This course provides a comprehensive introduction to Generative AI and Prompt Engineering, equipping learners with the skills to craft effective prompts that enhance AI-generated responses. Designed for professionals seeking to optimize AI interactions, the course covers fundamental AI concepts, the evolution of language models like GPT, BERT, and T5, and hands-on techniques to improve AI output precision. Learners will explore Zero-shot, Few-shot, Chain-of-Thought (CoT), and Tree-of-Thought (ToT) reasoning, refining their ability to structure prompts for various applications, including content creation, automation, and coding. The course also delves into ethical AI considerations and evaluates AI performance using industry best practices.

Target Audience -Content Creators looking to generate high-quality AI-driven content. -Developers and Data Scientists aiming to optimize AI model interactions. -Marketers leveraging AI for SEO, ad copywriting, and automation. -Product Managers and AI Enthusiasts seeking to understand AI prompt optimization. -Anyone interested in AI-driven tools like ChatGPT, DeepSeek.ai, and IBM Watsonx. Learning Objectives By the end of this course, learners will be able to: -Understand Generative AI models and their impact on various industries. -Craft effective prompts that yield high-quality AI-generated responses. -Apply advanced prompting techniques such as Zero-shot, Few-shot, and CoT reasoning. -Optimize AI interactions for tasks like content generation, automation, and coding. -Evaluate AI performance using key metrics and mitigate ethical risks in AI prompting. Module 1: Fundamentals of Generative AI and Prompt Engineering This module introduces learners to the core concepts of Generative AI, including how AI models generate content and why prompt engineering is essential. Learners will explore key language models, their real-world applications, and foundational prompt engineering techniques. The module also covers common prompt design pitfalls and methods to refine AI-generated responses. Module 2: Advanced Prompt Engineering and Real-World Applications Building upon the fundamentals, this module focuses on advanced prompt engineering techniques to optimize AI responses for SEO, content creation, automation, and coding. Learners will refine prompt structures, experiment with specificity, and explore AI tools like IBM Watsonx and LangChain. The module concludes with discussions on AI ethics, bias mitigation, and future trends in prompt engineering.