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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learn-python-a-to-z/
课程评论：没有评论
**Python A to Z：从零基础到进阶的全面指南** 本课程是一门从零开始、系统教授Python编程的综合性课程，涵盖Python IDLE和Google Colab的实际操作。课程内容从基础的变量创建、数值运算，到条件语句、循环，再到数据可视化、Pandas数据结构、数据科学、SQL连接及人脸识别等高级主题，提供了一站式的Python学习体验。 **课程亮点：** * **全面涵盖：** 从Python基础到数据科学、SQL连接和AI应用，满足各类学习需求。 * **代码实践：** 每节课都包含代码实现，强调动手能力。 * **工具支持：** 涵盖Python IDLE和Google Colab两大常用开发环境。 * **项目导向：** 课程最后设有课程作业和多个小型项目，巩固所学知识。 **课程大纲概览：** 1. **Python基础：** Python介绍、IDLE使用、基本代码编写、函数访问、数值运算、控制语句、代码保存与执行、程序结构、标识符、关键字、变量、运算符、数据类型、表达式、注释、输入输出、数据类型转换、调试。 2. **Google Colab实战：** Colab介绍、安装与打开、代码编写、函数访问、数值运算、控制语句、代码保存与执行。 3. **进阶编程：** 条件语句的多种变量实现、for循环与while循环的应用、系列打印。 4. **列表操作：** 列表创建、初始化、遍历、操作、常用方法（len(), append(), remove(), sort()等）及内置函数。 5. **Pandas库：** Pandas简介、Series（创建、操作、属性、选择）与DataFrame（创建、操作、索引、布尔索引）详解。 6. **数据可视化：** Matplotlib绘图原理，绘制线图、柱状图、直方图，并进行图表定制（标签、标题、图例）。 7. **数据科学与SQL：** CSV文件读取、SQL语言（DDL, DQL, DML）介绍、MySQL数据库操作（创建、使用、查询、数据定义与操作命令）、SQL连接Python、人脸识别项目。
This is an amazing course from A to Z which will be taking you from scratch level to advance one by one with a code implementation.This course covers from Python IDLE basic codes to Google colab code.It includes all basic as well as advance concepts like variable creation,simple and multiple numerical operations,conditional statements,loops,data visualization,pandas data structure,Data science, Sql Connectivity and Face Recognization.At the end of this course students will be getting a course work with many mini projects in the last lecture.This is a one stop course on Python which provides a perfect package covering all possible things in python Course Work-Lecture 11. Introduction to python2. Opening IDLE3. Writing first code on IDLE4. Accessing function 5. Simple and complex numerical's 6. Control Statements7. Saving and execution of code 8.Basics of Python programming9.Python interpreter - interactive and script mode10. The structure of a program, indentation, identifiers, keywords, constants, variables, types of operators, precedence of operators, data types, statements, expressions, evaluation of expressions, comments, input and output statements, data type conversion, debugging,Recapitalization and implementation of codes on Google Colab1. Introduction to google colab2. Installing and opening google colab 3. Writing first code 4. Accessing function 5. Simple and complex numerical's 6. Control Statements7. Saving and execution of code on google colabLecture 2-1. Implementation of conditional statements using 2 or more variables.2. Implementation of for loop,while loop using different possibilities3.Printing seriesLecture 3-1.Implementation of list.2.Functions on List3.Execution of ListList operations - creating, initializing, traversing and manipulating lists, list methods and built-in functions.: len(), list(), append(), extend(), insert(), count(), find(), remove(), pop(), reverse(), sort(), sorted(), min(), max(), sum()Lecture 4-Introduction to Python libraries- Pandas, Matplotlib. ● Data structures in Pandas - Series and data frames.Series: Creation of series from dictionary, scalar value; mathematical operations; series attributes, head and tail functions; selection, indexing and slicing.Lecture 5-Data Frames: Creation of data frames from dictionary of series, list of dictionaries, text/CSV files, display, iteration. Operations on rows and columns: add ( insert /append) , select, delete (drop column and row), rename, Head and Tail functions, indexing using labels, Boolean indexing.Lecture 6-Data Visualization: Purpose of plotting, drawing and saving of plots using Matplotlib (line plot, bar graph, histogram). Customizing plots:; adding label, title, and legend in plots.Lecture 7-Accessing ,uploading and reading csv files through python.-Structured Query Language: Data Definition Language, Data Query Language and Data Manipulation Language, Introduction to MySQL: Creating a database, using database, showing tables using MySQL, Data Types: char, varchar, int, float, date. -Data Definition Commands: CREATE, DROP, Data Query ,INSERT, UPDATE and DELETE.-Creation and doping of Databases-Connecting my sql to Python - Install sql connector,pip commands on google colab.-Face Recognization project at the end
