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Coursera

Introduction to Programming Using Python

Packt via Coursera

Overview

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This course introduces the basics of programming using the Python language, a powerful and versatile tool in software development. Python’s simplicity makes it an excellent choice for beginners, offering a strong foundation for future programming tasks in various domains such as web development, data science, and automation. You will start by learning how to use basic data types, assign values to variables, and perform operations on them. As you progress, you’ll learn to work with lists, loops, conditional statements, and functions to create programs with more complex logic. Through hands-on practice, you will enhance your problem-solving and programming skills. What makes this course stand out is its practical approach. It integrates foundational programming concepts with real-world examples and projects, ensuring that you can apply your skills to solve real problems. This course is perfect for beginners with no prior programming experience. It’s also ideal for anyone looking to transition into programming from other technical backgrounds. The course requires no advanced knowledge, but a general familiarity with computer usage will be helpful. By the end of the course, you will have a solid understanding of Python’s core features and be able to build your own Python programs.

Syllabus

  • Getting Started with Python
    • In this module, we will introduce the Python programming language and cover its essential features. We’ll explore basic data types such as strings, integers, and booleans. You will also learn how to assign variables and apply basic operations, setting the foundation for building your Python programming skills.
  • Efficient Variable Assignment Techniques
    • In this module, we will dive into efficient variable assignment techniques, focusing on using multiple assignment statements. You will learn how to combine variable definition and assignment for related variables, making your code cleaner and more efficient.
  • Data Type Conversion in Python
    • In this module, we will explore how to convert data between different types in Python, such as converting strings to integers. We will also address common issues that arise during conversions and provide tips on when and why type conversions are necessary in your programs.
  • Introduction to List Creation
    • In this module, we will introduce the list data type, one of Python’s most important structures. You’ll learn how to create lists, use list indexing, and understand their use in handling collections of data effectively.
  • Techniques for Modifying Lists
    • In this module, we will continue exploring lists by demonstrating how to modify them. You will learn how to delete and change elements, as well as how to update sections of lists for more advanced data manipulation.
  • Sorting and Reversing List Elements
    • In this module, we will examine sorting and reversing lists in Python. You will learn how to arrange list elements in a specified order and reverse them, gaining an essential skill for manipulating data effectively.
  • List Slicing Techniques
    • In this module, we will explore list slicing, an essential technique for accessing sublists. You will learn how to use slice syntax to extract specific portions of a list and apply these techniques to real-world data retrieval problems.
  • Mastering Python Operators
    • In this module, we will examine various Python operators, focusing on mathematical and comparison operators. You will learn how to perform calculations and comparisons, building the foundation for complex logic in your programs.
  • Understanding Operator Precedence
    • In this module, we will delve into operator precedence and the order of operations in Python. You will learn how expressions are evaluated and how to structure your code for clarity and accuracy using parentheses when necessary.
  • Conditional Logic with If Statements
    • In this module, we will introduce if statements as a way to create conditional logic in your programs. You will learn how to handle different outcomes with else and elif statements to add decision-making capabilities to your code.
  • Advanced Conditional Expressions
    • In this module, we will extend the use of conditional logic by introducing compound conditional expressions. You will learn how to test multiple conditions using logical operators and refine your decision-making logic in Python.
  • Iterating with For Loops
    • In this module, we will introduce for loops as a tool to iterate over data collections. You will learn how to automate repetitive tasks and efficiently process elements in data structures such as lists and ranges.
  • Looping with While Constructs
    • In this module, we will explore while loops and how they differ from for loops. You will learn how to control loop execution with conditions and avoid common pitfalls such as infinite loops.
  • Complex Iterations with Nested For Loops
    • In this module, we will explore nested for loops, which allow you to handle more complex iteration tasks. You will learn how to write and optimize nested loops, understanding their performance considerations in larger programs.
  • File Reading Techniques in Python
    • In this module, we will focus on reading files in Python. You will learn how to open and read file contents using basic Python functions, along with the importance of managing file resources safely using context managers.
  • File Copying Methods
    • In this module, we will explore how to write to files and copy files in Python. You will understand the difference between various file modes and apply these techniques to automate file copying tasks.
  • Automating Email Merges
    • In this module, we will automate email merging to send personalized emails. You’ll learn how to work with lists and files to generate dynamic email content, which you can send to multiple recipients at once.
  • Handling Console Inputs and Outputs
    • In this module, we will look at reading inputs from the console and formatting outputs for user readability. You will gain hands-on experience in handling user data and displaying it in an organized and understandable manner.
  • Processing Command Line Arguments
    • In this module, we will explore handling command-line arguments in Python. You will learn how to build Python tools that accept and process input directly from the command line to enhance your programs' functionality.
  • Creating Custom Functions
    • In this module, we will dive into defining custom functions, one of the core features of Python. You will learn how to create functions to break your code into reusable components, making your code more efficient and maintainable.
  • Implementing Default Arguments in Functions
    • In this module, we will explore the concept of default arguments. You will learn how to provide default values for function parameters, making your functions more flexible and user-friendly.
  • Working with Keyword and Positional Arguments
    • In this module, we will discuss keyword and positional arguments in Python functions. You will learn how to use both types of arguments effectively and when each is the best choice for making your code clear and easy to understand.
  • Exception Handling in Python
    • In this module, we will cover exception handling in Python using try-except blocks. You will learn how to catch and manage runtime errors to keep your programs running smoothly, and when it's appropriate to let an error stop the program.
  • Exploring the Math and Random Modules
    • In this module, we will introduce Python’s math and random modules. You will learn how to use these standard libraries to handle complex mathematical operations and generate random data for your applications.
  • Managing Datetime and File Metadata
    • In this module, we will explore how to use Python’s datetime and os modules. You’ll learn to manage file metadata and perform time-based tasks in your programs, improving the utility and efficiency of your code.

Taught by

Packt - Course Instructors

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