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

Introduction to PCAP - Certified Associate in Python Programming (PCAP-31-02) Exam

PCAP - Certified Python Programming Associate (PCAP-31-02) qualification is a technical certificate that tests the ability to perform coding tasks in the Python language related to the fundamentals of programming and the basic notions and techniques used in object-oriented programming.

PCAP - Certified Associate in Python Programming (PCAP-31-02) certification indicates that the person is familiar with general computer programming concepts such as conditional execution, loops, syntax of the Python programming language, semantics, and runtime environment, as well as general coding and object-oriented programming techniques.

Becoming certified by PCAP ensures that you are fully familiar with all the primary means offered by Python 3 to enable you to begin your own studies and open up a path to the career of the developer.

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Topics of PCAP - Certified Associate in Python Programming (PCAP-31-02) Exam

The syllabus for the PCAP - Certified Associate in Python Programming (PCAP-31-02) examination is listed below in detail of each section and their topics:

1. Control and Evaluations (25%)

Objectives covered by this section:

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

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
• 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
• lists in lists: matrices and cubes
• tuples: indexing, slicing, building, immutability

3. Functions and Modules (25%)

Objectives covered by this section:

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

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

Objectives covered by this section:

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

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