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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-analysis-with-python-full-course-for-beginners/
课程评论：没有评论
课程名称：2024年初学者Python数据分析全课程 课程概述： 本课程旨在帮助学生入门Python编程语言。Python是一种强大且现代的编程语言，适合有经验的程序员，同时也易于初学者学习。课程涵盖了学习Python所需的所有基础知识，并提供定期的测验和动手练习，以帮助学生深入理解并实践所学的概念。我们鼓励学生在学习中犯错，纠正错误并从中吸取经验。 课程内容： 1. **Python基础**：介绍Python及其安装工具，讲解学习Python的原因及其功能。 2. **编程基础**：奠定编程基础，包括数据类型、运算符、控制流、作用域等，结合实际例子展示如何使用这些概念。 3. **Python数据结构**：理解数据结构对于编程的重要性，重点讲解列表、元组和字典的使用和方法。 4. **Pandas库**：深入探讨Pandas库的函数，学习如何读取、提取、处理和操作数据，以及在数据科学和机器学习中常用的技术。 5. **Numpy库**：介绍Numpy科学计算包，演示如何进行数据处理，包括切片、索引、分组等操作。 6. **函数式编程**：学习Python中的函数式编程特性，使数据处理更加高效，包括Lambda函数、filter、map和reduce。 7. **异常处理**：了解代码中常见的错误，学习高效调试和处理异常的技巧。 8. **文件输入输出**：介绍从文件中读取和写入数据的Python概念，学习如何定位、打开、读取和关闭文件。 9. **课程项目**：通过真实的商业案例，运用Pandas和Numpy处理数据，解决商业问题，实践Python技能。 通过以上课程内容，学员将能够打下坚实的Python基础并能够进行数据分析。快来开始你的Python编程之旅吧！
Get startedPython is a powerful, modern programming language that has the capabilities required for experienced programmers, while being easy enough for beginners to learn. The course covers everything you need to get started with Python. The course also provides regular quizzes and hands-on exercises to enable you not only to understand the concepts but to practice them thoroughly. "Talk is cheap, show me your code", we want you to make mistakes, correct them and learn from experience.HighlightHere is a brief description of what you will learn in each section.Section 1. Python.This section covers the basics of Python, from python introduction to installing the required tools.Why learn Python? What Python can do? How to install Python tool kits?Section 2. FundamentalsIn this section, we will lay foundations on programming basics, such as data types, operators, control flows, scope etc. These concepts can apply to other programming languages as well. You may have heard of If statement, for loops, while loop before. In this section, we will use real examples to demonstrate the usage. Section 3: Python Data structuresUnderstanding data structures are vital to every programming. We will go through the three key data structures in Python and discuss how to use them efficiently. List/Tuple/DictionaryMethods in List/Tuple/DictionaryList comprehensionSection 4: PandasPandas is go-to library for data analysis in Python. In this section, we will go into the details of pandas library functions, and how to read, extract, process, manipulate data in Pandas. The techniques in this section are often used in data science and machine learning processes. Slicing IndexingGroupingFilteringUpdatingSection 5: NumpyNumpy is a python package for scientific computing. It provides a fast and flexible data processing data structure in Python. In this part, we will show how to use numpy to do data processing, such as slicing, indexing, grouping, filtering, updating, creating etc. Section 6: Functional ProgrammingPython functional programming features can make data processing more efficient. In this section, we will cover a few functional programming, such as Lambda function, filter, map, reduce.LambdaFilterMap ReduceSection 7: Exception handlingWhen writing codes, it takes time to debug. In this section, we will learn what are the usual type of errors in the code, how we can efficiently debug, and how to handle the exceptions. try: except blockRaise errorPrinciples for using exceptionsSection 8: File Input/OutputIn real life, data reside in files. In this part, we will introduce the python concepts necessary to use data from files in the programs, such aslocate filesopen/read fileswrite files close filesSection 9: Course projectIn this section, you will get exposure to a real business case and process the data using Pandas and Numpy to solve a few business questions. You will practice your python skills with real examples. _________________________________________________________________________So what are we waiting for? Let's begin our Python journey and start coding!
