Program Overview

Program Overview

The Programming in Finance and Economics I course is a comprehensive program designed to teach students how to solve quantitative problems in economics and finance using Python.

Description

The course is structured along computational concepts, covering topics such as:

• The Jupyter Notebook environment, Anaconda, and Visual Studio Code
• Basic Python programming, including variables, types, operators, and main commands
• Modular programming, user-defined functions, and loops
• Working with data in Python, data sources, and data APIs
• Utilizing AI services and service APIs
• Introduction to numerical algorithms
• Random number generation and simple simulations
• Optimization techniques
• Finding and installing Python packages and deploying programs
• Writing successful programs and research reports in Python
• Debugging and improving Python programs with AI assistance

Prerequisites

This course requires basic knowledge of a programming language, as specified in the admission criteria to the Master in Finance. For USI bachelor graduates, Informatica I is sufficient. Students from other universities require a similar introduction to programming. Students with little or no programming experience or limited experience with Python can attend the Digicamp Bootcamp at the start of the semester.

Objectives

The course aims to teach students how to:

• Learn the most important elements of the Python language
• Understand the differences between analytical and numerical problem-solving
• Translate mathematical or statistical problems into Python
• Organize data efficiently using Python
• Write efficient and durable Python programs
• Interact with cloud services, including data providers and LLMs-as-service
• Use AI copilots and assess the validity of their suggestions

Teaching Mode

The course is taught in presence.

Learning Methods

The course starts with a voluntary two-week Digicamp Bootcamp for students with limited programming experience. The course itself is organized into seven blocks of four hours, introducing new concepts and employing learning-by-doing to move from theory to practice. Students complete short online tutorials before each class and participate in programming exercises that are submitted to an online system for instant feedback.

Examination Information

The course assessment consists of:

• 10% participation in online tutorials, graded on timely completion
• 10% individual programming exercises during the course phase, graded on correctness and programming style
• 80% programming project in small groups, due at the end of the semester, graded on:
  • Completeness and correctness
  • Programming style
  • User documentation
  • Complexity of the problem and solution

Education

The course is part of the following programs:

• Master of Science in Economics, Lecture, 120 ECTS, Elective, 2nd year
• Master of Science in Economics, Lecture, Internship or Electives, Elective, 2nd year
• Master of Science in Economics, Lecture, Mandatory if without internship, Elective, 2nd year
• Master of Science in Economics, Lecture, minor Data Science, 1st year
• Master of Science in Economics in Finance, Lecture, 1st year

Prerequisite

Informatics I, Tenconi P., SA

Additional Information

• Semester: Fall
• Academic year: Not specified
• ECTS: 3.0
• Language: English