|
所在平台: Coursera |
课程主页: https://www.coursera.org/learn/practical-python-for-ai-coding--preparation-for-coding
课程评论：没有评论
课程名称：实用Python AI编程入门1 课程概述：本课程为完全没有Python编程基础的初学者设计，无需任何软件编码的先前知识或经验。课程中选择、介绍并解释了在AI编码中常用的Python语法、函数和库。此外，还介绍了一些在AI编码中非常重要的语法和函数，并解释了NumPy、Pandas与TensorFlow之间的互补关系，因此即使是经验丰富的Python用户也能从中受益。课程开始时将指导学员在个人电脑或笔记本上成功构建AI编码环境，使学员能够在完成课程后开始使用Scikit-learn、TensorFlow和Keras进行AI建模和编码。通过本课程，学员在自己的电脑上建立了AI编码环境，无需借助云服务，即可开始AI编程。 课程大纲： 1. 准备编码：设置AI编码环境 - 描述： 2. Python编码的基本概念和规则 - 描述： 3. 原始数据类型 - 描述： 4. 控制语句和迭代 - 描述： 5. 创建函数 - 描述： 6. 非原始数据类型：列表和元组 - 描述： 7. 非原始数据类型：字典和集合 - 描述：
Name:Preparation for coding : Setting up AI coding environment
Description:
Name:Basic concepts and rules of Python coding
Description:
Name:Primitive data types
Description:
Name:Control statements and iteration
Description:
Name:Creating functions
Description:
Name:Non-primitive data types: Lists and tuples
Description:
Name:Non-primitive data types: Dictionaries and sets
Description:
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.
