Justin Barnett

How to use ChatGPT and Generative AI to help create content

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In the rapidly evolving digital landscape, mastering Generative AI has transitioned from a futuristic skill to an absolute necessity for modern creators, marketers, and professionals. Led by instructor Justin Barnett, this comprehensive course, "How to use ChatGPT and Generative AI to help create content," demystifies the mechanics of state-of-the-art language and diffusion models. Students will explore an extensive suite of cutting-edge tools, including text-based systems like ChatGPT, Google Gemini, Microsoft Copilot, and Meta's Llama, alongside visual powerhouses such as Midjourney, Dall-E, and Adobe Firefly. Beyond basic commands, the curriculum dives deep into the strategic art of prompt engineering, instructing learners on how to prime models for highly specific outputs and construct custom GPTs using OpenAI's GPT Builder. You will also look under the hood to understand the foundations of Generative Adversarial Networks (GANs), Transformer architectures, and multimodal capabilities, ensuring you grasp the "why" behind the technology. Additionally, practical demonstrations show how to interface with the OpenAI API, fine-tune GPT-3.5 Turbo models, and utilize AI responsibly by examining ethical implications. Whether you are a copywriter aiming to accelerate your production, a developer seeking to integrate text-to-image workflows, or a business professional looking to future-proof your career, this course provides the actionable insights and hands-on demonstrations needed to turn artificial intelligence into your ultimate creative partner.

How to build AI Agents with Claude API in Python

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Unlock the power of Anthropic's state-of-the-art language models with this comprehensive developer's guide to building production-ready AI agents using Python. Designed for software engineers, data scientists, and AI enthusiasts, this course bridges the gap between theoretical artificial intelligence concepts and practical, hands-on implementation. Instructor Justin Barnett guides you step-by-step through the Claude 3 API landscape, detailing the specific differences, pricing structures, and rate limits across the model family to help you make cost-effective architectural decisions. You will master the fundamentals of Retrieval-Augmented Generation (RAG) by constructing a custom pipeline from scratch, leveraging vector databases to feed external knowledge directly to your LLM-powered applications. Beyond basic API interactions, you will dive deep into structural topics like the Model Context Protocol (MCP) and systematic evaluation frameworks. By learning how to write robust system prompts and establish metrics to run systematic evaluations, you will be equipped to iterate, debug, and confidently scale your AI applications from simple code scripts to resilient, autonomous agents capable of solving real-world business challenges.