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所在平台: Udemy |
课程主页: https://www.udemy.com/course/introduction-to-python-t/
课程评论：没有评论
Coursera 课程总结：Python 与机器学习入门 本课程旨在教授学员 Python 编程语言的基础知识及在机器学习领域的应用。Python 作为一门在全球范围内广受欢迎且需求量大的编程语言，尤其在商业领域和就业市场中，其受欢迎程度远超 Java 或 C++。Python 开发者的平均年薪超过 10 万美元，且预计未来还将持续增长。Python 以其易学性著称，即使是零编程基础或不熟悉其语法的学员，也能通过本课程成为专业的 Python 程序员。 课程内容涵盖： * **Python 基础编程：** 掌握 Python 的基本语法和编程概念。 * **文件操作：** 学习 Python 的文件读写功能。 * **自动化：** 实现 Word 和 Excel 文件的自动化处理。 * **网络爬虫：** 使用 BeautifulSoup4 进行网页内容抓取。 * **浏览器自动化：** 利用 Selenium 控制浏览器进行自动化操作。 * **数据分析与可视化：** 使用 Matplotlib 进行数据可视化。 * **正则表达式与任务管理：** 掌握 Regex 解析和任务管理技巧。 * **GUI 与游戏开发：** 使用 Tkinter 进行图形用户界面和游戏开发。 * **科学计算与库：** 深入理解 Python 在科学计算中的应用，特别是 NumPy, Pandas, Matplotlib, Seaborn 和 SciKit Learn 等库。 学完本课程，您将能够： * 熟练掌握 Python 编程。 * 使用 NumPy 和 Python 创建和操作数组。 * 利用 Pandas 创建和分析数据集。 * 使用 Matplotlib 和 Seaborn 库创建高质量的数据可视化图表。 * 构建包含多个 Python 数据分析项目的作品集，以展示给潜在雇主。 * 理解机器学习的基础概念，并初步了解 SciKit Learn 的用法。 此外，学员还将获得对课程中超过 100 个 Python 代码示例 Notebook 的终身访问权限，以及课程更新和未来新增的数据分析项目。
Python has rapidly become one of the most popular programming languages around the world. Compared to other languages such as Java or C++, Python consistently outranks and outperforms these languages in demand from businesses and job availability. The average Python developer makes over $100,000 - this number is only going to grow in the coming years.The best part? Python is one of the easiest coding languages to learn right now. It doesn't matter if you have no programming experience or are unfamiliar with the syntax of Python. By the time you finish this course, you'll be an absolute pro at programming!This course will cover all the basics and several advanced concepts of Python. We'll go over:The fundamentals of Python programmingWriting and Reading to FilesAutomation of Word and Excel FilesWeb scraping with BeautifulSoup4Browser automation with SeleniumData Analysis and Visualization with MatPlotLibRegex parsing and Task ManagementGUI and Gaming with TkinterAnd much more!You'll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data.You will also get lifetime access to over 100 example python code notebooks, new and updated videos, as well as future additions of various data analysis projects that you can use for a portfolio to show future employers!By the end of this course you will:- Have an understanding of how to program in Python.- Know how to create and manipulate arrays using numpy and Python.- Know how to use pandas to create and analyze data sets.- Know how to use matplotlib and seaborn libraries to create beautiful data visualization.- Have an amazing portfolio of example python data analysis projects!- Have an understanding of Machine Learning and SciKit Learn!
