CERTIFICATE IN PYTHON PROGRAMING ( S-C-PYT )

Certificate in Python Programming

Master Python & Build Real-World Applications!

Course Overview

This course provides a comprehensive introduction to Python, one of the most popular and versatile programming languages today. Whether you are a beginner or an experienced programmer, this course will teach you core programming concepts, automation techniques, data handling, and application development.

By the end of this course, you will have the skills to write clean and efficient Python code for web development, data analysis, automation, and artificial intelligence applications.

Course Duration

• Duration: 6 Months (Self-Paced or Instructor-Led)

Who Should Enroll?

This course is ideal for:

 Beginners looking to start a career in programming
 Students & professionals aiming to master Python for data science or AI
 Developers transitioning from other programming languages
 IT professionals & business analysts wanting to automate tasks

What You’ll Learn

 Introduction to Python & Setting Up Development Environment
 Python Syntax, Variables & Data Types
 Control Structures (Loops, Conditions, Functions)
 Object-Oriented Programming (OOP) in Python
 File Handling & Database Interaction
 Web Scraping & Data Analysis with Pandas & NumPy
 Introduction to Web Development & APIs with Flask/Django
 Basics of Machine Learning with Python

Certification

Upon successful completion, students will receive a Certificate in Python Programming, validating their expertise in Python for software development, automation, and data analysis.

Python Programming refers to writing code in the Python programming language. Python is one of the most popular and versatile programming languages due to its simplicity, readability, and wide range of applications, from web development to data science, machine learning, automation, and much more.

Key Features of Python:

1. Easy to Learn and Read: Python’s syntax is clear and intuitive, making it beginner-friendly. It focuses on readability and simplicity, allowing developers to express concepts in fewer lines of code.
2. Interpreted Language: Python is an interpreted language, meaning code is executed line by line, rather than being compiled.
3. Object-Oriented: Python supports object-oriented programming, which means it allows the use of classes and objects to structure code in a modular and reusable manner.
4. Extensive Libraries: Python has a rich ecosystem of libraries and frameworks, which makes it great for a wide range of applications like web development (e.g., Django, Flask), data analysis (e.g., Pandas, NumPy), machine learning (e.g., TensorFlow, scikit-learn), and more.

Basics of Python Programming:

1. Installing Python:

   • To start writing Python code, you need to install the Python interpreter on your system. You can download it from the official Python website: https://www.python.org/downloads/.

2. Python Syntax:

   1. Python syntax is simple and similar to human-readable English.
   2. Python code uses indentation (whitespace) instead of curly braces {} to define blocks of code, which makes it easier to read and maintain.

Core Concepts in Python Programming:

1. Variables and Data Types:

   • Python is dynamically typed, meaning you don't need to declare the data type of a variable explicitly.
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   name = "Alice" # String age = 25 # Integer height = 5.6 # Float is_student = True # Boolean

2. Control Flow (Conditionals and Loops):

   • if/elif/else Statements: Used for decision-making.
   • while Loops: Repeats a block of code as long as a condition is True.
   • for Loops: Iterates over a sequence (like a list, tuple, or string).

   Example of a for loop:

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   for i in range(1, 6): print(i)

3. Functions:

   • Functions allow you to organize your code into reusable blocks. They are defined using the def keyword.

   Example:

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   def greet(name): print(f"Hello, {name}!") greet("Alice") # Output: Hello, Alice!

4. Lists and Collections:

   • Lists are ordered, mutable collections of elements.

   Example:

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   fruits = ["apple", "banana", "cherry"] fruits.append("orange") # Adding an item to the list
   • Tuples are immutable collections, useful for fixed data.
   • Dictionaries are unordered collections of key-value pairs.
   • Sets are unordered collections that don't allow duplicate items.

5. Exception Handling:

   • Python provides a way to handle errors gracefully using try, except, and finally.

   Example:

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   try: x = 10 / 0 except ZeroDivisionError: print("You can't divide by zero!")

6. Object-Oriented Programming (OOP):

   • Python supports OOP concepts like classes, objects, inheritance, and polymorphism.

   Example of a class in Python:

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   class Car: def __init__(self, brand, model): self.brand = brand self.model = model def display(self): print(f"Car: {self.brand} {self.model}") my_car = Car("Toyota", "Corolla") my_car.display() # Output: Car: Toyota Corolla

7. File Handling:

   • Python provides simple methods for reading and writing files.

   Example of writing to a file:

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   with open("example.txt", "w") as file: file.write("Hello, Python!")

   Example of reading from a file:

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   with open("example.txt", "r") as file: content = file.read() print(content)

8. Libraries and Modules:

   • Python allows you to import built-in and external libraries (modules) to extend its functionality. For example:
     • math for mathematical operations
     • random for generating random numbers
     • datetime for handling date and time
     • pandas, NumPy for data manipulation

   Example of using the math module:

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   import math print(math.sqrt(16)) # Output: 4.0

Advanced Python Concepts:

1. List Comprehensions:

   • A concise way to create lists by applying an expression to each element in an existing list.

   Example:

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   numbers = [1, 2, 3, 4, 5] squared = [x**2 for x in numbers] # Output: [1, 4, 9, 16, 25]

2. Lambda Functions:

   • Anonymous functions that can be used to perform simple operations.

   Example:

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   add = lambda x, y: x + y print(add(5, 3)) # Output: 8

3. Generators:

   • Functions that allow you to iterate over a sequence of values lazily, using the yield keyword.

   Example:

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   def count_up_to(max): count = 1 while count <= max: yield count count += 1 for number in count_up_to(5): print(number)

4. Decorators:

   • Functions that modify the behavior of other functions. They are used for wrapping another function to add additional functionality.

   Example:

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   def decorator_function(func): def wrapper(): print("Before function call") func() print("After function call") return wrapper @decorator_function def greet(): print("Hello!") greet() # Output: Before function call, Hello!, After function call

Python Libraries for Specific Tasks:

• Data Science:

  1. NumPy: For numerical operations and working with arrays.
  2. Pandas: For data manipulation and analysis.
  3. Matplotlib and Seaborn: For data visualization.
  4. Scikit-learn: For machine learning and statistical modeling.
  5. TensorFlow and Keras: For deep learning.

• Web Development:

  1. Flask and Django: Web frameworks for building web applications.
  2. Requests: For making HTTP requests.
  3. BeautifulSoup: For web scraping.

• Automation and Scripting:

  1. Selenium: For web automation and testing.
  2. PyAutoGUI: For automating keyboard and mouse operations.

How to Get Started with Python Programming:

1. Install Python: Download and install Python from python.org.
2. Set up a Development Environment:
   • Use an IDE (Integrated Development Environment) like PyCharm, Visual Studio Code, or Jupyter Notebooks (for data science) to write Python code.
3. Practice:
   • Start solving problems on platforms like HackerRank, LeetCode, or CodeWars to improve your coding skills.
4. Build Projects:
   • Apply your knowledge by building small projects like a To-Do List app, Web Scraper, or a Simple Calculator to gain hands-on experience.

Conclusion:

Python is an extremely versatile programming language that’s used in various fields like web development, data science, automation, artificial intelligence, and more. Its simplicity and ease of use make it a great choice for beginners while still being powerful enough for advanced developers. Whether you're just getting started or looking to advance your skills, Python has a rich set of resources and libraries to help you achieve your goals.

Start Coding in Python – Enroll Today!