HIGAET AI Agent Builder
Build practical no-code and low-code AI agents using visual builders, knowledge bases, and integrations, ending with a deployed assistant for a real workflow.
Duration
8 weeks · 6-8 hours/week
Level
Intermediate
Delivery
Online
Status
Open for enrollment
Why this technology matters.
AI agent building is the practice of creating working assistants with visual no-code and low-code builders, knowledge bases, and integrations instead of writing everything from scratch. It matters now because many teams need a useful assistant for a real workflow quickly, without a full engineering project.
Support teams, small businesses, and operations staff use these agents to answer FAQs, route requests, and handle routine conversations from documents and knowledge sources. They solve fast deployment for well-scoped workflows with clear fallback and escalation paths, but they do not fix missing or outdated knowledge, poorly defined intents, or processes that truly need custom code.
By the end you will be able to build a conversational flow with intents, entities, and fallback paths, a knowledge-backed FAQ assistant grounded in documents, and a deployed assistant with escalation rules for a real workflow.
Why this course exists
The gap is between a clickable prototype and a deployed assistant that answers from real knowledge, handles fallbacks, and escalates safely. This course teaches the arc from Model and Prompt through Context and Retrieval to Tools, Evaluation, and Production, so students can ship a dependable low-code agent for a live workflow.
Know exactly what you're signing up for.
Who is this for
Prerequisites
- No previous AI agent experience required
- Comfort using web apps and visual builders
- Access to sample documents or FAQs for labs
Technologies & tools
Skills you'll gain
A 8 weeks arc, module by module.
- Module 01
Module 01 — Foundations: Agent builder concepts, flows, and use cases
- Module 02
Module 02 — Core: Conversation design, intents, and fallback handling
- Module 03
Module 03 — Core: Knowledge bases, documents, and grounded answers
- Module 04
Module 04 — Engineering: Integrations with forms, sheets, and CRMs
- Module 05
Module 05 — Engineering: Deployment to web, chat, and workspace channels
- Module 06
Module 06 — Advanced: Analytics, log review, and iteration cycles
- Module 07
Module 07 — Production: Privacy, access control, and handoff design
- Module 08
Module 08 — Capstone: Launch a deployed agent for a selected support workflow
Practical Training Flow
Learning → Guided Labs → Independent Practice → Industry Project → Capstone → Portfolio → Career Preparation. Practical hours are tracked alongside instructional hours and surfaced on the certificate.
Delivery as HIGAET Practical Training / Experiential Learning.
What you'll be able to do.
- Build assistants with visual agent builders and conversational flows
- Design intents, entities, fallback paths, and escalation rules
- Develop knowledge-backed answers from documents and FAQs
- Integrate spreadsheets, CRMs, forms, and messaging channels
- Deploy agents to web widgets and team workspaces
- Evaluate conversation logs and improve failed turns
- Secure access controls, data retention, and PII handling
- Automate follow-ups, ticket creation, and notification workflows
You will build.
Every project ships as HIGAET Practical Training / Experiential Learning — portfolio-ready work, not exercises.
- Project 01
FAQ knowledge-backed assistant
- Project 02
Intent and escalation flow bot
- Project 03
Integrated workflow assistant
- Capstone
Deployed no-code assistant for a real workflow
Speak the language first.
- Visual agent builders
- No-code canvas tools for assembling assistants from blocks for messages, logic, and integrations.
- Conversational flows
- Designed paths of prompts and replies that guide a user toward a completed task.
- Intents
- The user goals, such as booking or asking a question, that an assistant is trained to recognize.
- Entities
- Key details pulled from a message, such as dates or order numbers, that the flow needs to act on.
- Fallback paths
- Backup replies and routes used when the assistant does not understand a request.
- Escalation rules
- Conditions that hand a conversation to a human reviewer when the agent cannot resolve it.
- Knowledge bases
- Curated collections of documents and FAQs the assistant searches to answer questions.
- Workflow integrations
- Connections to email, calendars, or spreadsheets so the assistant can read and update real systems.
- Deployed assistants
- Published agents embedded in a website or channel so real users can interact with them.
Fix, check, and go deeper.
Troubleshooting & common mistakes
Assistant misunderstands common requests
Add more example phrases per intent, check for overlapping intents, and split confused intents into separate ones.
Knowledge answers cite outdated documents
Review the knowledge base for stale files, update or remove them, and re-test the affected questions.
Fallback triggers too often
Inspect fallback logs for patterns, add missing intents or synonyms, and widen entity values for those cases.
Escalation never fires on difficult cases
Lower the confidence threshold for handoff, test with edge-case messages, and confirm the escalation channel is connected.
Integration step fails after deployment
Re-check connection credentials and field mappings in the live environment, then run a test record through the flow.
Before you move on, you should be able to
- Build assistants with visual builders and conversational flows
- Design intents, entities, fallback paths, and escalation rules
- Develop knowledge-backed answers from documents and FAQs
- Evaluate assistant accuracy on real workflow conversations
- Deploy an assistant for a real operational workflow
- Explain how flows, knowledge, and integrations work together
- Build integrations that connect assistants to business tools
Start your application.
Share a few details and a HIGAET advisor will reach out within one business day with next steps.
Common questions
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View CourseReady to start HIGAET AI Agent Builder?
A 8 weeks course — AI & Generative Intelligence.