AI Marketing Automation Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This course provides a practical introduction to AI marketing automation, designed for intermediate learners. You'll explore core AI concepts and their application in automating marketing workflows without requiring coding experience. The curriculum spans approximately 15-20 hours, combining theory, hands-on exercises, and real-world case studies to build proficiency in leveraging AI tools for marketing efficiency and campaign optimization.
Module 1: Foundations of Computing & Algorithms
Estimated time: 3 hours
- Introduction to key concepts in foundations of computing & algorithms
- Discussion of best practices and industry standards
- Case study analysis with real-world examples
- Guided project work with instructor feedback
Module 2: Neural Networks & Deep Learning
Estimated time: 2 hours
- Introduction to key concepts in neural networks & deep learning
- Hands-on exercises applying neural networks & deep learning techniques
- Assessment: Quiz and peer-reviewed assignment
Module 3: AI System Design & Architecture
Estimated time: 4 hours
- Introduction to key concepts in AI system design & architecture
- Discussion of best practices and industry standards
- Interactive lab: Building practical solutions
- Guided project work with instructor feedback
Module 4: Natural Language Processing
Estimated time: 2 hours
- Introduction to key concepts in natural language processing
- Interactive lab: Building practical solutions
- Discussion of best practices and industry standards
- Assessment: Quiz and peer-reviewed assignment
Module 5: Computer Vision & Pattern Recognition
Estimated time: 3 hours
- Hands-on exercises applying computer vision & pattern recognition techniques
- Guided project work with instructor feedback
- Assessment: Quiz and peer-reviewed assignment
Module 6: Deployment & Production Systems
Estimated time: 4 hours
- Discussion of best practices and industry standards
- Guided project work with instructor feedback
- Hands-on exercises applying deployment & production systems techniques
- Interactive lab: Building practical solutions
Prerequisites
- Familiarity with basic digital marketing concepts
- Basic computer literacy
- No coding experience required
What You'll Be Able to Do After
- Understand core AI concepts including neural networks and deep learning
- Apply computational thinking to solve marketing automation challenges
- Build and deploy AI-powered marketing applications using modern tools
- Implement intelligent systems for workflow optimization and customer engagement
- Use prompt engineering and NLP techniques to enhance marketing content and personalization