Python Essentials Training

Python Essentials Training

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Course Length: 5 days
Delivery Methods: Multiple delivery options
Course Overview

Learn Python programming quickly! This hands-on class gives you practical experience building applications using Python. You will learn to use Python's built-in modules, structure your code efficiently, manage files, handle exceptions, create reusable code, test and debug code, access data, and much more. Whether you are a new programmer or an existing programmer who is new to Python, this class gives you a solid foundation in Python programming.

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Course Benefits
  • Write Python scripts with confidence.
  • Code with ease using Python Standard Library script modules.
  • Complete math operations with Python.
  • Access data in a Python program using string indexing and slicing strings.
  • Leverage data structures like sequences, dictionaries, and sets.
  • Use flow control tools to manage the execution of your program.
  • Strengthen your code with exception handling, testing, and debugging.
  • Quickly match, locate, and manage text using regular expressions.
  • Handle date and time with confidence.
  • Read, write, and edit files using Python.
  • Create reusable code to save time later.
  • Work with various data sources.
  • Use Python's object-oriented features to create flexible code that is easier to maintain.
Available Delivery Methods
Public Class
Public expert-led online training from the convenience of your home, office or anywhere with an internet connection. Guaranteed to run .
Private Class
Private classes are delivered for groups at your offices or a location of your choice.
Course Outline
  1. Python Basics
    1. Getting Familiar with the Terminal
    2. Running Python
    3. Running a Python File
    4. Exercise: Hello, world!
    5. Literals
    6. Exercise: Exploring Types
    7. Variables
    8. Exercise: A Simple Python Script
    9. Constants and Deleting Variables
    10. Writing a Python Module
    11. print() Function
    12. Collecting User Input
    13. Exercise: Hello, You!
    14. Reading from and Writing to Files
    15. Exercise: Working with Files
  2. Functions and Modules
    1. Defining Functions
    2. Variable Scope
    3. Global Variables
    4. Function Parameters
    5. Exercise: A Function with Parameters
    6. Returning Values
    7. Exercise: Parameters with Default Values
    8. Returning Values
    9. Importing Modules
    10. Methods vs. Functions
  3. Math
    1. Arithmetic Operators
    2. Exercise: Floor and Modulus
    3. Assignment Operators
    4. Precedence of Operations
    5. Built-in Math Functions
    6. The math Module
    7. The random Module
    8. Exercise: How Many Pizzas Do We Need?
    9. Exercise: Dice Rolling
  4. Python Strings
    1. Quotation Marks and Special Characters
    2. String Indexing
    3. Exercise: Indexing Strings
    4. Slicing Strings
    5. Exercise: Slicing Strings
    6. Concatenation and Repetition
    7. Exercise: Repetition
    8. Combining Concatenation and Repetition
    9. Python Strings are Immutable
    10. Common String Methods
    11. String Formatting
    12. Exercise: Playing with Formatting
    13. Formatted String Literals (f-strings) (introduced in Python 3.6)
    14. Built-in String Functions
    15. Exercise: Outputting Tab-delimited Text
  5. Iterables: Sequences, Dictionaries, and Sets
    1. Definitions
    2. Sequences
    3. Lists
    4. Sequences and Random
    5. Exercise: Remove and Return Random Element
    6. Tuples
    7. Ranges
    8. Converting Sequences to Lists
    9. Indexing
    10. Exercise: Simple Rock, Paper, Scissors Game
    11. Slicing
    12. Exercise: Slicing Sequences
    13. min(), max(), and sum()
    14. Converting between Sequences and Strings
    15. Unpacking Sequences
    16. Dictionaries
    17. The len() Function
    18. Exercise: Creating a Dictionary from User Input
    19. Sets
    20. *args and **kwargs
  6. Virtual Environments, Packages, and pip
    1. Exercise: Creating, Activiting, Deactivating, and Deleting a Virtual Environment
    2. Packages with pip
    3. Exercise: Working with a Virtual Environment
  7. Flow Control
    1. Conditional Statements
    2. Compound Conditions
    3. The is and is not Operators
    4. all() and any() and the Ternary Operator
    5. In Between
    6. Loops in Python
    7. Exercise: All True and Any True
    8. break and continue
    9. Looping through Lines in a File
    10. Exercise: Word Guessing Game
    11. The else Clause in Loops
    12. Exercise: for...else
    13. The enumerate() Function
    14. Generators
    15. List Comprehensions
  8. Exception Handling
    1. Exception Basics
    2. Generic Exceptions
    3. Exercise: Raising Exceptions
    4. The else and finally Clauses
    5. Using Exceptions for Flow Control
    6. Exercise: Running Sum
    7. Raising Your Own Exceptions
  9. Python Dates and Times
    1. Understanding Time
    2. The time Module
    3. Time Structures
    4. Times as Strings
    5. Time and Formatted Strings
    6. Pausing Execution with time.sleep()
    7. The datetime Module
    8. datetime.datetime Objects
    9. Exercise: What Color Pants Should I Wear?
    10. datetime.timedelta Objects
    11. Exercise: Report on Departure Times
  10. File Processing
    1. Opening Files
    2. Exercise: Finding Text in a File
    3. Writing to Files
    4. Exercise: Writing to Files
    5. Exercise: List Creator
    6. The os Module
    7. os.walk()
    8. The os.path Module
    9. A Better Way to Open Files
    10. Exercise: Comparing Lists
  11. PEP8 and Pylint
    1. PEP8
    2. Pylint
  12. Advanced Python Concepts
    1. Lambda Functions
    2. Advanced List Comprehensions
    3. Exercise: Rolling Five Dice
    4. Collections Module
    5. Exercise: Creating a defaultdict
    6. Counters
    7. Exercise: Creating a Counter
    8. Mapping and Filtering
    9. Mutable and Immutable Built-in Objects
    10. Sorting
    11. Exercise: Converting list.sort() to sorted(iterable)
    12. Sorting Sequences of Sequences
    13. Creating a Dictionary from Two Sequences
    14. Unpacking Sequences in Function Calls
    15. Exercise: Converting a String to a datetime.date Object
    16. Modules and Packages
  13. Regular Expressions
    1. Regular Expression Tester
    2. Regular Expression Syntax
    3. Python's Handling of Regular Expressions
    4. Exercise: Green Glass Door
  14. Working with Data
    1. Virtual Environment
    2. Relational Databases
    3. Passing Parameters
    4. SQLite
    5. Exercise: Querying a SQLite Database
    6. SQLite Database in Memory
    7. Exercise: Inserting File Data into a Database
    8. Drivers for Other Databases
    9. CSV
    10. Exercise: Finding Data in a CSV File
    11. Creating a New CSV File
    12. Exercise: Creating a CSV with DictWriter
    13. Getting Data from the Web
    14. Exercise: HTML Scraping
    15. XML
    16. JSON
    17. Exercise: JSON Home Runs
  15. Testing and Debugging
    1. Testing for Performance
    2. Exercise: Comparing Times to Execute
    3. The unittest Module
    4. Exercise: Fixing Functions
    5. Special unittest.TestCase Methods
  16. Classes and Objects
    1. Attributes
    2. Behaviors
    3. Classes vs. Objects
    4. Attributes and Methods
    5. Exercise: Adding a roll() Method to Die
    6. Private Attributes
    7. Properties
    8. Exercise: Properties
    9. Objects that Track their Own History
    10. Documenting Classes
    11. Exercise: Documenting the Die Class
    12. Inheritance
    13. Exercise: Extending the Die Class
    14. Extending a Class Method
    15. Exercise: Extending the roll() Method
    16. Static Methods
    17. Class Attributes and Methods
    18. Abstract Classes and Methods
    19. Understanding Decorators
Class Materials

Each student will receive a comprehensive set of materials, including course notes and all the class examples.

Class Prerequisites

Experience in the following would be useful for this Python class:

  • Some programming experience.
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