📚 Looks Good to Me (2023)
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📚 Introduction to Compiler Design (2024)
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📚 Programming Puzzles (2024)
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📚 Code Factory (2024)
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Ace the Python Coding Interview
Link: https://www.educative.io/path/ace-python-coding-interview?aff=KQEy
#python #coding #interview
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Python is a high level, dynamically typed, and object-oriented language that is easy to read and write. It has a large, supportive community of developers that contribute to its development and support. Python's simplicity, flexibility, and versatility make it a perfect choice in the industry. This Skill Path will take you through all that you need to know to crack your Python interviews with confidence. You’ll cover everything from data structures to object-oriented design and concurrency. You will also get to know the essential patterns behind popular coding interview questions. By the time you’re done, your skills will be polished to ace the interview of any company.
Link: https://www.educative.io/path/ace-python-coding-interview?aff=KQEy
#python #coding #interview
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📚 Numbers and Functions (2024)
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📚 Begin to Code (2024)
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📚 Coding Examples from Simple to Complex (2024)
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IP Address Information using Python
Is it useful to you❓
📂 Tags: #coding #Python
https://t.iss.one/DataScience4⭐️
Is it useful to you
https://t.iss.one/DataScience4
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Find your country on a Map using Python
Is it useful to you❓
📂 Tags: #coding #Python
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Is it useful to you
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Forwarded from Python | Machine Learning | Coding | R
#Python #LearnPython #Coding #JupyterNotebooks #OpenSource #FreeLearning #DataScience #Programming #TechEducation #AllenDowney #ThinkPython
- Learn by Doing: Perfect for beginners and coders upgrading to Python 3! Hands-on examples, exercises, and projects.
- Jupyter Notebook Edition: Entire book redesigned as interactive notebooks! Run code, visualize results, and experiment live.
- Free & Open Source: Licensed under CC BY-NC-SA—download, share, and contribute!
- From a Pro: Authored by Allen Downey, computer science professor and creator of the legendary *Think Series* (*Think Stats*, *Think Bayes*).
- Clear & Engaging: Simplifies complex concepts with humor and real-world analogies.
- Updated for modern Python 3 practices.
- Fully integrated Jupyter notebooks for interactive learning.
- Expanded exercises and case studies.
- New programmers starting with Python.
- Educators teaching coding or data science.
- Data enthusiasts who want to code smarter.
#Python3 #CodeForFree #InteractiveLearning — Unlock Python’s power, one notebook at a time!
https://t.iss.one/CodeProgrammer
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Forwarded from Python | Machine Learning | Coding | R
80 Python Interview Questions.pdf
410.4 KB
- Covers frequently asked questions in Python interviews
#Python #DataScience #Programming #InterviewPrep #Coding #PythonInterview #TechInterview #DataScientist #PythonProgramming #LearnPython #CodeNewbie #CareerGrowth #TechJobs #PythonCode #PythonTips
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Auto copy paste using Python
#Python #Programming #Coding #DataScience #MachineLearning #AI #WebDevelopment #Automation #OpenSource #TechSkills
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#Python #Programming #Coding #DataScience #MachineLearning #AI #WebDevelopment #Automation #OpenSource #TechSkills
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Working With Linked Lists in Python (Course)
Enroll Free: https://realpython.com/videos/working-linked-lists-overview/
Enroll Free: https://realpython.com/videos/working-linked-lists-overview/
#python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience
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Pagination in Django
https://testdriven.io/blog/django-pagination/
Looks at how to add pagination to a Django project.
https://testdriven.io/blog/django-pagination/
Looks at how to add pagination to a Django project.
#python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience #django
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Django Features and Libraries - course
Exploring Django Features and Libraries
The "Django Features and Libraries" course is designed to help learners deepen their understanding of Django by exploring its advanced features and built-in libraries. Django is a high-level Python web framework that promotes rapid development and clean, pragmatic design. This course provides hands-on experience in leveraging Django’s powerful tools to build scalable, efficient, and secure web applications.
Enroll Free: https://www.coursera.org/learn/django-features-libraries
Exploring Django Features and Libraries
The "Django Features and Libraries" course is designed to help learners deepen their understanding of Django by exploring its advanced features and built-in libraries. Django is a high-level Python web framework that promotes rapid development and clean, pragmatic design. This course provides hands-on experience in leveraging Django’s powerful tools to build scalable, efficient, and secure web applications.
Enroll Free: https://www.coursera.org/learn/django-features-libraries
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Data Management With Python, SQLite, and SQLAlchemy
In this tutorial, you’ll learn how to use:
1⃣ Flat files for data storage
🔢 SQL to improve access to persistent data
🔢 SQLite for data storage
🔢 SQLAlchemy to work with data as Python objects
Enroll Free: https://realpython.com/python-sqlite-sqlalchemy/
In this tutorial, you’ll learn how to use:
Enroll Free: https://realpython.com/python-sqlite-sqlalchemy/
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The Best Python Cheat Sheet.pdf
435.5 KB
Unlock Python mastery with The Best Python Cheat Sheet Perfect for coders and data scientists, this comprehensive guide covers Python 3.8+ syntax, built-in functions, flow control, lists, dictionaries, generators, decorators, regex, OOP, error handling, and more.
Includes ready-to-use code snippets, operator precedence rules, context managers, match-case patterns, and advanced topics like scope management and execution environments.
Ideal for quick reference, interviews, or daily #coding tasks.
Download now to boost your #Python #skills!
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Learning Common Algorithms with Python
• This lesson covers fundamental algorithms implemented in Python. Understanding these concepts is crucial for building efficient software. We will explore searching, sorting, and recursion.
• Linear Search: This is the simplest search algorithm. It sequentially checks each element of the list until a match is found or the whole list has been searched. Its time complexity is O(n).
• Binary Search: A much more efficient search algorithm, but it requires the list to be sorted first. It works by repeatedly dividing the search interval in half. Its time complexity is O(log n).
• Bubble Sort: A simple sorting algorithm that repeatedly steps through the list, compares adjacent elements and swaps them if they are in the wrong order. The process is repeated until the list is sorted. Its time complexity is O(n^2).
• Recursion (Factorial): Recursion is a method where a function calls itself to solve a problem. A classic example is calculating the factorial of a number (
#Python #Algorithms #DataStructures #Coding #Programming #LearnToCode
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By: @DataScience4 ✨
• This lesson covers fundamental algorithms implemented in Python. Understanding these concepts is crucial for building efficient software. We will explore searching, sorting, and recursion.
• Linear Search: This is the simplest search algorithm. It sequentially checks each element of the list until a match is found or the whole list has been searched. Its time complexity is O(n).
def linear_search(data, target):
for i in range(len(data)):
if data[i] == target:
return i # Return the index of the found element
return -1 # Return -1 if the element is not found
# Example
my_list = [4, 2, 7, 1, 9, 5]
print(f"Linear Search: Element 7 found at index {linear_search(my_list, 7)}")
• Binary Search: A much more efficient search algorithm, but it requires the list to be sorted first. It works by repeatedly dividing the search interval in half. Its time complexity is O(log n).
def binary_search(sorted_data, target):
low = 0
high = len(sorted_data) - 1
while low <= high:
mid = (low + high) // 2
if sorted_data[mid] < target:
low = mid + 1
elif sorted_data[mid] > target:
high = mid - 1
else:
return mid # Element found
return -1 # Element not found
# Example
my_sorted_list = [1, 2, 4, 5, 7, 9]
print(f"Binary Search: Element 7 found at index {binary_search(my_sorted_list, 7)}")
• Bubble Sort: A simple sorting algorithm that repeatedly steps through the list, compares adjacent elements and swaps them if they are in the wrong order. The process is repeated until the list is sorted. Its time complexity is O(n^2).
def bubble_sort(data):
n = len(data)
for i in range(n):
# Last i elements are already in place
for j in range(0, n-i-1):
if data[j] > data[j+1]:
# Swap the elements
data[j], data[j+1] = data[j+1], data[j]
return data
# Example
my_list_to_sort = [4, 2, 7, 1, 9, 5]
print(f"Bubble Sort: Sorted list is {bubble_sort(my_list_to_sort)}")
• Recursion (Factorial): Recursion is a method where a function calls itself to solve a problem. A classic example is calculating the factorial of a number (
n!). It must have a base case to stop the recursion.def factorial(n):
# Base case: if n is 1 or 0, factorial is 1
if n == 0 or n == 1:
return 1
# Recursive step: n * factorial of (n-1)
else:
return n * factorial(n - 1)
# Example
num = 5
print(f"Recursion: Factorial of {num} is {factorial(num)}")
#Python #Algorithms #DataStructures #Coding #Programming #LearnToCode
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By: @DataScience4 ✨
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