Introduction to Python (online course)

If you are looking for a powerful programming language, you should learn Python, a language with a simple syntax and a powerful set of libraries. Python is easy for beginners to learn and is widely used in many fields, especially in scientific data exploration. In this one-day Python training workshop, you will learn to program using Python 3

Researchers, students, engineers, analysts, programmers who are interested in an introduction to the Python programming language.

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The primary aim of this introductory course is to provide learners with foundational knowledge of Python. It is designed for a broad range of participants, including students, researchers in data science and statistics, and other professionals seeking to learn and apply Python in their respective fields.

Learning Goals

By the end of this introductory course, participants will be able to:

• Understand the basics of Python, its practical uses, and its applications.
• Successfully set up Python environments and execute Python code.
• Master fundamental Python programming concepts.
• Gain exposure to key Python libraries

Detailed Learning Objectives:

• Install Anaconda for Python: Guide participants through the installation and setup of the Anaconda Distribution for Python.
• Grasp Python Fundamentals: Introduce essential Python concepts such as variables, data types, and data structures.
• Use Jupyter Notebook: Demonstrate effective usage of Jupyter - Notebook for running Python code interactively.
• Code Basics: Develop the ability to write and execute basic Python code, focusing on variables, comparisons, and core data structures.
• Create Python Statements: Teach participants to construct and apply Python statements (e.g., loops, conditionals).
• Use Python Methods and Functions: Explore built-in Python functions and methods to enhance coding efficiency.
• Develop Custom Functions: Enable participants to write their own Python functions for reusable code.
• Explore Python Libraries: Provide a brief introduction to important Python libraries such as NumPy, Pandas, and Matplotlib, which are essential for data analysis and visualization.