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Course Outline
Introduction to LangGraph for Marketing Automation
- Overview of LangGraph concepts and nodes
- Graph-based orchestration for content workflows
- Examples in email automation
Designing Conditional Content Flows
- Branching logic in email campaigns
- Personalization strategies with dynamic content
- Decision trees for customer journeys
Integrating LLMs for Content Generation
- Prompt design and chaining for multi-step content generation
- Handling outputs and structured content
- Automating copy for newsletters, product updates, and campaigns
State Management and Context Handling
- Tracking recipient interactions and engagement
- Short-term vs. persistent memory in workflows
- Context passing between nodes for consistency
APIs and External Integrations
- Email platform integration (e.g., SMTP, SendGrid, HubSpot)
- CRM and marketing database connectivity
- Tool calling and external data fetching
Evaluation, Monitoring, and Optimization
- Measuring open rates, click-through, and engagement
- Debugging workflow paths and branching outcomes
- Iterative optimization of personalization strategies
Packaging and Deployment of Workflows
- Version control and workflow management
- Scheduling and automation triggers
- Operational best practices and hand-off to production teams
Summary and Next Steps
Requirements
- Basic programming knowledge in Python
- Experience with content automation or marketing workflows
- Familiarity with email automation platforms or APIs
Audience
- Marketers
- Content strategists
- Automation developers
14 Hours
