Wiley
Efficient Inference and Fine-Tuning
This unit teaches strategies for producing concise outputs, scaling inference efficiently, and adapting large language models with minimal compute and […]
FreeLLM Customization and Inference
This unit introduces methods to adapt large language models through full and parameter-efficient fine-tuning and examines the cost and performance […]
FreeGenerative AI Creative Production
This capstone unit synthesizes advanced prompting strategies, iterative workflows, and content-validation techniques to produce portfolio-ready creative assets using generative AI. […]
FreePractical Prompting and Production
This unit advances students from foundational GenAI concepts to applied creative production, focusing on advanced prompt engineering, model selection, multimodal […]
FreePrompting, Ethics, and Production
This unit builds on foundational GenAI concepts to teach advanced prompt engineering, model selection, and human-in-the-loop quality control for creative […]
FreeFoundations of Generative AI
This unit establishes foundational knowledge and practices for using generative AI in creative content workflows, including core concepts, prompting, model […]
FreeDeploying GenAI with RAG on AWS
This unit consolidates GenAI concepts into practical, cloud-based solutions by focusing on Retrieval-Augmented Generation (RAG) design, implementation on AWS, and […]
FreeAmazon Bedrock and GenAI Services
This unit explores AWS services for generative AI with a deep focus on Amazon Bedrock, model customization, prompt and flow […]
FreeGenerative AI Foundations on AWS
This unit covers technical foundations and practical development workflows for generative AI on AWS, including foundation models, LLMs, prompt engineering, […]
FreeFoundations of Generative AI
This unit surveys the historical foundations of computing and artificial intelligence and builds conceptual fluency in machine learning, deep learning, […]
FreeAI Model Monitoring and Platform Evaluation
This unit focuses on building and operating enterprise-grade model monitoring systems in the cloud, comparing AI/ML platform offerings (including Microsoft) […]
FreeOperationalizing Enterprise AI
This unit covers the operational aspects of enterprise AI: MLOps automation (CI/CD), model deployment, monitoring strategies (real-time vs. batch), feature […]
FreeOperationalizing Enterprise AI
This unit covers the practical steps to deploy, monitor, and scale AI solutions in the cloud, including MLOps practices, environment […]
FreeFoundations of Enterprise AI Adoption
This unit introduces core concepts, organizational challenges, and practical frameworks for adopting AI at enterprise scale. Students learn responsible AI […]
FreeApplied Deep Learning Integration and Deployment
This capstone unit integrates applied deep learning tools, frameworks, and hardware to solve real-world problems across vision, speech, forecasting, and […]
FreeApplied Deep Learning Implementation
This unit guides students through practical construction, optimization, and deployment of deep learning models using modern frameworks and tools. Students […]
FreeFoundations of Deep Learning
This unit builds practical and conceptual foundations for deep learning: environment setup, core tensor math, and the architectures and workflows […]
FreeFoundations of Deep Learning
This unit introduces core concepts, tools, and math needed to understand and begin building deep learning models. Students will learn […]
FreeAdvanced Prompting and Production
This unit deepens students’ ability to apply ChatGPT to complex, domain-specific media production tasks by teaching advanced prompting strategies, multi-persona […]
FreeAdvanced Prompting for Media Production
This unit expands foundational prompting skills into advanced strategies for digital content creation, covering parameter tuning, role/personality design, and converting […]
Free