This course aims to provide industry leaders with an over-arching introduction to AI and introduces key technical concepts, AI safety and ethics, and best business and management practices for AI specific projects.
This course covers foundations and applications of data science approaches to predictive modeling in medicine.
This course provides executive government leaders with the tools to harness artificial intelligence (AI) for the benefit of their organizations using a holistic perspective on AI technology integration.
The Johns Hopkins Healthcare Systems Engineering and Thinking course provides participants with a deep understanding of today's ongoing healthcare challenges and the tools and strategies they need to develop high-impact, long-lasting systems-based solutions.
This program provides a strategic understanding of AI and ML technologies, data and resource optimization, responsible AI practices, generative AI and effective AI project management. It will equip learners with a framework to drive AI innovation and manage large-scale AI projects effectively.
This Applied Generative AI program focuses on building and deploying generative AI solutions. Learners will gain hands-on experience in Python, prompt engineering, content generation, and sentiment analysis. Key topics include AI agents with LangChain, Retrieval Augmented Generation (RAG), and fine-tuning large language models. By the end, participants will be able to create AI-driven solutions for various applications while ensuring ethical and responsible AI practices.
This course provides senior leaders with a comprehensive approach to adopting AI technology. It provides a framework to unpack the question, “How do we turn our organization’s AI strategy into action?”
This workshop introduces state-of-the-art methods for developing testing and evaluation plans for AI-driven systems and addresses novel challenges these systems present.
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