Blogs and Tutorials from External Sources

A beginner-friendly guide from Google designed for elementary and middle school students (Grades 2-8), covering AI basics, digital citizenship, and responsible use through scripted lessons, vocabulary, discussions, and interactive activities to build critical thinking skills.

Google Research’s AI Quests program offers engaging, hands-on challenges and explorations in AI, aimed at students and educators to deepen understanding of AI applications, ethics, and real-world impacts through quest-based learning experiences.

Stanford’s CRAFT resources provide a collection of adaptable lessons integrating AI into subjects like science, arts, history, and math, for middle and high school students, emphasizing ethics, biases, and societal implications with activities like games and debates.

AWS’s comprehensive guide on the responsible use of AI throughout its lifecycle, targeting developers, deployers, and users with best practices on fairness, transparency, privacy, and governance to promote ethical AI literacy and risk mitigation.

Coursera’s directory of AI courses from providers like IBM, Google Cloud, and DeepLearning.AI, suitable for beginners to advanced learners, covering machine learning, generative AI, ethics, and practical skills with hands-on projects and certifications.

A detailed resource on prompt engineering, covering techniques to develop and optimize prompts for language models (LLMs) in applications like question answering and reasoning, with sections on latest papers, advanced methods, model-specific guides, lectures, and tools to enhance AI literacy and effective LLM interaction.

Explores context engineering as an advanced approach beyond prompt engineering, focusing on managing tokens in LLMs for agentic systems, including strategies like system prompts, tool design, few-shot examples, just-in-time retrieval, compaction, structured note-taking, and sub-agent architectures to build steerable and performant AI agents.

Anthropic’s GitHub repository for an interactive tutorial on prompt engineering, designed to guide users through hands-on exercises and concepts for optimizing prompts with models like Claude, though detailed content access may require direct exploration.

OpenAI Academy’s collection of ready-to-use prompts for faculty using ChatGPT Edu, including examples for creating dynamic case studies, research proposals, cross-disciplinary frameworks, debate moderation, feedback analysis, personalized learning paths, crisis simulations, and data visualizations to support teaching and research.

A Vimeo video providing an introductory overview of prompt engineering concepts and techniques for interacting with AI models, suitable for beginners building foundational skills in AI literacy.

A Vimeo video delving into advanced techniques in prompt engineering, building on basic concepts to optimize interactions with AI systems, though detailed transcript or key points may require viewing for full insights.

OpenAI Academy’s collection of ready-to-use prompts tailored for higher education students using ChatGPT Edu, covering areas like adaptive study plans, peer review feedback, research assistance, real-world scenario practice, career pathway exploration, and collaborative project management to enhance learning, assignments, and professional development through effective prompt engineering.

An Anthropic engineering guide outlining practical patterns for constructing AI agents using large language models, distinguishing between workflows and agents, with emphasis on simplicity, tool design, and applications like customer support and coding, ideal for learning AI system design.

A GitHub repository hosting a book dedicated to learning the foundational concepts of large language models (LLMs), providing educational resources for understanding LLM basics and development.

A Google Developers blog post on designing efficient, production-grade multi-agent systems with tiered context management, compaction techniques, and scalability for long-horizon AI tasks.

Andrej Karpathy’s one-hour YouTube talk introducing LLMs as neural networks for next-word prediction, covering training processes, future directions, multimodality, and security challenges, suitable for AI beginners.

An in-depth YouTube video exploring LLM training pipelines, from pretraining on internet data to reinforcement learning, with insights on hallucinations, tool use, and model limitations.

Official GitHub code repository for the O’Reilly book “Hands-On Large Language Models,” offering practical code examples and resources for building and applying LLMs.

Microsoft’s GitHub repository featuring a 12-lesson course for beginners on building AI agents, including tutorials, code samples, videos, and topics like tool use, RAG, and deployment using Azure AI.

A GitHub repository teaching agentic AI through the Dapr Agentic Cloud Ascent (DACA) design pattern, covering OpenAI Agents SDK, memory, knowledge graphs, and cloud technologies like Kubernetes.

A GitHub hub providing in-depth tutorials on large language models (LLMs), retrieval-augmented generation (RAG), and real-world AI agent applications for practical AI engineering.