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所在平台: Udemy |
课程主页: https://www.udemy.com/course/google-colab-for-data-science-ai-using-python/
课程评论：没有评论
课程名称：学习使用 Google Colab 的 Python 课程概述：本课程旨在从零开始教授 Python 编程，采用实践导向的方式，非常适合初学者。Python 是一种功能强大、多用途且友好的编程语言，广泛应用于网页开发、数据科学、自动化和人工智能。在此课程中，您将使用 Google Colab 这一免费、基于云的编程平台来学习 Python，无需安装任何软件，您可以从任何设备轻松编写和执行 Python 代码。通过逐步的课程、动手练习和真实世界的实例，您将建立扎实的 Python 编程基础，并培养实际应用所需的技能。无论您是绝对初学者、学生还是希望提升技术能力的专业人士，本课程将为您提供系统的学习体验。 您将学习： - Python 基础：理解 Python 语法、变量、数据类型、运算符和表达式。 - 控制流程和循环：实现条件语句（if-else）、循环（for、while）及循环控制机制（break、continue）。 - 函数与模块化编程：编写可重用的代码，使用函数、参数、返回值和 lambda 函数。 - 数据结构：学习如何有效存储和操作数据，包括列表、元组、字典和集合。 - 面向对象编程（OOP）：理解 OOP 原则，包括类、对象、继承、封装和多态。 - 文件处理与异常管理：使用 try-except 块有效读取、写入和处理文本及 CSV 文件。 - 使用 Google Colab 的实践：探索 Google Colab 的功能，包括代码单元、markdown、文件管理和库集成。 - Python 库的使用：利用 NumPy、Pandas、Matplotlib 和 Seaborn 进行数据处理和可视化。 - 正则表达式与 API 交互：使用 requests 库进行文本处理的模式匹配和与外部 REST API 的交互。 - 高级 Python 特性：学习装饰器、迭代器、生成器和上下文管理器，以编写高效的 Python 代码。 - 数据分析与可视化：加载和分析数据集，清理和转换数据，并使用 Plotly 创建交互式图表。 - 机器学习简介：基本了解机器学习，探索数据预处理和使用 scikit-learn 训练简单模型。 课程亮点： - 100% 动手学习：在实际编码练习和项目中应用 Python 概念。 - 无需安装：直接在 Google Colab 中工作，消除设置复杂性。 - 逐步指导：每个概念都有明确的示例和练习。 - 实际应用：学习 Python 在自动化、数据科学和网页开发中的应用。 - 互动编码体验：在结构化环境中与导师主导的练习一起编码。
Learn Python from Scratch Using Google Colab - A Hands-On, Beginner-Friendly Approach!Python is one of the most powerful, versatile, and beginner-friendly programming languages used in web development, data science, automation, and artificial intelligence. In this course, you will learn Python from scratch using Google Colab, a free, cloud-based coding platform that eliminates the need for software installation, making it easy to write and execute Python code from any device.Through step-by-step lessons, hands-on exercises, and real-world examples, you will build a strong foundation in Python programming and develop the skills needed for practical applications. Whether you are an absolute beginner, a student, or a professional looking to enhance your technical skills, this course will provide the structured learning experience you need.What You Will LearnPython Basics - Understand Python syntax, variables, data types, operators, and expressions. Control Flow and Loops - Implement conditional statements (if-else), loops (for, while), and loop control mechanisms (break, continue).Functions and Modular Programming - Write reusable code using functions, parameters, return values, and lambda functions.Working with Data Structures - Learn how to store and manipulate data efficiently with lists, tuples, dictionaries, and sets Object-Oriented Programming (OOP) - Understand the principles of OOP, including classes, objects, inheritance, encapsulation, and polymorphism.File Handling & Exception Management - Read, write, and process text and CSV files while handling errors efficiently using try-except blocks.Hands-On with Google Colab - Explore the features of Google Colab, including code cells, markdown, file management, and library integration. Working with Python Libraries - Use NumPy, Pandas, Matplotlib, and Seaborn for data manipulation and visualization.Regular Expressions & API Interactions - Apply pattern matching for text processing and interact with external REST APIs using the requests library.Advanced Python Features - Learn about decorators, iterators, generators, and context managers for writing efficient Python code.Data Analysis and Visualization - Load and analyze datasets, clean and transform data, and create interactive plots using Plotly.Introduction to Machine Learning - Get a basic understanding of machine learning, explore data preprocessing, and train simple models using scikit-learn.Course Highlights100% Hands-On Learning - Apply Python concepts in real-world coding exercises and projects.No Installations Required - Work directly in Google Colab, eliminating setup complexities. Step-by-Step Guidance - Every concept is explained with clear examples and practice exercises. Practical Applications - Learn how Python is used in automation, data science, and web development. Interactive Coding Experience - Code along with instructor-led exercises in a structured environment.
