The interview was focused on sql, python and machine learning concepts. For SQL, candidates might expect questions related to querying databases, manipulating data, and understanding relational database concepts such as joins, indexes, and normalization. In Python, questions could cover topics like data manipulation libraries (such as Pandas), data visualization (using libraries like Matplotlib or Seaborn), and potentially even machine learning libraries like Scikit-learn or TensorFlow. As for machine learning concepts, candidates might be asked about fundamental algorithms (e.g., linear regression, decision trees), model evaluation techniques, feature engineering, and potentially more advanced topics depending on the role's requirements.