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PCAP - Certified Associate in Python Programming (PCAP-31-03) Certification Path

The Certified Associate in Python Programming Certification includes only one PCAP-31-03 exam. There are no official prerequisites for the exam, but the applicants are recommended to have little prior knowledge of any programming language, should have very basic knowledge of Mathematics, and have attempted the PCAP-31-03 practice exams.

Who should take the PCAP - Certified Associate in Python Programming (PCAP-31-03) Exam

The qualification for the PCAP - Certified Associate in Python Programming (PCAP-31-03) exam is a globally recognized validation that recognizes individuals who receive it as having Python programming skills. If candidates want major changes in their career advancement, they need better knowledge, skills, and talents. Evidence of this advanced knowledge and ability is presented by the PCAP - Certified Associate in Python Programming (PCAP-31-03) Exam certification. If an applicant has the knowledge and skills needed to pass the PCAP - Certified Associate in Python Programming (PCAP-31-03) exam, Python Programming Language Syntax, Semantics, Runtime Setting, General Coding Techniques, and Object-Oriented Programming, then he can take this examination.

The following students can take the PCAP - Certified Associate in Python Programming (PCAP-31-03) Exam. The ability to use a personal computer and very basic mathematical skills are the only preliminary prerequisite:

• Students with little to no previous programming awareness
• High school students
• Students at universities
• Anyone involved in computer training
• Vocational school students

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Topics of PCAP - Certified Associate in Python Programming (PCAP-31-03) Exam

The syllabus for the PCAP-31-03 exam dumps is listed below in detail of each section and their topics:

1. Control and Evaluations (25%)

Objectives covered by this section:

• bitwise operators: ~ & ^ | « »
• building loops: while, for, range(), in, iterating through sequences
• formatting print() output with end= and sep= arguments
• expanding loops: while-else, for-else, nesting loops, and conditional statements
• conditional statements: if, if-else, if-elif, if-elif-else
• literals: Boolean, integer, floating-point numbers, scientific notation, strings
• string operators: * +
• accuracy of floating-point numbers
• the pass instruction
• relational operators (== != > >= < <= ), building complex Boolean expressions
• controlling loop execution: break, continue
• numeric operators: * / % // + -
• operators: unary and binary, priorities and binding
• assignments and shortcut operators
• simple strings: constructing, assigning, indexing, slicing comparing, immutability
• Boolean operators: not and or
• simple lists: constructing vectors, indexing, and slicing, the len() function
• basic concepts: interpreting and the interpreter, compilation and the compiler, language elements, lexis, syntax and semantics, Python keywords, instructions, indenting
• basic input and output: input(), print(), int(), float(), str() functions

2. Data Aggregates (25%)

Objectives covered by this section:

• dictionaries: building, indexing, adding and removing keys, iterating through dictionaries as well as their keys and values, checking key existence, keys(), items(), and values() methods
• tuples: indexing, slicing, building, immutability
• lists in lists: matrices and cubes
• lists in detail: indexing, slicing, basic methods (append(), insert(), index()) and functions (len(), sorted(), etc.), del instruction, iterating lists with the for loop, initializing, in and not in operators, list comprehension, copying and cloning
• strings in detail: ASCII, UNICODE, UTF-8, immutability, escaping using the \ character, quotes and apostrophes inside strings, multiline strings, copying vs. cloning, advanced slicing, string vs. string, string vs. non-string, basic string methods (upper(), lower(), isxxx(), capitalize(), split(), join(), etc.) and functions (len(), chr(), ord()), escape characters
• tuples vs. lists: similarities and differences, lists inside tuples and tuples inside lists

3. Functions and Modules (25%)

Objectives covered by this section:

• pyc file creation and usage
• import directives, qualifying entities with module names, initializing modules
• name scopes, name hiding (shadowing), the global keyword
• defining and invoking your functions and generators
• Python hashbangs, using multiline strings as module documentation
• converting generator objects into lists using the list() function
• map(), filter(), reduce(), reversed(), sorted() functions and the sort() method
• hiding module entities
• writing and using modules, the name variable
• constructing and distributing packages, packages vs. directories, the role of the init.py file
• lambda functions, defining and using
• the if operator
• parameters vs. arguments, positional keyword and mixed argument passing, default parameter values
• return and yield keywords, returning results, the None keyword, recursion

4. Classes, Objects, and Exceptions (25%)

Objectives covered by this section:

• inheritance and overriding, finding class/object components
• writing and using constructors
• defining your classes, superclasses, subclasses, inheritance, searching for missing class components, creating objects
• the role of the str method
• single inheritance vs. multiple inheritances
• exceptions hierarchy, assigning more than one exception to one except branch
• adding your exceptions to an existing hierarchy
• the anatomy of an exception object
• introspection: dict, name, module, bases properties, examining class/object structure
• the init method
• input/output basics: opening files with the open() function, stream objects, binary vs. text files, newline character translation, reading and writing files, byte array objects
• assertions
• name mangling
• read(), readinto(), readline(), write(), close() methods
• the try-except-else-finally block, the raise statement, the except-as variant
• using predefined exceptions and defining your ones
• class methods: defining and using the self-parameter meaning and usage
• class attributes: class variables and instance variables, defining, adding, and removing attributes, explicit constructor invocation
• invoking methods, passing and using the self-argument/parameter
• hasattr(), type(), issubclass(), isinstance(), super() functions

Python Institute PCAP-31-03 Exam Syllabus Topics:

Reference: https://pythoninstitute.org/certification/pcap-certification-associate/pcap-exam-syllabus/

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