Principles of Programming

Upon completion of the course, the student will be able to

• design, structure and implement simple programs in Python,
• understand the setup and philosophy of the programming environment and of the different methods of interacting with the language kernel (command windows/scripts/notebooks),
• use different data types, operands, and control flow commands to build programs,
• understand the main techniques of functional programming,
• use the core Python libraries for Finance applications (Numpy, Scipy, Pandas).

Prerequisites:

No prerequisites.

Course contents:

• Overview of the programming environment:
  • Anaconda
  • Command window
  • Spyder and Scripts
  • Jupyter Notebooks
• Program components
  • Data types
  • Operands
  • Conditions
  • Control Flow instructions
  • Loops
• Functional programming
  • Designing and implementing functions (local/global)
  • Loading functions
  • Overloading and adapting functions.
• Overview of the main Python libraries.
  • Numpy: Numerical calculations
  • Scipy: Optimization, numerical computing
  • Sympy: Symbolic computing
  • Matplotllib: Generating graphs
  • Pandas: Database manipulation
  • Yahoofinance: Downloading financial data

Recommended reading:

• Python for Finance: Analyze Big Financial Data by Yves Hilpisch, O’Reilly 2021.
• Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib 2nd ed. Edition by Robert Johansson.

Teaching methods:

The course is conducted in the class, and the students must bring their laptops to practice the taught material. The free Anaconda environment should be installed.

Language of instruction:

English.