Low-Code/No-Code AI Integration Platforms

Use visual tools to integrate GenAI without deep coding skills.

Pillar

Technology – Platforms, Tools, Infrastructure & Productivity

Overview

This course introduces low-code and no-code platforms that enable users to build and integrate Generative AI capabilities into business applications quickly and efficiently without extensive programming knowledge. Participants will explore popular platforms, learn to create AI workflows visually, and understand how to deploy AI-powered solutions that accelerate innovation and reduce time-to-market.

Learning Objectives

Participants will be able to:

• Understand the benefits and limitations of low-code/no-code AI platforms

• Identify suitable use cases for no-code GenAI integration

• Design and build AI workflows using drag-and-drop interfaces

• Connect AI models to business processes through visual tools

• Deploy and manage AI solutions with minimal coding

Target Audience

• Business analysts and citizen developers

• Digital transformation and innovation managers

• Product owners and solution architects

• IT professionals exploring rapid AI deployment

Duration

20 hours over 4 days (5 hours per day)

Delivery Format

• Interactive platform demonstrations

• Step-by-step workflow building exercises

• Use case discussions and group projects

• Q&A and troubleshooting sessions

Materials Provided

• Access to low-code/no-code AI integration platforms (trial versions)

• Stepwise guides and video tutorials

• Sample AI workflow templates

• Best practice checklists for no-code AI deployment

Outcomes

• Ability to design and deploy GenAI integrations without coding

• Enhanced collaboration between business and IT teams

• Faster AI solution delivery with reduced technical barriers

• Understanding of governance and control in no-code environments

Outline / Content

Day 1: Introduction to Low-Code/No-Code AI Platforms

• Overview of market-leading platforms

• Understanding GenAI capabilities in no-code environments

Day 2: Designing AI Workflows Visually

• Building AI-driven processes using drag-and-drop tools

• Connecting data sources and AI services

Day 3: Deployment and Management

• Testing and deploying AI workflows

• Monitoring performance and user feedback

Day 4: Use Cases, Governance, and Best Practices

• Real-world examples of no-code AI integrations

• Managing compliance and security in no-code platforms

• Future trends and continuous improvement