WSQ , IBF, SkillsFuture, PEI Approved Training Provider

Build Powerful Agentic AI Workflows with Langflow and MCP

This hands-on course is designed for professionals and developers keen to harness the power of Agentic AI using Langflow and Model Context Protocol (MCP). You’ll start by exploring the fundamentals of Agentic AI and Large Language Models (LLMs), including real-world use cases. Learn to build, customize, and deploy LLM-powered chatbots without coding, and get practical with Langflow installation and interface navigation. Through guided exercises, participants will create and deploy simple agentic workflows, preparing the foundation for advanced AI automation.

As the course progresses, you'll dive into building Retrieval Augmented Generation (RAG) workflows, multi-agent task flows, and Streamlit-based AI apps. Gain a comprehensive understanding of tokenization, embeddings, vector stores, and AI agent reasoning frameworks. The training concludes with the Model Context Protocol (MCP), where you'll learn to build and deploy MCP servers and clients using Langflow. Whether you're creating customer service bots, travel planners, or AI assistants, this course equips you with the tools to launch intelligent, agentic AI applications efficiently.

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant Applications

No funding is available for this course

For WSQ funding, please checkout the details at WSQ - Build Agentic AI and NLP Applications with Langflow

Course Code: C804

Fee

$600.00 (GST-exclusive)
$654.00 (GST-inclusive)

The course fee listed above is before subsidy/grant, if applicable. We will apply for the grant and send you the invoice with nett fee.

Course Date

Course Time

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Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Course Cancellation/Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom

Course Details

Topic 1 Introduction to Agentic AI and Langflow

  • Overview of Agentic AI and LLM
  • Use Cases of Agentic AI and LLM
  • Build and Deploy Your Non Code LLM Powered Chatbot
  • Installation of Langflow
  • Explore Langflow Interface
  • Build and Deploy a Simple Agentic AI Flow with Langflow

Topic 2 Build a RAG with Langflow

  • Overview of Tokenization, Embedding and Vector Store
  • Introduction to Retrieval Augmented Generation (RAG)
  • Chucking Strategies
  • Best Practices of Using RAG
  • Build a RAG workflow with Langflow

Topic 3 Build an AI Agent with Langflow

  • Overview of AI agent fundamentals - tools, memories and LLM
  • Reasoning framework for AI agents
  • Build a sequential task multi agent workflow on Langflow
  • Build a travel planning agent workflow on Langflow

Topic 4 Build a Streamlit AI Chabot App

  • Streamlit fundamentals
  • Create a LLM chatbot with Streamlit
  • Create and deploy a text classifier with Streamlit

Topic 5 Model Context Protocol (MCP)

  • Overview of Model Context Protocol MCP
  • Create MCP Client and Server with Langflow
  • Deploy a Langflow MCP server

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

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:

TBD

Hardware: Window or Mac Laptops

Job Roles

  • AI Workflow Developer
  • AI Solutions Engineer
  • Conversational AI Designer
  • LLM Application Developer
  • Chatbot Developer
  • AI Product Manager
  • Data Scientist (LLM Applications)
  • Machine Learning Engineer
  • AI Research Assistant
  • RAG Engineer
  • NLP Engineer
  • AI Automation Specialist
  • Technical Innovation Lead
  • Digital Transformation Consultant
  • Software Developer (AI Tools)
  • Customer Experience Technologist
  • Streamlit App Developer
  • AI Solutions Consultant
  • Agentic Systems Engineer
  • AI Project Coordinator

Trainers

Solomon Soh Zhe Hong: Solomon is ACTA certified and has trained and coached over 100 professionals in the area of data science, python programming and coding. Solomon is a Certified AI Engineer Associate by AI Singapore and holds certifications in Alibaba Cloud Architect and Alteryx respectively. Solomon interests include Reinforcement Learning, Natural Language Processing and Time-Series analysis.

Alfred Yap Swee Leong: Alfred Yap is an ACLP certified trainer with strong financial and shopper marketing domain background and extensive experience in information technology. In addition, he is both an IBM certified Cloud Computing Practitioner and an IBM Enterprise Design Thinking Practitioner.
Alfred Yap has spent decades teaching adult learners since the 90s. Kickstarting his teaching career as a trainer for Oracle University. Thereafter, he has had vast experience conducting ICT related training to various companies in the Consulting, Media, and Training industry.
Alfred Yap earned his undergraduate degree from USF, America and master degree from NTU, Singapore majoring in Knowledge Management. His current interests include Cyber Security, Cloud computing and Blockchain.

Customer Reviews (3)

might recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
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3. How do you find the training environment
/ (Posted on 1/26/2024)
Interesting course in this GPT era. Review by Course Participant/Trainee
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
So far so good, the pace is match with my learning. (Posted on 12/1/2023)
will recommend Review by Course Participant/Trainee
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
Already good (Posted on 12/1/2023)

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