The course introduces students to computational tools for data processing and visualization in a clear and effective way for engineering applications. It begins with Python programming fundamentals, covering functions, operators, conditions, loops, string operations, and data structures. Students then progress to file handling, random data generation, and working with formats such as TXT, CSV, and JSON. The core of the course focuses on data analysis using Pandas and NumPy, enabling exploration, filtering, grouping, and statistical evaluation of tabular datasets. Visualization techniques are taught with Matplotlib and Seaborn, including scatter plots, histograms, heatmaps, and boxplots. The course combines theoretical knowledge with practical project-based learning, preparing students to handle and present engineering data.