Wiley
Practical Prompt Engineering and Integration
This unit moves beyond foundational prompt concepts to practical application: students learn to design, evaluate, and integrate prompts and AI […]
FreeFoundations of AI Prompting and Tools
This unit establishes foundational knowledge of AI types, text-generation techniques, prompt design, and common multimodal tools (text, image, audio) while […]
FreeDeploying Generative AI Apps
This capstone unit guides students through prototyping, securing, and deploying a generative AI web application using Amazon Bedrock and related […]
FreeMultimodal Generation and Guardrails
This unit teaches hands-on techniques for generating and controlling multimodal outputs with Amazon Bedrock, including image creation with Stable Diffusion […]
FreeBedrock Foundations and AWS Integration
This unit guides students through configuring the AWS CLI and preparing a development environment to use Amazon Bedrock, covering both […]
FreeFoundations of Generative AI with Bedrock
This unit introduces the current generative AI landscape, prompt engineering best practices, an overview of the Amazon Bedrock API and […]
FreeAdvanced Prompt Applications and Futures
This capstone unit surveys practical examples across multiple generative AI systems (image, audio, and latent models), examines ethical and accessibility […]
FreeGenerative Models and Prompting
This unit explores a range of generative AI systems (audio, image, code, and face-swap) and how prompt design influences their […]
FreeGenerative AI Models and Prompting
This unit surveys major generative AI models (text, image, audio, and music) and examines how prompts shape their behavior, outputs, […]
FreeFoundations of Prompt Engineering
This unit introduces core concepts of AI, machine learning, and prompt engineering and provides hands-on practice crafting, testing, and refining […]
FreeModel Optimization, Deployment, and Scaling
This unit covers advanced TensorFlow techniques for improving model training, managing experiments, and preparing models for production deployment. Students will […]
FreeModel Building and Training
This unit guides students through constructing, training, evaluating, and tuning TensorFlow models for classification tasks. It covers tensor transformations, input […]
FreeBuilding and Executing TensorFlow Models
This unit teaches students how to assemble, train, test, and run TensorFlow models in both local and cloud/cluster environments. Learners […]
FreeFoundations of TensorFlow and ML
This unit introduces core machine learning principles and the TensorFlow ecosystem, including installation, basic APIs, and fundamental data constructs. Students […]
FreeStrategic Implementation and Governance
This capstone unit synthesizes technical, business, ethical, and environmental considerations of AI-driven spatial computing, emphasizing risk management, stakeholder impacts, and […]
FreeAI Integration for Spatial Experiences
This unit explores how AI (including ML/DL, CV, and GenAI) is integrated into spatial computing to create immersive, measurable, and […]
FreeApplied Spatial Computing and AI
This unit examines how AI and spatial computing transition from research and science fiction into business-ready solutions. Students explore technology […]
FreeFoundations of Spatial Computing
This unit introduces the evolution, core concepts, and contemporary business significance of spatial computing driven by AI, including historical milestones […]
FreeSecuring LLMs in Azure Cloud
This unit covers securing Large Language Model (LLM) applications in Microsoft Azure, including Azure AI Search, the LLM application security […]
FreeSecure Azure LLM Infrastructure
This unit explores how to design, deploy, and secure a three-tier LLM application in Azure using retrieval-augmented generation (RAG) and […]
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