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Duke University

Python Programming Fundamentals

Duke University via Coursera

Overview

This introductory course is designed for beginners and individuals with limited programming experience who want to embark on their software development or data science journey using Python. Throughout the course, learners will gain a solid understanding of algorithmic thinking, Python syntax, code testing, debugging techniques, and modular code development--essential skills for a successful career in software engineering, development, or data science. By the end of this course, you will learn to: - Gain a stepwise approach to problem-solving using algorithms and programming logic. - Apply common functions, conditional statements, and loops to build Python scripts and programs. - Work with the VS Code programming environment to enhance coding proficiency. - Use testing and debugging strategies to ensure code reliability. - Perform logical and mathematical operations on datasets. In the final week of the course you will apply your new algorithm design and programming skills to a data analysis problem: analyzing heart rate data.

Syllabus

  • Algorithm Design
    • This module, you will learn best practices for developing code in any language by beginning with an algorithm: a stepwise approach to solving a problem. You’ll then apply the concepts by developing your own algorithms and properly identifying when to use specific data types in Python.
  • Translating Ideas into Code
    • This Module, you will learn how to take the logical process of algorithm design and translate an algorithm into functional Python code. You will apply this by correctly identifying proper Python syntax for a given algorithm, and then subsequently by creating your own Python program for a given algorithm.
  • Validating Your Code
    • This module, you will learn different approaches to testing Python code, and methods for debugging code. You will apply this by conducting a code review, identifying opportunities to use asserts to debug code, and generating your own test cases.
  • Diving Deeper with Lists
    • This module, you will learn how to filter and perform operations (logical and mathematical) across a given dataset, and how to create modular code that can be used in discrete pieces. You will apply this by writing your own functions to identify a list item with a given property, and writing a program to calculate a set of conclusions from a given dataset.

Taught by

Andrew D. Hilton, Nick Eubank, Genevieve M. Lipp and Kyle Bradbury

Reviews

3.9 rating at Coursera based on 38 ratings

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