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Advanced NLP with Large Language Models (LLM

Course Information

  • Sessions 2 days
  • Duration 15 hrs
  • Level Beginner
  • Assessment NA

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

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Certification

  • Certificate of Completion from Tertiary Infotech - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Infotech.

Build Powerful Agentic AI Workflows with Langflow and MCP

Course Code: C804

3 Review(s) | Add Your Review

What's This Course About

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.

Funding Options

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 Fee

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

Course Date

Course Time

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Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

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.

Cancellation & Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
  • 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

Course Details

What You'll Learn

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

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

Trainers

Teh Siew Yee

Teh Siew Yee is an experienced adult educator and corporate trainer specializing in business communication, workplace effectiveness, and professional development. With years of experience across both corporate and training environments, she has helped learners enhance their skills in problem-solving, collaboration, and interpersonal communication. Her ability to translate complex concepts into clear, practical strategies ensures that participants can immediately apply their learning in the workplace.

As an ACLP-certified trainer, Siew Yee delivers WSQ courses with a strong focus on learner engagement and workplace application. She integrates case studies, role-plays, and reflective exercises into her sessions, ensuring participants develop not only knowledge but also confidence in real-world contexts. By combining her corporate experience with adult education expertise, she empowers learners to improve workplace efficiency, strengthen teamwork, and achieve personal and organizational success.

Review

Customer Reviews (3)

might 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
/ (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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