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所在平台: Udemy |
课程主页: https://www.udemy.com/course/its-303-python-certification-exam-t-specialist-preparation/
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课程名称：ITS-303 Python认证考试IT专家准备 课程概述：现在是获得Python认证的最佳时机！本课程专为准备IT专家Python认证考试（Certiport Pearson VUE）而设计，涵盖以往微软MTA 98-381的内容。课程包含六个练习测试，涵盖所有知识领域的准备问题，帮助考生为考试做好准备。每个问题都有详细解释，并提供“自己动手试试”的代码，考生可以运行这些代码以更好地理解相关主题。同时，您可以下载所有问题的代码（下载链接在欢迎邮件中）。 课程大纲： 1. 数据类型和运算符的操作 - 评估表达式以识别Python为变量分配的数据类型：str、int、float和bool。 - 执行和分析数据及数据类型操作：类型转换、索引、切片、构建数据结构、列表及列表操作。 - 根据运算符优先级确定执行顺序：赋值、比较、逻辑、算术、身份（is）、包含（in）。 - 选择操作符以实现预期结果。 2. 决策与循环的控制流 - 构建和分析使用分支语句的代码段：if、elif、else、嵌套和复合条件表达式。 - 构建和分析执行迭代的代码段：while、for、break、continue、pass、嵌套循环及包含复合条件的循环。 3. 输入和输出操作 - 构建和分析执行文件输入和输出操作的代码段：打开、关闭、读取、写入、追加、检查存在性、删除、with语句。 - 构建和分析执行控制台输入和输出操作的代码段：从控制台读取输入、打印格式化文本（string.format()方法、f-String方法）、使用命令行参数。 4. 代码文档和结构 - 文档化代码段：使用缩进、空格、注释和文档字符串；通过pydoc生成文档。 - 构建和分析包含函数定义的代码段：调用签名、默认值、返回、def、pass。 5. 故障排查与错误处理 - 分析、检测和修复有错误的代码段：语法错误、逻辑错误、运行时错误。 - 分析和构建处理异常的代码段：try、except、else、finally、raise。 - 进行单元测试：unittest、函数、方法及断言方法（assertIsInstance、assertEqual、assertTrue、assertIs、assertIn）。 6. 使用模块和工具的操作 - 使用内置模块执行基本文件系统和命令行操作：io、os、os.path、sys（导入模块、打开、读取和写入文件、命令行参数）。 - 解决复杂计算问题：Math（fabs、ceil、floor、trunc、fmod、frexp、nan、isnan、sqrt、isqrt、pow、pi）、datetime（now、strftime、weekday）、random（randrange、randint、random、shuffle、choice、sample）。 为什么要学习Python？ Python易于学习，语法简单，代码可读性强。使用Python编写程序的代码行数少于大多数其他编程语言。Python的流行迅速增长，现在已成为最受欢迎的编程语言之一。Python的应用广泛，涉及自动化、Web应用开发、人工智能、数据科学等多个领域。 - 自动化：Python能够通过自动化任务（如网站抓取、软件测试用例自动化及日常办公室任务）使生活更加便利。 - Web开发：Python是快速Web应用开发的理想选择，使用Django、Pyramid和Flask等框架可快速开发Web应用。 - 人工智能：随着人工智能时代的来临，Python在智能系统开发中变得越来越受欢迎。 - 数据科学：Python在数据科学领域的应用增长迅速，凭借其简单性和强大的计算能力，数据科学家们对其依赖不断加大。 总之，Python在IT行业的广泛应用趋势不会减缓，未来将继续在不断变化的发展环境中占据重要地位。
Now is the time to get certified for Python!ITS-303 Python (Information Technology Specialist)Formerly Microsoft MTA 98-381There are six Practice Tests with preparation questions from all knowledge areasto prepare for the ITS-303 Python (Information Technology Specialist) exam at Certiport (Pearson VUE).Every question has an explanation and a Try-It-Yourself-Codewhich you can run to better understand the topic.You can download the Try-It-Yourself-Code for all questions.(The download link will be in your welcome message.)Exam SyllabusOperations using Data Types and OperatorsEvaluate expressions to identify the data type Python assigns to variables:str, int, float, and boolPerform and analyse data and data type operations:Data type conversion, indexing, slicing, construct data structures, lists, list operationsDetermine the sequence of execution based on operator precedence:Assignment, comparison, logical, arithmetic, identity (is), containment (in)Select operators to achieve the intended result:Assignment, comparison, logical, arithmetic, identity (is), containment (in)Flow Control with Decisions and LoopsConstruct and analyze code segments that use branching statements:if, elif, else, nested and compound conditional expressionsConstruct and analyze code segments that perform iteration:while, for, break, continue, pass, nested loops, loops that include compound conditional expressionsInput and Output OperationsConstruct and analyze code segments that perform file input and output operations:open, close, read, write, append, check existence, delete, with statementConstruct and analyze code segments that perform console input and output operations:Read input from console, print formatted text (string.format() method, f-String method), use command-line argumentsCode Documentation and StructureDocument code segments:Use indentation, white space, comments, and documentation strings; generate documentation by using pydocConstruct and analyze code segments that include function definitions:Call signatures, default values, return, def, passTroubleshooting and Error HandlingAnalyze, detect, and fix code segments that have errors:Syntax errors, logic errors, runtime errorsAnalyze and construct code segments that handle exceptions:try, except, else, finally, raisePerform unit testingUnittest, functions, methods, and assert methods (assertIsInstance, assertEqual, assertTrue, assertIs, assertIn)Operations using Modules and ToolsPerform basic file system and command-line operations by using built-in modules:io, os, os.path, sys (importing modules, opening, reading and writing files, command-line arguments)Solve complex computing problems by using built-in modules:Math (fabs, ceil, floor, trunc, fmod, frexp, nan, isnan, sqrt, isqrt, pow, pi) datetime (now, strftime, weekday), random (randrange, randint, random, shuffle, choice, sample)Why learn Python?Python is easy to learn. The syntax is simple and the code is very readable. With Python, you can write programs in fewer lines of code than with most other programming languages. The popularity of Python is growing rapidly. It is now one of the most popular programming languages. Python has a wide variety of applications. It is used for automation, web application development, artificial intelligence, data science and so on:AutomationPython can make life easier by automating many tasks, such as scraping a website to collect data, automating test cases in software development, or automating everyday office tasks. Python can easily access and read all kinds of files, which opens up the possibility of saving a lot of time by automating repetitive tasks.Web DevelopmentPython is a good choice for rapid web application development. With many frameworks like Django, Pyramid, and Flask, you can develop web applications with great speed using Python. Python is used on the server side of web development. You can use Python to interact with database and create RESTful API services.Artificial IntelligenceThe near future will be the era of artificial intelligence. In the past, computers and machines were used to perform mathematical calculations at very high speeds, but now many large organizations and researchers are working to develop intelligent systems that can perform tasks like a human. To some extent, machines are able to understand human emotions and their natural language. They can mimic certain human actions that were not possible before. Again, Python is very popular for developing AI systems.Data ScienceEarlier, Python was mainly used to build applications and write scripts to automate tasks, but now a brand new trend of data science has given Python an even bigger boost. Data scientists are heavily dependent on Python because it is so simple, has a large community, and can perform huge calculations with ease.Python is being used in a wide variety of fields, and there are no signs that this trend is coming to a halt. It's safe to say that Python is here to stay for the long haul in this ever-changing and evolving IT industry.
