The interview consisted of 2 rounds: the first focused on intermediate-level Python programming and project-related questions, including two list-based Python tasks solvable within 20 minutes each—emphasizing the need for practice with concise interview questions. The second round was more challenging, probing deep into machine learning expertise, including questions on lending projects, dimensionality reduction, and statistical concepts such as bias, variance, and probability.