According to DeepLearning.AI, a new course titled 'Getting Structured LLM Output' has been announced, developed in collaboration with @dottxtai and instructed by @willkurt and @cameron_pfiffer. This course focuses on teaching methods to convert freeform LLM outputs into structured data formats, which is crucial for software development applications. The emphasis is on building systems that can reliably read and utilize structured data, enhancing the efficiency of software solutions.

According to Andrew Ng, a new short course titled 'Long-Term Agentic Memory with LangGraph' has been launched. This course, developed in collaboration with @LangChainAI and taught by its Co-Founder and CEO, @hwchase17, focuses on building an agent with long-term memory, highlighting the importance of personal assistance and productivity tasks in the current technological landscape.

According to DeepLearning.AI, they have launched a new short course in collaboration with ArizeAI focused on evaluating the performance of AI agents. This course is designed to help participants track, test, and improve AI agent performance, which is crucial for ensuring optimized functionality and accuracy in practical applications.

According to Andrew Ng, a new course on how Transformer LLMs work has been announced, created in collaboration with Jay Alammar and Maarten Gr, co-authors of 'Hands-On Large Language Models'. This course provides an in-depth exploration of the transformer architecture, which is crucial for understanding the technology behind large language models.