• Home
  • Building Multi Agent Aplications with Gemini ADK

Building Multi Agent Aplications with Gemini ADK

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.

Course Brochure

Download Course Brochure

Certification

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

Building Multi Agent Aplications with Gemini ADK

Course Code: C829

2 Review(s) | Add Your Review

Share

What's This Course About

Master the art of building intelligent multi-agent applications with Google's Gemini ADK in this comprehensive, hands-on course. You will start by understanding single agent foundations — including agent lifecycle, model configuration, structured input/output, and session handling — before progressing to advanced topics such as function calling, tool execution, external API integration, and vector database-powered memory systems. This course equips you with the practical skills to design, build, and deploy AI agents that can reason, remember, and take action autonomously.

Take your AI development expertise to the next level by learning how to architect sophisticated multi-agent systems using supervisor, hierarchical, and pipeline patterns. You will explore agent-to-agent communication, shared memory, workflow orchestration, and the Model Context Protocol (MCP) for structured context passing and tool discovery. With dedicated modules on production-grade design — covering routing strategies, observability, security guardrails, and deployment at scale — you will graduate ready to build robust, enterprise-quality multi-agent applications powered by Gemini ADK.

Funding Options

For WSQ funding, please checkout the details at WSQ - Develop Artificial Intelligence and Large Language Model (LLM) Applications with Google Gemini

Course Fee

$700.00 (GST-exclusive)
$763.00 (GST-inclusive)

Course Date

Course Time

* Required Fields

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: Single Agent Foundations

Overview of Gemini ADK architecture

Agent lifecycle (User → Model → Tools → Memory → Response)

Model configuration and system instructions

Structured input and JSON output

Stateless vs stateful agents

Session handling basics

Building a single agent application

Topic 2: Tools, Memory and Sessions

Function calling and tool execution flow

External API integration

Custom tools (calculator, retrieval, database)

Tool chaining and error handling

Short-term memory (conversation history)

Long-term memory concepts

Vector database integration

Session management and user tracking

Topic 3: Multi-Agent Architecture

Why multi-agent systems

Agent specialization and separation of concerns

Supervisor, hierarchical and pipeline patterns

Agent-to-agent communication

Shared memory across agents

Workflow orchestration and delegation

Building a multi-agent application

Topic 4: MCP and Production Design

Model Context Protocol (MCP) fundamentals

Context envelope and capability declaration

Tool registry and discovery

Structured context passing between agents

Routing strategies (rule-based vs LLM-based)

Observability and tracing

Security and guardrails

Deployment and scaling considerations

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 Solutions Architect
  • Machine Learning Engineer
  • Multi-Agent Systems Developer
  • AI Platform Engineer
  • Conversational AI Developer
  • LLM Application Developer
  • AI Integration Specialist
  • Agentic AI Engineer
  • AI Product Manager
  • Natural Language Processing Engineer
  • AI Automation Engineer
  • Cloud AI Engineer
  • AI DevOps Engineer
  • Intelligent Systems Designer
  • AI Research Engineer
  • Full Stack AI Developer
  • AI Infrastructure Engineer
  • Chatbot and Virtual Agent Developer
  • AI Technical Consultant
  • Enterprise AI Developer

Trainers

Trainers

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.
CY Quah is an ACLP-certified trainer and data science professional with extensive experience in Python, NLP, and machine learning. He has led AI training programs for SAP, Temasek Polytechnic, and IMDA under the SGUnited Mid-Career Pathways initiative, and has delivered corporate workshops on text analytics, recommender systems, and chatbot development. His expertise includes applying NLP tools such as NLTK, spaCy, and Gensim for sentiment analysis, topic modeling, and text classification.
Solomon Soh is an experienced Data Scientist and AI Trainer with a strong record of teaching and mentoring in Python programming, data analytics, and machine learning. Currently a Data Science Trainer with IBM Singapore, he has coached teams on projects involving natural language processing, computer vision, and chatbots, achieving a 96% learner satisfaction rating for his communication and technical expertise. His career spans roles at Workforce Optimizer, Certis Cisco, Ernst & Young, and IQVIA, where he applied Python-driven analytics to improve operations, optimize staffing, and deliver actionable insights. His academic background includes a double degree in Economics and Psychology from Singapore Management University (Summa Cum Laude, triple major in Analytics), an MBA, and a Master’s in Financial Engineering.
Yap Swee Leong is an ACLP-certified trainer with experience in adult education and IT-focused training. He has delivered courses across digital systems, IT fundamentals, and business technology, equipping learners with the skills to adapt to digital workplaces. With his strong foundation in instructional design and applied learning, he makes technical concepts accessible to diverse groups of learners. In his network security training, Yap focuses on building beginner-level understanding of key security principles, including password policies, secure browsing, and basic risk management. His sessions are designed to provide non-technical learners with confidence in recognizing and addressing everyday cybersecurity threats. By using practical, relatable examples, he ensures participants develop essential habits for safeguarding personal and organizational data.

Review

Customer Reviews (2)

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
Programme is good, covers both theory and codes. Codes are useful for application. (Posted on 4/20/2020)
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
Add some more machine learning forecasting elements (Posted on 8/27/2019)

Write Your Own Review

You're reviewing: Building Multi Agent Aplications with Gemini ADK

How do you rate this product? *

  1 star 2 stars 3 stars 4 stars 5 stars
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