• Overview of artificial intelligence and machine learning
• Introduction to prompt engineering
• Importance of prompt engineering in AI applications
• Basic concepts and terminology
Understanding AI Models and Language Models
• Types of AI models (supervised, unsupervised, reinforcement learning)
• Introduction to language models (GPT, BERT, T5, etc.)
• How language models work
• Use cases of language models
Basics of Prompt Engineering
• What is a prompt?
• How to write effective prompts
• Principles of prompt design
• Evaluating prompt performance
Advanced Prompt Engineering Techniques
• Fine-tuning and training models with custom prompts
• Contextual prompts and dynamic prompting
• Handling ambiguity and edge cases
• Prompt optimization techniques
Practical Applications of Prompt Engineering
• Text generation and summarization
• Conversational AI and chatbots
• Sentiment analysis and text classification
• Creative writing and content creation
Tools and Frameworks for Prompt Engineering
• Overview of popular AI tools and platforms (OpenAI, Hugging Face, etc.)
• Using APIs for prompt engineering
• Introduction to coding for prompt engineering (Python, PyTorch, TensorFlow)
• Building and deploying AI applications
Ethical Considerations in AI and Prompt Engineering
• Ethical issues in AI (bias, fairness, transparency)
• Responsible AI practices
• Ensuring ethical prompt design
• Case studies and best practices
Final Project and Presentation
• Planning and executing a prompt engineering project
• Applying learned concepts to real-world scenarios
• Presentation of final projects
• Feedback and assessment
