Programming in Python

Why Python?

  • Readable Syntax: Python's simple, natural language-like syntax makes it easy to learn and understand, even for beginners.
  • Wide Community Support: Extensive resources, tutorials, and a large user base make it accessible and beginner-friendly.
  • Versatile Applications: Suitable for a variety of fields, including data analysis, web development, artificial intelligence, and more.
  • Comprehensive Libraries: Offers powerful libraries like Pandas, NumPy, and Matplotlib, simplifying complex tasks with minimal code.
  • Interactive Development: Tools like Jupyter Notebooks make Python coding interactive and ideal for learning and experimenting.

Important Python Packages

A package in Python is a collection of modules, functions, and documentation that extends the capabilities of the base Python programming language, simplifying tasks like data manipulation, visualization, and numerical computing; the packages listed below are particularly useful for data analysis and scientific research.

  • Pandas: A powerful tool for data analysis and manipulation, handling diverse datasets and cleaning messy data.
  • Seaborn: A visualization library for creating clear, high-quality graphs, including relational, distribution, and categorical plots.
  • NumPy: A fundamental library for numerical computing, offering efficient tools for arrays, linear algebra, and matrix operations.

Introductory Python Courses at Duke

  • COMPSCI 94: Programming and Problem Solving
    • Learn the basics of programming by studying problems in one application area such as genomics, animation, robotics, etc.
  • COMPSCI 101: Introduction to Computer Science
    • Introduction to practices and principles of computer science and programming, including their social impact
    • Emphasis on the design, implementation, testing, and analysis of algorithms and programs.

Asynchronous Python Courses