Certified Associate in Python Programming Practice Test 2023

12 de enero de 2023 0

Here we go!!

PCAP™ – Certified Associate in Python Programming 2023 (With explanation and including pictures)

Are you ready to take the PCAP™ – Certified Associate in Python Programming exam? Test yourself by answering 121 questions! This course is in the form of practice tests and consists of 121 questions that may appear during the PCAP™ – Certified Associate in Python Programming exam. Some questions are self-explanatory. Where necessary, explanations are added to the questions. This course allows you to confirm your proficiency and give you the confidence you need to earn the PCAP™ – Certified Associate in Python Programming certification.

Certified Associate in Python Programming PCAP Practice test

PCAP Certified Associate in Python Programming PCAP Practice test Learn python Certified Associate Programming

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The PCAP™ certification shows that the individual is familiar with the following concepts: modules, packages, and PIP, character encoding, strings and string processing, generators, iterators, closures, files, file streams, and file processing, exception hierarchies, and exception classes and objects, working with selected Standard Library modules, and the fundamentals of the Object-Oriented Programming (OOP) approach.

PCAP™ – Certified Associate in Python Programming certification gives its holders confidence in their programming skills, helps them stand out in the job market, and gives them a head start on preparing for and advancing to the professional level.

Real Exam details:

duration: 65 minutes + 10 minutes NDA/tutorial
passing score: 70%
number of questions: 40
format: single and multiple choice questions
languages: English
price: about $ 300

Can I take the practice test more than once?

You can take each practical test multiple times. After completing the practice test, your final result will be published. Each time you take the test, the order of questions and answers is randomized.

Do I have a time limit for practice tests?

Each test has a time limit and it is set as in the exam, 90 seconds per question. This gives a total of over 6 hours for questions in this course.

What result is required?

The required grade for each practice test is 70% correct answers.

Are the questions multiple choice?

In order to reflect the form of the interview as much as possible and to raise the level of difficulty, the questions are single and multiple choice.

Can I see my answers?

You can review all submitted responses and see which were correct and which were not.

Are the questions updated on a regular basis?

Yes.

Exam Syllabus

Computer Programming and Python Fundamentals

Understand fundamental terms and definitions
interpreting and the interpreter, compilation and the compiler, lexis, syntax and semantics
Understand Python’s logic and structure
keywords, instructions, indenting, comments
Introduce literals and variables into code and use different numeral systems
Boolean, integers, floating-point numbers, scientific notation, strings, binary, octal, decimal, and hexadecimal numeral system, variables, naming conventions, implementing PEP-8 recommendations
Choose operators and data types adequate to the problem
numeric operators: ** * / % // + –, string operators: * +, assignments and shortcut operators, operators: unary and binary, priorities and binding, bitwise operators: ~ & ^ | << >>, Boolean operators: not and or, Boolean expressions, relational operators ( == != > >= < <= ), the accuracy of floating-point numbers, type casting
Perform Input/Output console operations
print(), input() functions, sep= and end= keyword parameters, int() and float() functions

Conditional Blocks and Loops

Make decisions and branch the flow with the if instruction
conditional statements: if, if-else, if-elif, if-elif-else, multiple conditional statements, nesting conditional statements
Perform different types of iterations
the pass instruction, building loops with while, for, range(), and in; iterating through sequences, expanding loops with while-else and for-else, nesting loops and conditional statements, controlling loop execution with break and continue

Data Collections – Tuples, Dictionaries, Lists, and Strings

Collect and process data using lists
constructing vectors, indexing and slicing, the len() function, basic list methods (append(), insert(), index()) and functions (len(), sorted(), etc.), the del instruction; iterating through lists with the for loop, initializing loops; in and not in operators, list comprehensions; copying and cloning, lists in lists: matrices and cubes
Collect and process data using tuples
tuples: indexing, slicing, building, immutability; tuples vs. lists: similarities and differences, lists inside tuples and tuples inside lists
Collect and process data using dictionaries
dictionaries: building, indexing, adding and removing keys; iterating through dictionaries and their keys and values, checking the existence of keys; keys(), items() and values() methods
Operate with strings
constructing strings, indexing, slicing, immutability; escaping using the \ character; quotes and apostrophes inside strings, multi-line strings, basic string functions and methods

Functions and Exceptions

Decompose the code using functions
defining and invoking user-defined functions and generators; the return keyword, returning results, the None keyword, recursion
Organize interaction between the function and its environment
parameters vs. arguments; positional, keyword and mixed argument passing; default parameter values, name scopes, name hiding (shadowing), the global keyword
Python Built-In Exceptions Hierarchy
BaseException, Exception, SystemExit, KeyboardInterrupt, abstractive exceptions, ArithmeticError, LookupError along with IndexError and KeyError; TypeError and ValueError exceptions, the AssertError exception along with the assert keyword
Basics of Python Exception Handling
try-except, try-except Exception, ordering the except branches, propagating exceptions through function boundaries; delegating responsibility for handling exceptions

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:

Automation

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.

Web Development

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.

Artificial Intelligence

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.

Data Science

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.