AI Marketing Brand Growth Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview (80-120 words) describing structure and time commitment.
Module 1: Foundations of Computing & Algorithms
Estimated time: 2-3 hours
- Review of tools and frameworks commonly used in practice
- Introduction to core AI concepts including neural networks and deep learning
- Implement prompt engineering techniques for large language models
- Case study analysis with real-world examples
Module 2: Neural Networks & Deep Learning
Estimated time: 2 hours
- Understand core AI concepts including neural networks and deep learning
- Hands-on exercises applying neural networks & deep learning techniques
- Review of tools and frameworks commonly used in practice
- Assessment: Quiz and peer-reviewed assignment
Module 3: AI System Design & Architecture
Estimated time: 3-4 hours
- Design algorithms that scale efficiently with increasing data
- Implement intelligent systems using modern frameworks and libraries
- Review of tools and frameworks commonly used in practice
- Interactive lab: Building practical solutions
Module 4: Natural Language Processing
Estimated time: 4 hours
- Understand transformer architectures and attention mechanisms
- Introduction to key concepts in natural language processing
- Implement prompt engineering techniques for large language models
- Discussion of best practices and industry standards
Module 5: Computer Vision & Pattern Recognition
Estimated time: 3 hours
- Explore applications of computer vision in marketing contexts
- Review of tools and frameworks commonly used in practice
- Interactive lab: Building practical solutions
- Guided project work with instructor feedback
Module 6: Deployment & Production Systems
Estimated time: 1-2 hours
- Introduction to key concepts in deployment & production systems
- Case study analysis with real-world examples
- Guided project work with instructor feedback
Prerequisites
- Familiarity with basic marketing concepts
- Basic understanding of data and analytics
- Interest in AI applications for brand growth
What You'll Be Able to Do After
- Evaluate model performance using appropriate metrics and benchmarks
- Leverage AI-driven insights to enhance brand positioning and campaign personalization
- Apply prompt engineering techniques to optimize content generation
- Design scalable AI systems for marketing automation and customer engagement
- Analyze real-world case studies to inform strategic brand growth decisions