Practical AI for Business Training in Bangkok, Thailand

This course is designed for business professionals, analysts, and decision-makers who want to understand and implement Artificial Intelligence (AI) solutions to drive business value. The training emphasizes real-world applications of AI, covering how to identify opportunities, build basic models, integrate AI tools into workflows, and evaluate outcomes for continuous improvement.

Foundations and No-Code AI Implementation

Module 1: Understanding AI in the Business Context

• Introduction to AI Concepts
• What is AI, Machine Learning, Deep Learning, and NLP
• Key differences and business relevance
• Business Drivers for AI Adoption
• Efficiency, personalization, automation, and data insights
• Identifying value creation opportunities
• AI Use Cases Across Functions
• Marketing: personalization, customer segmentation
• HR: resume screening, sentiment analysis
• Finance: fraud detection, forecasting
• Operations: predictive maintenance, optimization
• Ethics, Risks, and AI Governance
• Responsible AI, bias, transparency, and compliance
• Governance frameworks and practical safeguards

Module 2: Exploring AI Tools

• Overview of AI Platforms and Tools
• ChatGPT, Azure AI, Google Vertex AI, Amazon Bedrock, and IBM Watson
• Criteria for choosing tools (cost, scalability, integration)
• Hands-on Demos

Module 3: No-Code / Low-Code AI Implementation

• Text-Based AI Applications
• Building solutions for classification, summarization, and translation
• Automating text tasks using AI APIs and no-code tools
• Practical Workshop
• Building an AI workflow with Microsoft Power Platform
• Example: Automating document tagging and sentiment analysis
• Tool Deep Dive
• KNIME and Alteryx for data preparation and AI pipeline creation
• Integrating workflows with existing business systems

AI Deployment, Integration, and Strategy

Module 4: Conversational AI and Document Automation

• Introduction to Conversational AI
• Designing intelligent chatbots and assistants
• Tools: Power Virtual Agents, Dialogflow, and ChatGPT APIs
• Document and Email Automation
• Automating document classification and extraction
• Email triage and routing using AI models
• Hands-on Exercise

Module 5: AI Deployment and Business Integration

• Deploying AI Models
• Using AI inside spreadsheets (Excel + Copilot), web apps, and CRMs
• Connecting AI models to databases and APIs
• AI and RPA Integration
• Combining AI with UiPath and Power Automate for end-to-end automation
• Case examples: invoice processing, customer support automation
• Evaluating AI Performance
• Setting KPIs and success metrics (accuracy, ROI, adoption)
• Interpreting model results for business decision-making

Module 6: Building an AI Roadmap

• Developing an AI Adoption Strategy
• Identifying high-impact use cases and quick wins
• From pilot to production: scaling AI across the organization
• Workshop: Create a Mini AI Pilot Project
• Define a use case, select tools, outline implementation steps
• Wrap-Up and Discussion
• Sharing pilot ideas and feedback
• Q&A and next steps