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课程名称:PCAP-31-03 Python编程认证助理考试准备 课程概述:PCAP-31-03课程专注于帮助学员为Python编程认证助理考试(PCAP)做准备。课程包含301道独特的问题,协助学员在第一次尝试中通过认证考试。该资格认证测量候选人解决与高级Python编程相关任务的能力,包括对象导向编程、高级概念、使用标准库模块和包,以及设计、构建和改进程序及应用等能力。 考试详细信息: - 考试名称:PCAP: Python编程认证助理 - 有效期:终身 - 考试时长:65分钟+10分钟非披露协议/教程 - 及格分数:70% - 问题数量:40道 - 格式:单选题和多选题 - 语言:英语 - 价格:约300美元 课程内容包括: 1. **模块和包(12%)**:涵盖导入和使用模块及包的各种方法,使用math和random模块生成随机值等。 2. **异常处理(14%)**:学习如何使用Python定义的异常处理错误以及自定义异常的创建与使用。 3. **字符串操作(18%)**:理解字符的机器表示,使用内置字符串方法进行各种操作。 4. **面向对象编程(34%)**:深入理解类和对象,类的结构及其方法的使用,构建继承的类层次结构等。 5. **其他内容(22%)**:包括使用列表推导式、闭包、输入/输出操作等。 Python因其简单易读的语法和广泛的应用而受到欢迎,涵盖从自动化、网页应用开发、人工智能到数据科学等多个领域。此课程旨在帮助学员提高编程能力,为未来的职业发展打下坚实基础。 无论你是第一次学习准备备考,还是希望再次挑战,PCAP认证考试将是你迈向高薪职业的新起点。
Certified Associate in Python Programming (PCAP) Exam Preparation - Carefully selected Certified Associate in Python Programming (PCAP) Exam Questions to help you pass on your first attempt. 301 Unique Questions.If you are planning to take Certified Associate in Python Programming (PCAP) Exam and want to see what kind of questions are coming in the Certified Associate in Python Programming (PCAP)- Real Exam, these practice questions are the best for you.Certification is a professional credential that measures the candidate's ability to accomplish coding tasks related to advanced programming in the Python language and related technologies, advanced notions and techniques used in object-oriented programming, the use of selected Python Standard Library modules and packages, designing, building and improving programs and applications utilizing the concepts of GUI and network programming, as well as adopting the coding conventions and best practices for code writing.Exam details:Exam name PCAP: Certified Associate in Python ProgrammingValidity: lifetimeDuration: 65 minutes + 10 minutes NDA/tutorialPassing score: 70%Number of questions: 40Format: single and multiple choice questionsLanguages: EnglishPrice: about $ 300Certified Associate in Python Programming: PCAP Exam Syllabus:#) Modules and Packages (12%)Import and use modules and packagesimport variants: import, from import, import as, import *advanced qualifying for nested modulesthe dir() functionthe sys.path variablePerform evaluations using the math modulefunctions: ceil(), floor(), trunc(), factorial(), hypot(), sqrt()Generate random values using the random modulefunctions: random(), seed(), choice(), sample()Discover host platform properties using the platform modulefunctions: platform(), machine(), processor(), system(), version(), python_implementation(), python_version_tuple()Create and use user-defined modules and packagesidea and rationalethe __pycache__ directorythe __name__ variablepublic and private variablesthe __init__. py filesearching for/through modules/packagesnested packages vs. directory trees#) Exceptions (14%)Handle errors using Python-defined exceptionsexcept, except:-except, except:-else:, except (e1, e2)the hierarchy of exceptionsraise, raise exassertevent classesexcept E as ethe arg propertyExtend the Python exceptions hierarchy with self-defined exceptionsself-defined exceptionsdefining and using self-defined exceptions#) Strings (18%)Understand machine representation of charactersencoding standards: ASCII, UNICODE, UTF-8, code points, escape sequencesOperate on stringsfunctions: ord(), chr()indexing, slicing, immutabilityiterating through strings, concatenating, multiplying, comparing (against strings and numbers)operators: in, not inEmploy built-in string methodsmethods:.isxxx(),.join(),.split(),.sort(), sorted(),.index(),.find(),.rfind()#) Object-Oriented Programming (34%)Understand the Object-Oriented approachideas and notions: class, object, property, method, encapsulation, inheritance, superclass, subclass, identifying class componentsEmploy class and object propertiesinstance vs. class variables: declarations and initializationthe __dict__ property (objects vs. classes)private components (instances vs. classes)name manglingEquip a class with methodsdeclaring and using methodsthe self parameterDiscover the class structureintrospection and the hasattr() function (objects vs classes)properties: __name__, __module__ , __bases__Build a class hierarchy using inheritancesingle and multiple inheritancethe isinstance() functionoverridingoperators:not is, ispolymorphismoverriding the __str__() methoddiamondsConstruct and initialize objectsdeclaring and invoking constructors#) Miscellaneous (22%)Build complex lists using list comprehensionlist comprehensions: the if operator, nested comprehensionsEmbed lambda functions into the codelambdas: defining and using lambdasself-defined functions taking lambdas as argumentsfunctions: map(), filter()Define and use closuresclosures: meaning and rationaledefining and using closuresUnderstand basic Input/Output terminologyI/O modespredefined streamshandles vs. streamstext vs. binary modesPerform Input/Output operationsthe open() functionthe errno variable and its valuesfunctions: close(),.read(),.write(),.readline(), readlines()using bytearray as input/output bufferPython 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:Python 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.Python 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.The 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.Earlier, 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.Perhaps this is your first step toward the certification, or perhaps you are coming back for another round. We hope that you feel this exam challenges you, teaches you, and prepares you to pass the Certified Associate in Python Programming (PCAP) Test. If this is your first study guide, take a moment to relax. This could be the first step to a new high-paying job and an AMAZING career.Practicing for an exam like the (PCAP) can be a full-time job. In fact some exams are actually paid for by work because they are so intensive. Certification is not simple and takes immense work. It takes time, practice, and the right focus. We understand that because we have been in this industry for years and working in space full of less savory test prep sources.