Introduction to Large Language Models (LLMs) and their architecture. 5.33

Key concepts: Tokenization, context windows, and model parameters. 7.25

Understanding LLM "personalities" and interpretation. 4.83

Basic conversational flow: Establishing and maintaining context. 6.17

Comparing leading LLMs and choosing the right model. 8.50

Developing a confident AI vocabulary. 5.67

Anatomy of a powerful prompt: Components and best practices. 6.00

Iterative prompting: The "back-and-forth" method. 7.50

Techniques for clarity: Specificity and avoiding ambiguity. 5.75

Using negative constraints for precise output. 4.33

Setting up your Laravel environment for AI interaction. 8.25

Making basic AI API calls from Laravel. 7.00

Zero-shot prompting: Unleashing inherent LLM knowledge. 5.17

Few-shot prompting: Guiding with examples. 7.67

Role-playing techniques for specific AI personas. 6.33

Constraint-based prompting for enforced output rules. 5.83

Case studies of strategic prompting in action. 7.00

Building a Laravel web service for few-shot categorization. 9.50

Chain-of-Thought (CoT) prompting for step-by-step reasoning. 7.17

Tree-of-Thought (ToT) for exploring multiple reasoning paths. 6.75

Recursive prompting for refining results. 8.00

Leveraging external tools and APIs with AI. 9.25

Implementing conditional logic in AI workflows. 5.50

Building multi-step AI assistants in Laravel. 10.00

Using AI for deep analysis and information extraction. 7.33

Document summarization techniques: Abstractive vs. Extractive. 8.67

Sentiment analysis and entity recognition with LLMs. 6.17

Integrating with Google Cloud Natural Language API. 9.00

Prompting for data transformation and reformatting. 5.92

Developing Laravel applications for textual data analysis. 11.00

Introduction to multi-modal AI capabilities. 6.50

Leveraging Google Cloud Vision AI for image analysis. 8.83

Prompting for image generation and manipulation. 7.25

Processing and analyzing various file types with AI. 9.33

Integrating multi-modal AI into Laravel applications. 10.75

AI for scenario exploration and contingency planning. 7.00

Role-playing complex interactions with AI. 8.50

Leveraging AI for brainstorming and innovation. 6.67

Prompting for "what-if" analysis and risk assessment. 7.83

Building interactive AI tools in Laravel for strategic planning. 11.25

Best practices for AI API integration in Laravel. 8.17

Managing API keys and secure credentials. 6.00

Implementing robust error handling and retry mechanisms. 7.75

Performance optimization: Caching and asynchronous processing (Laravel Queues). 9.50

Cost management for AI services. 5.33

Introduction to Google Cloud API Gateway. 8.00

Developing a production-ready Laravel AI API endpoint. 12.00

Data privacy and AI: Leakage and prompt injection vulnerabilities. 7.50

Best practices for securing AI interactions: Input/output validation. 6.75

Google Cloud security features for AI (IAM, VPC, DLP). 9.00

Ethical AI principles: Bias detection, fairness, transparency. 8.17

Responsible AI development and user trust. 5.83

Legal and compliance considerations for AI. 6.33

Securing your Laravel AI applications. 10.25

Capstone Project Kick-off: Scope, architecture, and user stories. 8.00

Guided development of your AI-powered Laravel application. 15.00

Deployment strategies on Google Cloud (Cloud Run, App Engine). 12.50

Setting up CI/CD pipelines on Google Cloud. 9.75

Monitoring and logging AI applications with Google Cloud Operations. 7.33

Scaling AI solutions: Auto-scaling and resource management. 8.83

Presentation of Capstone Projects and peer feedback. 20.00