ChatGPT: Master Free AI Tools to Supercharge Productivity Specialization Course Syllabus

Overview (80-120 words) describing structure and time commitment.

Module 1: Introduction to Prompt Engineering

Estimated time: 6 hours

• Understanding the basics of ChatGPT and large language models
• Core principles of effective prompting
• Common prompt patterns and best practices
• Writing clear, specific, and actionable prompts

Module 2: Crafting Effective Prompts for Real-World Tasks

Estimated time: 6 hours

• Designing prompts for planning and project management
• Creating prompts for writing and content generation
• Using prompts for data analysis and interpretation
• Refining prompts through iteration and feedback

Module 3: Advanced Prompt Techniques

Estimated time: 8 hours

• Applying in-context learning to guide AI responses
• Implementing Retrieval-Augmented Generation (RAG) techniques
• Mastery of template patterns for consistent outputs
• Formatting responses with precision using constraints and structures

Module 4: Custom GPT Development

Estimated time: 7 hours

• Designing custom AI assistants for specific use cases
• Ingesting domain-specific documents for enhanced knowledge
• Building conversational flows and compliance rules
• Testing and refining custom GPTs for reliability and tone

Module 5: Multimodal Prompt Integration

Estimated time: 4 hours

• Integrating text, image, and file inputs into prompts
• Using multimodal inputs for diverse workflows
• Optimizing AI interactions across formats

Module 6: Final Project

Estimated time: 5 hours

• Design and build a custom GPT assistant for a real-world productivity scenario
• Incorporate document ingestion and retrieval-augmented capabilities
• Present a functional prototype with documented prompt engineering process

Prerequisites

• Basic familiarity with AI and natural language processing concepts
• Access to OpenAI's ChatGPT platform (free or paid version)
• Experience with digital workflows in professional or academic settings

What You'll Be Able to Do After

• Engineer precise and effective prompts for diverse applications
• Apply advanced techniques like in-context learning and RAG
• Build and deploy custom GPT assistants for specialized tasks
• Integrate multimodal inputs into AI-driven workflows
• Enhance productivity across writing, analysis, and decision-making