This credential earner demonstrates knowledge of artificial intelligence (AI) concepts, such as natural language processing, computer vision, machine learning, deep learning, chatbots, and neural networks; AI ethics; and the applications of AI. The individual has a conceptual understanding of how to run an AI model using IBM Watson Studio. The earner is aware of the job outlook in fields that use AI and is familiar with the skills required for success in various roles in the domain. Issued by IBM-SkillsBuild
	This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
	Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. Demonstrate your understanding of foundational concepts in generative AI.
	This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
	This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 7 AI principles.
	As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.