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Course Details
Course Details
What You'll Learn
Topic 1: Multi-AI-Agent Content Ideation and Digital Storyboarding
Topic 2: Audience Research and Content Requirement Analysis
Topic 3: Multi-Channel Content Creation and Agent Workflow Coordination
Topic 4: Content Distribution, Strategy Guidelines and Responsible AI Practices
Course Info
Prerequisite
Basic Python, terminal commands and familiarity with data or APIs are recommended for the practical exercises.
Software Requirement
Install and test the listed software before class. Confirm the required version and account or licence access in your joining instructions. Cloud and AI services may charge subscription or usage fees.
Also prepare the tools needed for the practical exercises:
Confirm the version, account permissions and any API usage budget with the trainer before class.
Hardware Requirement
Bring a Windows or Mac laptop supported by the listed software, with a working keyboard and sufficient storage for course exercises.
Bring your own computer and charger, with a reliable internet connection and permission to install the required software. For live online classes, also prepare a microphone or headset.
If you need help arranging a suitable device, contact us before the class to confirm availability.
Job Roles
Job Roles
- Content Strategist
- Copywriter
- Digital Marketing Specialist
- Content Manager
- SEO Specialist
- UX Writer
- Technical Writer
- Creative Director
- Digital Content Producer
- Machine Learning Engineer (with a content focus)
- AI Agent Workflow Developer
- Brand Communications Manager
- Blogging Strategist
- Social Media Manager
- AI Content Automation Specialist
Trainers
Trainers
Dr. Muhammed Siraj is a cybersecurity specialist and academic with 15 years of experience, serving as Senior Lecturer in the Department of Informatics and Director of Graduate and Continuous Education at Academic City University in Accra. He holds a PhD in Security in Computing from Universiti Putra Malaysia, where his research focused on blockchain security, an MSc in Information and Communication Technology from Aalborg University in Denmark, and a degree from the University of Ghana. He is a licensed independent assessor with Ghana's Cyber Security Authority, holds leadership roles in national cybersecurity and privacy professional bodies, and is certified as a Certified Ethical Hacker (CEH), Computer Hacking Forensic Investigator (CHFI) and Certified Data Protection Supervisor (CDPS). Before joining Academic City, he served as Acting Director of ICT and Data Protection Supervisor at Wisconsin International University College. His expertise spans penetration testing, digital forensics, incident response, malware analysis, cryptography, cloud and IoT security, zero trust architecture, cyber threat intelligence, data protection, and governance, risk and compliance.
Dr. Siraj's research interests cover blockchain, cybersecurity, distributed computing, consensus protocols and machine learning, with published work on blockchain consensus security, smart-contract privacy preservation for sensitive records in the cloud, and new consensus mechanisms. This background gives him a distinctive perspective on artificial intelligence: as organisations adopt AI tools, agents and data-driven automation, he helps learners understand how to protect the data these systems depend on, recognise new attack surfaces, and put sound governance, privacy and access controls in place so that AI can be used safely and responsibly. In the classroom he connects technical practice with regulation, privacy and human factors, drawing on real-world security and data-protection cases to show how concepts apply in professional settings, and his experiential, hands-on teaching style has made him a trusted trainer for students and working professionals alike.
Getting several AI agents to plan, retrieve information and act together is a problem Dr. Alfred Ang solves in day-to-day engineering, not just in the classroom. Dr. Ang is a full-stack AI developer and Agentic AI solution architect, a corporate trainer, and Chief Technology Officer of Tertiary Infotech Academy Pte Ltd in Singapore, the organisation behind Tertiary Courses. A good example is an automated video production pipeline in which a topic request from a web form triggers an agent that researches the subject, writes the script, renders the animation, verifies the result and publishes it, each stage handing work to the next. Dr. Ang has also built retrieval-augmented chatbots with n8n, including a Telegram agent that answers questions from uploaded PDFs and a customer-service assistant whose course brochures are ingested into Supabase, Pinecone or Qdrant vector databases. Further projects include an ERP prototype where AI agents prepare purchase orders that pass through human-in-the-loop approvals by email, Asana or Telegram, a stock-analysis Telegram agent that reasons through Buy, Sell or Hold recommendations, and an AI-powered content platform built on the Claude Agent SDK with a self-improving chatbot. Beyond agents, Dr. Ang builds complete products end to end, from front end and back end to databases, cloud deployment and native mobile apps, including the self-hosted AI learning and training management system used to run classes. More than 300 public repositories document this work on GitHub, offering a rare look at how multi-agent ideas behave once real users and real data are involved.
In this Multi Agents System with AutoGen course, Dr. Ang uses that experience to keep the focus on agents that actually finish useful work. The course begins with the foundations: how large language models behave, what turns a model into an agent, and how AutoGen compares with CrewAI as a framework for building them. Learners then create a first agent with AutoGen AgentChat, giving it a clear role, instructions and tools, and watching how it reasons through a task. The second topic tackles retrieval-augmented generation, explaining why agents need access to fresh, trusted information and guiding learners through building a RAG agent that grounds its answers in their own documents rather than guessing. The final topic brings everything together in multi-agent workflows, where learners design agents with distinct responsibilities, decide how they hand work to one another and orchestrate the whole team in AutoGen to automate a complex task. Dr. Ang teaches by building in small steps, running each version, reading the agent conversation and adjusting roles or prompts when the output drifts, which mirrors how agent systems are refined in practice. Lessons drawn from production work run throughout: keeping each agent's job narrow, inserting a human review point where decisions matter, and testing behaviour before trusting it with real tasks. Learners leave with working AutoGen code they can extend for their own organisation and a clear mental model of when multiple agents add value. For more examples of agentic systems in action, browse Dr. Ang's public repositories at https://github.com/alfredang
Review
Customer Reviews (7)
- Knowledgeable trainer Review by Course Participant/Trainee
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The course materials were detailed and easy to reference afterwards. Great value for money. (Posted on 3/1/2026)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 - Exceeded my expectations 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 11/17/2025)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 - Fantastic experience Review by Course Participant/Trainee
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The course content was comprehensive and up to date. The practical exercises were the best part. (Posted on 10/5/2025)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 - Learned a lot Review by Course Participant/Trainee
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Very engaging session. The trainer patiently answered all our questions and gave useful tips. (Posted on 7/8/2025)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 - Great learning experience 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 6/27/2025)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
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