AI Marketing Chatgpt Gemini 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: 3 hours
- Review of tools and frameworks commonly used in practice
- Guided project work with instructor feedback
- Interactive lab: Building practical solutions
- Apply computational thinking to solve complex engineering problems
Module 2: Neural Networks & Deep Learning
Estimated time: 4 hours
- Interactive lab: Building practical solutions
- Case study analysis with real-world examples
- Discussion of best practices and industry standards
- Design algorithms that scale efficiently with increasing data
Module 3: AI System Design & Architecture
Estimated time: 3 hours
- Hands-on exercises applying AI system design & architecture techniques
- Case study analysis with real-world examples
- Discussion of best practices and industry standards
- Evaluate model performance using appropriate metrics and benchmarks
Module 4: Natural Language Processing
Estimated time: 2 hours
- Hands-on exercises applying natural language processing techniques
- Guided project work with instructor feedback
- Implement prompt engineering techniques for large language models
Module 5: Computer Vision & Pattern Recognition
Estimated time: 4 hours
- Hands-on exercises applying computer vision & pattern recognition techniques
- Guided project work with instructor feedback
- Review of tools and frameworks commonly used in practice
- Discussion of best practices and industry standards
Module 6: Deployment & Production Systems
Estimated time: 2 hours
- Introduction to key concepts in deployment & production systems
- Hands-on exercises applying deployment & production systems techniques
- Discussion of best practices and industry standards
Prerequisites
- Familiarity with basic marketing concepts
- No coding experience required
- Access to ChatGPT and Google Gemini platforms
What You'll Be Able to Do After
- Build and deploy AI-powered applications for real-world marketing use cases
- Implement intelligent systems using modern AI frameworks and libraries
- Apply prompt engineering techniques to optimize content generation with ChatGPT and Gemini
- Enhance productivity through automation of content creation and campaign management
- Design scalable AI solutions for digital marketing and customer engagement