Digital Tools

The course provides fundamental Python skills for solving engineering problems. After successfully completing the course, students will be able to:

• understand the fundamentals of programming in Python (variables and expressions, control structures, functions, and common data structures)
• use the core components of Python’s extensive scientific computing toolkit (NumPy, SciPy, Matplotlib, Pandas, Python Control)
• find, read, and understand technical documentation
• use the necessary tools and environments for developing and running Python programs
• apply these skills to solve typical engineering problems

Python Fundamentals:

• Types, values, variables, expressions, operators
• Conditionals and loops
• Functions
• Basic data structures

Object-Oriented Programming:

• Classes and objects
• Attributes and methods
• Inheritance
• Polymorphism
• Dataclasses

Scientific Computing with Python:

• NumPy: arrays, vectorized operations, linear algebra
• Matplotlib: various plots, interactive visualizations, and animations
• SciPy: numerical integration, solving equations, optimization
• Pandas: series, tables, statistics, and other aggregations
• Python Control Systems Library: transfer functions, state-space representations, working with linear time-invariant systems

Python Projects:

• Structuring and setting up projects
• Testing
• Programming best practices

The lecture materials accompanying the course “Digital Tools” are provided on the “Python for Engineers” website and on StudIP. These primarily include the lecture notes, exercise assignments, an online development environment, and optional supplementary materials.