What mistakes should MCA students avoid while learning machine learning?

Machine learning uses data to build models that identify patterns or make predictions. Students should learn data preparation, model selection, evaluation and the limitations of predictions. This makes machine learning more valuable when it is supported by hands-on practice and a clear explanation of what you built. This point is specifically relevant to the machine learning aspect of MCA study. For this specific question about machine learning, the practical takeaway is to relate the concept to your own MCA learning goal. In other words, this guidance addresses: What mistakes should MCA students avoid while learning machine learning?