Python Syllabus
Here’s a straight-to-the-point breakdown of what a python course covers from the basics to advanced concepts like data handling, automation and object-oriented programming. No fluff, just the essentials to get you coding fast.
Getting Started with Python Programming
Welcome to the getting started with Python progarmming section! Here, we'll cover the essential elements you need to kickstart your journey in Python programming. From syntax and keywords to comments, variables, and indentation, we'll explore the foundational concepts that underpin Python development.
- Learn Python Basics
- Syntax
- Keywords in Python
- Comments in Python
- Learn Python Variables
- Learn Python Data Types
- Indentation and why is it important in Python
Learn Python Input/Output
In this segment, we explore the fundamental aspects of handling input and output operations in Python, crucial for interacting with users and processing data effectively. From mastering the versatile print() function to exploring advanced formatting techniques and efficient methods for receiving user input, this section equips you with the necessary skills to harness Python's power in handling data streams seamlessly.
- Python print() function
- f-string in Python
- Print without newline in Python
- Python | end parameter in print()
- Python | sep parameter in print()
- Python | Output Formatting
- Taking Input in Python
- Taking Multiple Inputs from users in Python
Python Data Types
Python data types offers, enabling you to manipulate and manage data with precision and flexibility. Additionally, we'll delve into the dynamic world of data conversion with casting, and then move on to explore the versatile collections Python provides, including lists, tuples, sets, dictionaries, and arrays.
By the end of this section, you'll not only grasp the essence of Python's data types but also wield them proficiently to tackle a wide array of programming challenges with confidence.
- Strings
- Numbers
- Booleans
- Python List
- Python Tuples
- Python Sets
- Python Dictionary
- Python Arrays
- Type Casting
Python Operators
In this section of Python Operators we will cover from performing basic arithmetic operations to evaluating complex logical expressions. Here We'll delve into comparison operators for making decisions based on conditions, and then explore bitwise operators for low-level manipulation of binary data. Additionally, we'll unravel the intricacies of assignment operators for efficient variable assignment and updating. Lastly, we'll demystify membership and identity operators, such as in and is, enabling you to test for membership in collections and compare object identities with confidence.
- Arithmetic operators
- Comparison Operators
- Logical Operators
- Bitwise Operators
- Assignment Operators
- Membership & Identity Operators | Python "in", and "is" operator
Python Conditional Statement
Python Conditional statements are pivotal in programming, enabling dynamic decision-making and code branching. In this section of Python Tutorial, we'll explore Python's conditional logic, from basic if...else statements to nested conditions and the concise ternary operator. We'll also introduce the powerful match case statement, new in Python 3.10. By the end, you'll master these constructs, empowering you to write clear, efficient code that responds intelligently to various scenarios. Let's dive in and unlock the potential of Python's conditional statements.
- Python If else
- Nested if statement
- Python if-elif-else Ladder
- Python If Else on One Line
- Ternary Condition in Python
- Match Case Statement
Python Loops
Here, we'll explore Python loop constructs, including the for and while loops, along with essential loop control statements like break, continue, and pass. Additionally, we'll uncover the concise elegance of list and dictionary comprehensions for efficient data manipulation. By mastering these loop techniques, you'll streamline your code for improved readability and performance.
- For Loop
- While Loop
- Loop control statements (break, continue, pass)
- Python List Comprehension
- Python Dictionary Comprehension
Python Functions
Python Functions are the backbone of organized and efficient code in Python. Here, we'll explore their syntax, parameter handling, return values, and variable scope. From basic concepts to advanced techniques like closures and decorators. Along the way, we'll also introduce versatile functions like range(), and powerful tools such as *args and **kwargs for flexible parameter handling. Additionally, we'll delve into functional programming with map, filter, and lambda functions.
- Arguments and Return Values in Python Function
- Python Function Global and Local Scope Variables
- Use of pass Statement in Function
- Return statemen in Python Function
- Python range() function
- *args and **kwargs in Python Function
- Python closures
- Python ‘Self’ as Default Argument
- Decorators in Python
- Python closures
- Map Function
- Filter Function
- Reduce Function
- Lambda Function
Python OOPs Concepts
In this section of Python OPPs, we'll explore the core principles of object-oriented programming (OOP) in Python. From encapsulation to inheritance, polymorphism, abstract classes, and iterators, we'll cover the essential concepts that empower you to build modular, reusable, and scalable code.
Python Exception Handling
In this section of Python Tutorial, we'll explore Python Exception Handling that how Python deals with unexpected errors, enabling us to write robust and fault-tolerant code. We'll cover file handling, including reading from and writing to files.
File Handling
In this section, we will cover file handling, including reading from and writing to files.
- File Handling
- Different File Modes
- Read Files
- Write/Create Files
- OS Module
- pathlib Module
- Directory Management
- Quiz: File Handling
Python Database Handling
In this section we will learn how to access and work with MySQL and MongoDB databases
Python Packages or Libraries
The biggest strength of Python is a huge collection of Python Packages standard libraries which can be used for the following:
Data Science with Python
1. Foundational Libraries: These are the core libraries that form the base for all data science workflows. Start here to build a strong foundation.
2. Advanced Visualization and Statistical Tools: Once you’re comfortable with basic data handling and visualization, move to creating cleaner visuals and performing statistical analysis.
- Seaborn
- Statsmodel
3. Machine Learning Libraries: After mastering data manipulation and visualization, step into machine learning, starting with simpler models and moving to advanced ones.
4. Deep Learning Frameworks: If you’re interested in AI and deep learning, these libraries will allow you to build and train neural networks.
To learn more, you can refer to Python for Data Science.
Web Development with Python
1. Core Web Frameworks (Backend Development with Python): These are the primary tools for building Python-based web applications.
2. Database Integration: Learn how to connect Python web frameworks to databases for storing and retrieving data.
3. Front-End and Backend Integration: Learn how to connect Python backends with front-end technologies to create dynamic, full-stack web applications.
4. API Development: Learn to build APIs (Application Programming Interfaces) for connecting your backend with front-end apps or other services.
To learn more, you can refer to Python for Web Development.
Python Quizzes
Python quiz page covers topics including variables, data types and how to manage output effectively. You'll explre operators and control flow to structure our code, along with loops (for and while) for repetitive tasks. Additionally, you'll gain knowledge with Python data structures such as lists, tuples, dictionaries and sets.
This Python tutorial is updated based on latest Python 3.13.1 version.
