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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/practical-python-for-ai-coding-2
课程评论：没有评论
课程名称：实用Python人工智能编程2 概述：该课程专为Python编程初学者设计，无需任何软件编码的先前知识或经验。课程精选、介绍并解释在人工智能编程中常用的Python语法、函数和库。此外，课程还介绍了在AI编程中常用的重要语法和函数，并解释了NumPy、Pandas和TensorFlow之间的互补关系，因此即使是经验丰富的Python用户也能受益。课程开始时，会指导学员在个人电脑或笔记本上构建AI编程环境，以便能在完成课程后使用Scikit-learn、TensorFlow和Keras进行AI建模和编码。通过该课程，学员将拥有自己的AI编程环境，无需加入或使用基于云的服务即可开始AI编码。 课程大纲： - 名称：Numpy库：使用数组 - 描述：讲解Numpy库的基本用法及其在数据处理中的应用。 - 名称：Pandas库：使用DataFrames - 描述：介绍Pandas库及其在数据分析中的功能。 - 名称：字符串和文件 - 描述：讲解如何处理字符串数据和文件操作。 - 名称：数据可视化：matplotlib和seaborn - 描述：学习如何使用这两个库进行数据可视化。 - 名称：面向对象编程：引入类对象 - 描述：介绍面向对象编程的基础知识。
Name:Numpy library: Using arrays
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Name:Pandas library: Using DataFrames
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Name:Strings and files
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Name:Data visualization: matplotlib and seaborn
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Name:Object oriented programming: introducing class object
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Introduction video : https://youtu.be/TRhwIHvehR0 This course is for a complete novice of Python coding, so no prior knowledge or experience in software coding is required. This course selects, introduces and explains Python syntaxes, functions and libraries that were frequently used in AI coding. In addition, this course introduces vital syntaxes, and functions often used in AI coding and explains the complementary relationship among NumPy, Pandas and TensorFlow, so this course is helpful for even seasoned python users. This course starts with building an AI coding environment without failures on learners’ desktop or notebook computers to enable them to start AI modeling and coding with Scikit-learn, TensorFlow and Keras upon completing this course. Because learners have an AI coding environment on their computers after taking this course, they can start AI coding and do not need to join or use the cloud-based services.
