Agentic AI Content For Practitioners Teams Marketing Course Syllabus

Overview: This intermediate-level course on Agentic AI Content for Practitioners, Teams & Marketing provides a practical understanding of how to leverage AI agents for content creation, marketing automation, and scalable business workflows. Designed for professionals in marketing and AI-driven roles, the course blends foundational AI concepts with real-world applications. Through case studies, hands-on labs, and guided projects, learners will gain skills in prompt engineering, AI system design, and deployment. Estimated time commitment is approximately 18–24 hours across six modules, making it ideal for working professionals seeking to integrate AI into marketing strategies and content operations.

Module 1: Foundations of Computing & Algorithms

Estimated time: 2 hours

• Case study analysis with real-world examples
• Review of tools and frameworks commonly used in practice
• Introduction to algorithmic thinking for AI workflows
• Assessment: Quiz and peer-reviewed assignment

Module 2: Neural Networks & Deep Learning

Estimated time: 4 hours

• Introduction to key concepts in neural networks & deep learning
• Hands-on exercises applying neural networks & deep learning techniques
• Understanding core AI concepts including neural networks and deep learning
• Guided project work with instructor feedback
• Case study analysis with real-world examples

Module 3: AI System Design & Architecture

Estimated time: 3 hours

• Introduction to key concepts in AI system design & architecture
• Discussion of best practices and industry standards
• Design algorithms that scale efficiently with increasing data
• Assessment: Quiz and peer-reviewed assignment

Module 4: Natural Language Processing

Estimated time: 4 hours

• Introduction to key concepts in natural language processing
• Implement prompt engineering techniques for large language models
• Review of tools and frameworks commonly used in practice
• Interactive lab: Building practical solutions
• Understand transformer architectures and attention mechanisms

Module 5: Computer Vision & Pattern Recognition

Estimated time: 3 hours

• Introduction to key concepts in computer vision & pattern recognition
• Discussion of best practices and industry standards
• Review of tools and frameworks commonly used in practice
• Assessment: Quiz and peer-reviewed assignment

Module 6: Deployment & Production Systems

Estimated time: 2 hours

• Introduction to key concepts in deployment & production systems
• Review of tools and frameworks commonly used in practice
• Interactive lab: Building practical solutions
• Assessment: Quiz and peer-reviewed assignment

Prerequisites

• Familiarity with basic marketing principles
• Working knowledge of digital content creation tools
• Basic understanding of AI concepts preferred but not required

What You'll Be Able to Do After

• Design scalable AI-driven content workflows using agentic systems
• Apply prompt engineering techniques to optimize large language model outputs
• Build and deploy AI-powered applications for real-world marketing use cases
• Evaluate model performance using appropriate metrics and benchmarks
• Integrate AI agents into marketing strategies for automation and personalization