Create Agentic AI Automations Without Coding
About This Course
In the fast-evolving world of AI, understanding how to design and deploy intelligent agents—without writing a single line of code—is becoming an essential skill. This course on Agentic AI provides a practical, step-by-step journey into the world of AI agents, empowering learners to conceptualize, build, and deploy AI workflows using non-coding platforms.
Designed for professionals and enthusiasts in product management, technology, and innovation roles, this course demystifies the concepts of agentic AI, chatbot development, and Retrieval Augmented Generation (RAG). Learners will explore no-code tools like n8n, Langflow, Agentx, Flowise, HeyGen, and Microsoft Copilot Studio, gaining hands-on experience to rapidly prototype and deploy AI applications.
Structured across three progressive learning units, the course first establishes foundational knowledge of AI agents and workflows, then guides learners through building practical chatbot solutions, and finally moves into advanced applications like RAG for deep research and contextual response systems. Whether you're aiming to improve customer service, automate internal workflows, or build AI-driven products, this course equips you with the right tools and frameworks.
By the end of the course, you'll not only understand the difference between generative and agentic AI, but also be able to create functional AI agents that solve real-world problems—boosting efficiency, user engagement, and business innovation.
What You'll Learn
🔹 Unit 1: Introduction to AI Agents and Workflows
Understand what Agentic AI is, and how it differs from Generative AI.
Explore key reasoning frameworks that power intelligent agents.
Analyze use cases across industries and identify where agentic workflows can be applied.
Create your first AI agent using platforms like n8n and Langflow.
🔹 Unit 2: Developing AI Chatbots
Dive into no-code chatbot development using Agentx, Promptly, and Flowise.
Learn how to integrate digital human avatars via HeyGen to create engaging AI experiences.
Correlate AI algorithm design with efficiency in product management workflows.
Improve existing agent applications for real-world use cases.
🔹 Unit 3: Implementing RAG Applications
Understand the architecture and benefits of Retrieval Augmented Generation (RAG).
Build agentic RAG applications to enhance AI reasoning and context retention.
Leverage Microsoft Copilot Studio to develop intelligent RAG-based search and research agents.
Evaluate AI’s effectiveness and feasibility for product development and maintenance.
By progressing from foundational theory to hands-on practice and advanced applications, learners are equipped not just with tools, but with strategic insight into building scalable, intelligent systems.
Entry Requirements
Knowledge and Skills
• Able to operate computer functions with minimum Computer Literacy Level 2
• 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 years and above