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The tutor and student reviewed the student's Python assignment code, clarifying concepts such as data generation, graph interpretation, and the logic behind specific variable calculations. They discussed the importance of foundational Python skills and data structures for problem-solving, and planned to continue with list operations in the next session.

The Tutor and Student reviewed data visualization techniques using Matplotlib for plotting sensor data (temperature, vibration, load). They practiced creating labeled graphs and focused on the implementation of highlighting anomalies by plotting red dots, preparing for further discussion on metrics and assignment completion.

The Student and Tutor completed the Python coding for a sensor monitoring system, covering sensor data generation, anomaly detection, and CSV logging with real-time timestamps and automated data collection. They also implemented functions for statistical analysis of the logged data and received an introduction to Matplotlib for data visualization. The next session will focus on completing the visualization aspect of the assignment.

Student and Tutor covered Python file handling, including writing, reading, and appending to text files, as well as working with CSV files. They also learned about functions and applied these concepts to build functions for generating mock sensor data and detecting anomalies, directly addressing the requirements of the Student's assignment. The plan is to complete the assignment in the next class and then move on to data visualizations.

The Tutor and Student began reviewing a Python assignment to build a robotic arm monitoring system. They covered simulating sensor data using Python's `random` module, implementing anomaly detection with conditional logic, and discussed data logging into JSON/CSV files and the use of the `matplotlib` library for visualization. Future sessions will focus on file handling and data visualization theory.

The Student and Tutor reviewed key concepts of distributed databases in preparation for an upcoming exam. They covered the definition, problems with centralized systems, advantages and disadvantages of distributed databases, and the distinction between distributed processing and distributed databases. The session also detailed the components of a distributed database system and different types of transparency, with the Tutor sharing notes for revision.