Overzicht
The Generative AI & Prompt Engineering course provides foundational knowledge of Generative AI concepts, prompt engineering techniques, foundation models, and AWS Generative AI services used to build intelligent AI-powered applications. Learners will explore core Generative AI concepts, business use cases, model lifecycles, and prompt engineering strategies for interacting effectively with large language models (LLMs).
The course also covers prompt design techniques, prompt optimization, parameter-efficient fine-tuning, P-tuning, and A/B testing approaches used to improve AI responses and model performance. In addition, learners will explore Amazon Q services and Amazon Bedrock, including foundation model selection, Guardrails, Knowledge Bases, RAG architectures, Agents, integrations, and Generative AI application development on AWS.
This course is structured into three modules with approximately 6–8 hours of video content and quizzes to reinforce learning. Course Modules:
Module 1:
Generative AI Foundations Module 2:
Prompt Engineering Module 3:
Amazon Q & Bedrock By the end of this course, learners will be able to:
Understand core Generative AI concepts, foundation models, and AI use cases Understand prompt engineering principles and effective prompt design techniques Explore fine-tuning, prompt learning, and model optimization approaches Understand Retrieval-Augmented Generation (RAG) architectures and vector embeddings Explore Amazon Q services for business and developer productivity Understand Amazon Bedrock, foundation models, Guardrails, Agents, and AI integrations Identify appropriate Generative AI services and architectures for different business and application requirements This course is ideal for learners preparing for Generative AI application development, AI-powered cloud solutions, prompt engineering roles, and foundational AWS AI certification learning.
Lesprogramma
- Generative AI Foundations
Welcome to the Generative AI Foundations module, you’ll focus on the foundational concepts of generative AI and how these models are used in real-world applications. We’ll begin with What is Generative AI Model? and Key Terms of Generative AI, helping you understand the core terminology and how these models generate content.Next, you’ll explore Potential Use Cases of Generative AI, along with the Challenges of Generative AI, giving you a balanced view of where these technologies add value and where limitations exist.As the week progresses, you’ll dive into the Components of Generative AI and the Lifecycle of Foundation Models, enabling you to understand how models are built, trained, and deployed.By the end of this week, you’ll have a strong understanding of generative AI fundamentals and be prepared to explore prompt engineering and advanced AI services in the upcoming modules.
- Prompt Engineering
Welcome to the Prompt Engineering module, you’ll focus on designing and optimizing prompts to effectively interact with generative AI models. We’ll begin with Prompt Engineering and a hands-on Prompt Engineering Demo, helping you understand how structured inputs influence model outputs.Next, you’ll explore the Fundamentals of Prompt Design and Techniques for Effective Prompts, along with a demo to apply these techniques in real scenarios and improve response quality.As the week progresses, you’ll dive into advanced methods such as Parameter Efficient Finetuning, Prompt Learning (P-tuning), and A/B Testing, enabling you to refine prompts and evaluate their performance systematically.By the end of this week, you’ll be equipped to design, test, and optimize prompts for better accuracy and efficiency in generative AI applications.
- Amazon Q & Bedrock
Welcome to the Amazon Q & Bedrock module, you’ll focus on AWS generative AI services and how to build and evaluate AI-powered applications. We’ll begin with Amazon Q, exploring What is Amazon Q Business, Amazon Q Apps, and Amazon Q Developer, helping you understand how AI assistants can enhance productivity and development workflows.Next, you’ll explore Types of Foundation Models and Business Metrics for Generative AI, enabling you to align model selection and performance with real-world business goals. As the week progresses, you’ll dive into Amazon Bedrock, starting with an overview and demo to understand how to access and use foundation models on AWS. You’ll also learn how to choose the right model, perform Finetuning, and evaluate models using appropriate Evaluation Metrics, supported by a hands-on Bedrock Evaluation Demo. By the end of this week, you’ll be equipped to select, customize, and evaluate foundation models using Amazon Q and Amazon Bedrock for building effective generative AI solutions.
Gegeven door
Whizlabs Instructor
Vakgebieden
Artificial Intelligence
