Prompt Engineering
Description
A comprehensive proficiency pathway designed to develop expertise in prompt engineering for Large Language Models (LLMs). This pathway covers foundational AI concepts through advanced prompting techniques, enabling professionals to effectively communicate with generative AI systems, optimize outputs, and build production-ready applications.
Learning Objectives
Upon completion of this proficiency pathway, learners will be able to design, evaluate, and iterate sophisticated prompts for Large Language Models across diverse applications. Learners will develop mastery in foundational AI concepts including neural networks and NLP, understand the architecture and behavior of modern LLMs, craft prompts using multiple proven techniques, optimize model behavior through parameter tuning, integrate external knowledge sources, and apply prompt engineering to specialized domains while maintaining ethical and security standards.
Courses in this Bundle (12)
Cognitive and Soft Skills Development
This subject develops essential non-technical competencies that distinguish exceptional prompt engineers from competent technicians. It cultivates cri...
Core Prompt Engineering Concepts and Principles
Foundational understanding of prompt engineering as an emerging skill and discipline. This subject establishes the conceptual framework for effective ...
Evaluation and Quality Assessment
This subject teaches systematic methods for evaluating prompt and model quality. Learners will use qualitative and quantitative metrics, design evalua...
Security, Ethics, and Adversarial Resilience
This subject equips learners to recognize, prevent, and respond to security and ethical risks in prompt engineering. It addresses adversarial prompts,...
Multimodal Prompt Engineering
This subject covers prompt engineering for multimodal models that process and generate combinations of text, images, and other media. Learners will le...
Basic Prompting Techniques
Practical mastery of fundamental prompting techniques that form the foundation of prompt engineering practice. This subject covers core methods for co...
Foundations of Artificial Intelligence and Language Models
Comprehensive study of foundational concepts in Artificial Intelligence, Machine Learning, and Natural Language Processing that underpin Large Languag...
Understanding and Tuning LLM Behavior
Deep knowledge of how Large Language Models operate internally and how to configure them for optimal performance. This subject covers model selection,...
Retrieval Augmented Generation (RAG) and Knowledge Integration
This subject develops the skills required to design, implement, and prompt Retrieval Augmented Generation (RAG) systems that combine LLMs with externa...
Prompt Engineering for Specialized Domains
This subject focuses on applying prompt engineering practices in high-value professional domains including healthcare, finance, law, marketing, softwa...
Advanced Prompting Methodologies
Sophisticated prompting strategies designed to enhance model reasoning, enable complex problem-solving, and scaffold multi-step tasks. This subject co...
Practical Implementation and Production Systems
This subject develops the operational and architectural competencies required to deploy prompt-based systems in production environments. Learners will...