What you will learn
Introduction to Python
Certified Entry-Level Python Programmer (PCEP) Topics Overview
Data Analytics tool for Python
Algorithms
Description
Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of its features support functional programming and aspect-oriented programming (including by metaprogramming[58] and metaobjects (magic methods)) PCEP – Certified Entry-Level Python Programmer Certification: Exam Syllabus
Exam block #1: Basic Concepts (17%)
Objectives covered by the block (5 exam items)
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fundamental concepts: interpreting and the interpreter, compilation and the compiler, language elements, lexis, syntax and semantics, Python keywords, instructions, indenting
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literals: Boolean, integer, floating-point numbers, scientific notation, strings
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comments
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the print() function
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the input() function
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numeral systems (binary, octal, decimal, hexadecimal)
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numeric operators: ** * / % // + –
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string operators: * +
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assignments and shortcut operators
Exam block #2: Data Types, Evaluations, and Basic I/O Operations (20%)
Objectives covered by the block (6 exam items)
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operators: unary and binary, priorities and binding
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bitwise operators: ~ & ^ | << >>
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Boolean operators: not and or
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Boolean expressions
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relational operators ( == != > >= < <= ), building complex Boolean expressions
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accuracy of floating-point numbers
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basic input and output operations using the input(), print(), int(), float(), str(), len() functions
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formatting print() output with end= and sep= arguments
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type casting
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basic calculations
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simple strings: constructing, assigning, indexing, immutability
Exam block #3: Control Flow – loops and conditional blocks (20%)
Objectives covered by the block (6 exam items)
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conditional statements: if, if-else, if-elif, if-elif-else
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multiple conditional statements
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the pass instruction
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building loops: while, for, range(), in
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iterating through sequences
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expanding loops: while-else, for-else
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nesting loops and conditional statements
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controlling loop execution: break, continue
Exam block #4: Data Collections – Lists, Tuples, and Dictionaries (23%)
Objectives covered by the block (7 exam items)
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simple lists: constructing vectors, indexing and slicing, the len() function
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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
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lists in lists: matrices and cubes
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tuples: indexing, slicing, building, immutability
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tuples vs. lists: similarities and differences, lists inside tuples and tuples inside lists
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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
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strings in detail: escaping using the character, quotes and apostrophes inside strings, multi-line strings, basic string functions.
Exam block #5: Functions (20%)
Objectives covered by the block (6 exam items)
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defining and invoking your own functions and generators
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return and yield keywords, returning results,
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the None keyword,
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recursion
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parameters vs. arguments,
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positional keyword and mixed argument passing,
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default parameter values
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converting generator objects into lists using the list() function
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name scopes, name hiding (shadowing), the global keyword
Content
Introduction
Introduction to data analytics with Python
Algorithms and Data Structures
Python Documentation and Libraries