WA3016
Introduction to Python 3 Programming (Practical Programming for Beginners) Training
Whether you’re focusing on machine learning, data engineering, systems administration, or another field, it's likely you're going to need to understand the fundamentals of Python programming. In our intensive 3-day Python course, we will cover the essential skills of this versatile programming language through theoretical concepts and hands-on labs.
Course Details
Duration
3 days
Target Audience
- Developers
- Data Analysts
Skills Gained
- Understand the foundational principles of Python syntax, data types, and expressions
- Explore the various tools and environments for running Python code, including shells, REPLs, and Jupyter notebooks
- Gain proficiency in defining and manipulating variables, control flow statements, and data structures like lists, dictionaries, and sets
- Build functions with confidence leveraging techniques like parameter passing, recursion, and higher-order functions
- Access and implement functionalities from essential Python modules for file handling, random numbers, regular expressions, and more
- Apply your Python skills to practical exercises and lab challenges, tackling real-world scenarios with code
- Foster a creative problem-solving mindset, leveraging Python as a powerful tool for automation, data analysis, and building impactful applications
Course Outline
- Python 3 Introduction
- What is Python?
- Python Documentation
- Where Can I Use Python?
- Which version of Python am I running?
- Running Python Programs
- Python Shell
- Dev Tools and REPLs
- IPython
- Jupyter
- Hands-On Exercise
- The Anaconda Python Distribution
- Python Variables and Types
- Variables and Types
- More on Variables
- Assigning Multiple Values to Multiple Variables
- More on Types
- Variable Scopes
- The Layout of Python Programs
- Comments and Triple-Delimited String Literals
- Sample Python Code
- PEP8
- Getting Help on Python Objects
- Null (None)
- Strings
- Finding Index of a Substring
- String Splitting
- Raw String Literals
- String Formatting and Interpolation
- String Public Method Names
- The Boolean Type
- Boolean Operators
- Relational Operators
- Numbers
- "Easy Numbers"
- Looking Up the Runtime Type of a Variable
- Divisions
- Assignment-with-Operation
- Hands-On Exercise
- Dates and Times
- Hands-On Exercise
- Control Statements and Data Collections
- Control Flow with The if-elif-else Triad
- An if-elif-else Example
- Conditional Expressions (a.k.a. Ternary Operator)
- The While-Break-Continue Triad
- The for Loop
- The range() Function
- Examples of Using range()
- The try-except-finally Construct
- Hands-On Exercise
- The assert Expression
- Lists
- Main List Methods
- List Comprehension
- Zipping Lists
- Enumerate
- Hands-On Exercise
- Dictionaries
- Working with Dictionaries
- Other Dictionary Methods
- Sets
- Set Methods
- Set Operations
- Set Operations Examples
- Finding Unique Elements in a List
- Common Collection Functions and Operators
- Hands-On Exercise
- Tuples
- Unpacking Tuples
- Hands-On Exercise
- Functions and Modules
- Built-in Functions
- Functions
- The "Call by Sharing" Parameter Passing
- Global and Local Variable Scopes
- Default Parameters
- Named Parameters
- Dealing with Arbitrary Number of Parameters
- Keyword Function Parameters
- Hands-On Exercise
- What is Functional Programming (FP)?
- Concept: Pure Functions
- Concept: Recursion
- Concept: Higher-Order Functions
- Lambda Functions in Python
- Examples of Using Lambdas
- Lambdas in the Sorted Function
- Hands-On Exercise
- Python Modules
- Importing Modules
- Installing Modules
- Listing Methods in a Module
- Creating Your Own Modules
- Creating a Module's Entry Point
- Working with File I/O and Useful Modules
- Reading Command-Line Parameters
- Hands-On Exercise (N/A in DCC)
- Working with Files
- Reading and Writing Files
- Hands-On Exercise
- Hands-On Exercise
- Random Numbers
- Hands-On Exercise
- Regular Expressions
- The re Object Methods
- Using Regular Expressions Examples
- Lab Exercises
- Lab 1. Understanding Jupyter Notebooks
- Lab 2. Python Variables
- Lab 3. Dates and Times
- Lab 4. The if, for, and try Constructs
- Lab 5. Understanding Lists
- Lab 6. Dictionaries
- Lab 7. Sets
- Lab 8. Tuples
- Lab 9. Functions
- Lab 10. Functional Programming
- Lab 11. Reading Command-Line Parameters
- Lab 12. File I/O
- Lab 13. Using HTTP and JSON
- Lab 14. Random Numbers
- Lab 15. Regular Expressions
Upcoming Course Dates
