Latest videos about Prompt Engineering
Claude Certified Developer Foundations (CCDV-F) Certification Course
- The course "Claude Certified Developer Foundations (CCD-ENF)" teaches developers to work with Claude, focusing on building production-ready cloud applications and agents. It covers APIs, SDKs, code, tool use, prompting, context management, testing, security, and optimization. - The certification exam is role-based, not tiered like traditional foundation/associate/professional levels. It consists of 53 multiple-choice questions, requires a 72% passing score, and has a 2-hour duration. The certification is valid for 12 months. - Key architectural concepts include agent architecture (dynamic policy, natural instructions) and workflow architecture (predetermined steps, state machines). The course emphasizes using these architectures together, with agents handling dynamic decisions and workflows managing structured automation. - The course delves into practical aspects of working with Claude, such as using the Agent SDK for programmatic interaction, implementing sub-agents for specialized tasks, managing context with commands like `compact` and `clear`, and understanding prompt versioning and caching. - Security and optimization are critical, covering topics like defensive parsing, PII handling, permission rules (tool-based access control), sandboxing for bash tools, and prompt caching to manage costs and performance. The importance of specific prompting and independent validation to counter overconfidence and hallucinations is also highlighted.
Claude Certified Architect - Foundations – Prepare for and pass the exam!
- The course focuses on the Claude Architect Foundations Certification from Anthropic, emphasizing hands-on labs for practical application of concepts. - The certification is primarily aimed at individuals building AI workflows, planning to adopt Claude as their main AI driver, or part of the Claude partner network. - The course covers five domains: agentic architecture and orchestration, tool design and MCP integration, Claude Code configuration and workflows, prompt engineering, structured output, context management, and reliability. - The instructor highlights the importance of using `stop_reason` for loop termination in agentic workflows, as natural language parsing, iteration caps, or text presence can be unreliable. - Key architectural patterns like Hub and Spoke for coordinator agents, dynamic selection, and refinement loops are explored, along with anti-patterns and best practices for managing context and handling errors.
AI Agents For Beginners – OpenClaw Case Study
- This course offers a beginner-friendly, hands-on approach to building real AI agents, moving from LLM fundamentals to multi-agent systems without complex setup. - Led by Mumshed, founder of CodeCloud, the course emphasizes practical skills, culminating in a case study of OpenClaw, a production-inspired AI agent. - Participants will build four specialized AI agents (Zippy, Savvy, Meshy, Cody) to understand orchestration, research, memory, and coding capabilities. - The curriculum covers core AI concepts like LLM architecture (transformers, pre-training, generation), tokenization, temperature, context windows, and effective prompting techniques. - The course provides hands-on lab environments with pre-configured API keys and cloud sandboxes, allowing learners to focus purely on building and deploying AI agents.