Students learn how Generative AI can be applied to real-world business functions.

What You'll Learn

• AI for marketing

• AI for sales

• AI for customer support

• AI for HR

• AI for recruitment

• AI for finance workflows

• AI for operations

• AI for research

• AI for business analysis

• AI-powered reporting

• AI document processing

• AI meeting management

• AI knowledge management

• AI-assisted decision making

Students learn how to connect AI tools with everyday business applications without requiring extensive programming knowledge.

What You'll Learn

• Introduction to workflow automation

• No-code vs low-code automation

• Automation triggers

• Actions and conditions

• Workflow logic

• Data mapping

• Connecting applications

• Webhooks fundamentals

• AI-powered workflows

• Automated content generation

• Automated email workflows

• Automated lead processing

• Automated notifications

• Error handling

• Workflow testing

Tools Introduced

• Make

• Zapier

• n8n

• Google Workspace

• Airtable

• Notion

Students learn the fundamentals of APIs and how AI applications communicate with external systems.

What You'll Learn

• Introduction to APIs

• REST APIs

• HTTP methods

• GET, POST, PUT and DELETE

• API requests and responses

• JSON fundamentals

• API authentication

• API keys

• Webhooks

• Connecting AI models with applications

• Using AI APIs

• API testing

• API integration workflows

• Error handling

• Rate limits and usage considerations

Students learn how AI can process documents, extract information, summarize data, and automate repetitive knowledge-based tasks.

What You'll Learn

• AI document processing

• PDF analysis

• Data extraction

• Document summarization

• Information classification

• Structured data extraction

• AI-assisted spreadsheet workflows

• AI-powered data analysis

• Email data processing

• Automated report generation

• Knowledge management

• Document workflows

• Human-in-the-loop workflows

• Data privacy considerations

Students develop practical AI automation solutions.

Projects

• AI Lead Management Automation

• AI Customer Support Workflow

• AI Resume Screening Workflow

• AI Content Repurposing System

• AI Document Processing Workflow

• Automated Business Reporting System

Students learn how AI applications can use external knowledge sources to generate more relevant and context-aware responses.

What You'll Learn

• Introduction to RAG

• Limitations of standard LLMs

• Knowledge bases

• Document ingestion

• Text chunking

• Embeddings

• Vector databases

• Semantic search

• Retrieval

• Context injection

• RAG architecture

• Building knowledge-based AI assistants

• RAG evaluation

• Introduction to vector databases

Students learn how to combine AI models, APIs, automation platforms, and user interfaces to create practical AI applications.

What You'll Learn

• AI application architecture

• AI APIs

• Model selection

• API integration

• User input processing

• AI response handling

• Structured outputs

• Application workflows

• AI-powered chatbots

• AI assistants

• Document Q&A systems

• AI content applications

• AI business applications

• Application testing

• Deployment fundamentals

Students learn how to identify repetitive business processes and transform them into intelligent automated workflows.

What You'll Learn

• Business process analysis

• Identifying automation opportunities

• Workflow mapping

• AI-powered decision workflows

• Intelligent document processing

• Automated customer support

• Automated lead qualification

• Automated CRM workflows

• AI-powered reporting

• Automated email management

• Automated content workflows

• Multi-application workflows

• Human approval workflows

• Error handling and recovery

• Automation monitoring

• Workflow optimization

Students are introduced to programming concepts that allow them to build more flexible AI automation solutions.

What You'll Learn

• Python fundamentals for AI automation

• Variables and data types

• Functions

• Conditional logic

• Loops

• Working with APIs using Python

• JSON processing

• API authentication

• Web requests

• Data processing

• Connecting Python with AI APIs

• Building simple AI automation scripts

• Automating repetitive tasks

• Integrating Python with workflow platforms

• Error handling

• Basic application deployment

Students complete an end-to-end AI automation project combining Generative AI, automation, APIs, agents, and business workflows.

Capstone Project Process

Business Problem → Process Analysis → Automation Strategy → AI Model Selection → Prompt Design → API Integration → Workflow Automation → AI Agent / RAG Integration → Testing → Monitoring → Deployment → Documentation

Capstone Project Options

Students can develop projects such as:

• AI Customer Support Automation

• AI Lead Qualification & CRM Automation

• AI Recruitment Assistant

• AI Marketing Automation System

• AI Document Processing System

• AI Knowledge Base Assistant

• AI Sales Assistant

• AI Business Reporting Automation

• AI Content Automation System

• AI Research Assistant