The course is organized in four lectures that cover the full life-cycle of an AI & ML product from the research and formulation of the business idea, how initial and user data is collected, curated, and standardized, so it can be fed back to the system, what the tools that are available to train and evaluate your ML models are, followed by best practices when deploying and monitoring your model.