1. Review the project brief, objectives, and supporting material to understand the scope and expected outcome.

2. Carry out the main task described in the submission, including data collection & preprocessing gather cybersecurity and network data from smart grid-related sources and perform preprocessing such as handling missing values, normalization, and feature selection. machine learning model development develop and train machine learning and deep learning models (e.g., random forest, svm, lstm) for detecting cyber threats and anomalies. intrusion detection system (ids) development assist in designing and implementing a machine learning-based ids for monitoring and identifying suspicious activities in real time. cyberattack simulation & testing simulate different types of cyberattacks such as dos, false data injection, and mitm to evaluate system robustness and detection capability. performance evaluation & documentation analyze model performance using metrics like accuracy, precision, recall, and f1-score, and prepare reports and documentation of finding.

3. Develop, implement, or refine the central solution for machine learning intern, electrical and electronics intern, whether that involves a model, prototype, simulation, or analytical workflow.

4. Test and evaluate intermediate results, compare alternatives, and improve the approach based on performance or observations.

5. Document methods, assumptions, findings, and final results for reporting, discussion, or publication.