Collecting and Preparing High-Quality Data

Data is the fuel for any AI project, so gathering, cleaning, and preparing relevant data is essential. When exploring how to build an AI agent, you must ensure that your data is diverse, representative, and accurately reflects real-world scenarios. This step involves eliminating duplicates, handling missing values, and normalizing data formats, all of which create a solid foundation for your agent’s success.