By moving the AI and machine learning algorithms to the Oracle Database where the data is stored, Oracle database 23ai provides over 30 in-database parallel and scalable AI algorithms and allows us to use SQL or R and Python to securely run these AI algorithms directly on business data stored in the Oracle database. This session aims to help traditional database professions learn how to use these AI and machine learning algorithms through more familiar tools such as Oracle Machine Learning for SQL(OML4SQL) and OML notebook provided in the Oracle Autonomous Database (ADB) environment. Join us to learn the machine learning tasks such as data exploration and preparation, model building, model evaluation and model deployment in the Oracle Autonomous Database (ADB) through some live demos and examples. AutoML tools such as AutoML UI and AutoMI Python API will also be discussed in the session. We will touch a little bit on the AI vector search newly introduced in Oracle Database 23ai and how this vector search plays an important role in Retrieval Augmented Generation (RAG) with Large Language Models(LLMs). For more details on this topic, we will have a next topic: AI for Data: Vector search in Oracle Database 23ai