app development with agentic AI frameworks, compares Google ADK, Microsoft Autogen and CrewAI, and has learners build agents with defined roles, tools and collaboration patterns in each, so they understand the strengths and trade-offs of every approach. The second topic, agentic AI and RAG deployment on Streamlit Cloud, adds retrieval over documents, wraps the agents in a Streamlit interface and deploys the finished application so it can be shared with colleagues or clients. The final topic, model alignment and guardrails, covers prompt-injection defences, output validation, content filtering, human-in-the-loop checkpoints and techniques for keeping agents on task and within policy. Dr. Ang codes live and explains design decisions in context, drawing on the Streamlit apps and guarded chatbots already in production to show what tends to break when agents meet real users. Participants build and deploy their own multi-agent application during the course and leave with code they can extend. Developers, data scientists and solution architects with basic Python skills will gain a clear, framework-neutral understanding of how to design, ship and safeguard multi-agent systems. Learners also explore how to monitor deployed agents, manage API keys and secrets safely on Streamlit Cloud, and estimate the running costs of different model choices, so their applications remain secure and affordable after launch. To explore the Streamlit apps, RAG chatbots and agent projects behind this course, visit Dr. Ang's portfolio at https://github.com/alfredang.
Review
Customer Reviews (6)
- Knowledgeable trainer Review by Course Participant/Trainee
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The trainer is an expert in the subject and shared many practical insights from real projects. (Posted on 22/04/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Good course materials Review by Course Participant/Trainee
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The trainer is an expert in the subject and shared many practical insights from real projects. (Posted on 06/04/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Worth every cent Review by Course Participant/Trainee
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The trainer is an expert in the subject and shared many practical insights from real projects. (Posted on 04/01/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Engaging trainer Review by Course Participant/Trainee
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The trainer is an expert in the subject and shared many practical insights from real projects. (Posted on 24/05/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Very useful course Review by Course Participant/Trainee
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Very informative and interactive. The small class size meant we got a lot of personal attention. (Posted on 17/12/2024)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
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