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Now you can directly find job opportunities on WhatsApp. Here is the list of top job related channels on WhatsApp 👇
Latest Jobs & Internship Opportunities: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
Python & AI Jobs: https://whatsapp.com/channel/0029VaxtmHsLikgJ2VtGbu1R
Software Engineer Jobs: https://whatsapp.com/channel/0029VatL9a22kNFtPtLApJ2L
Data Science Jobs: https://whatsapp.com/channel/0029VaxTMmQADTOA746w7U2P
Data Analyst Jobs: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J
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❤4
Tools & Tech Every Developer Should Know ⚒️👨🏻💻
❯ VS Code ➟ Lightweight, Powerful Code Editor
❯ Postman ➟ API Testing, Debugging
❯ Docker ➟ App Containerization
❯ Kubernetes ➟ Scaling & Orchestrating Containers
❯ Git ➟ Version Control, Team Collaboration
❯ GitHub/GitLab ➟ Hosting Code Repos, CI/CD
❯ Figma ➟ UI/UX Design, Prototyping
❯ Jira ➟ Agile Project Management
❯ Slack/Discord ➟ Team Communication
❯ Notion ➟ Docs, Notes, Knowledge Base
❯ Trello ➟ Task Management
❯ Zsh + Oh My Zsh ➟ Advanced Terminal Experience
❯ Linux Terminal ➟ DevOps, Shell Scripting
❯ Homebrew (macOS) ➟ Package Manager
❯ Anaconda ➟ Python & Data Science Environments
❯ Pandas ➟ Data Manipulation in Python
❯ NumPy ➟ Numerical Computation
❯ Jupyter Notebooks ➟ Interactive Python Coding
❯ Chrome DevTools ➟ Web Debugging
❯ Firebase ➟ Backend as a Service
❯ Heroku ➟ Easy App Deployment
❯ Netlify ➟ Deploy Frontend Sites
❯ Vercel ➟ Full-Stack Deployment for Next.js
❯ Nginx ➟ Web Server, Load Balancer
❯ MongoDB ➟ NoSQL Database
❯ PostgreSQL ➟ Advanced Relational Database
❯ Redis ➟ Caching & Fast Storage
❯ Elasticsearch ➟ Search & Analytics Engine
❯ Sentry ➟ Error Monitoring
❯ Jenkins ➟ Automate CI/CD Pipelines
❯ AWS/GCP/Azure ➟ Cloud Services & Deployment
❯ Swagger ➟ API Documentation
❯ SASS/SCSS ➟ CSS Preprocessors
❯ Tailwind CSS ➟ Utility-First CSS Framework
React ❤️ if you found this helpful
Coding Jobs: https://whatsapp.com/channel/0029VatL9a22kNFtPtLApJ2L
❯ VS Code ➟ Lightweight, Powerful Code Editor
❯ Postman ➟ API Testing, Debugging
❯ Docker ➟ App Containerization
❯ Kubernetes ➟ Scaling & Orchestrating Containers
❯ Git ➟ Version Control, Team Collaboration
❯ GitHub/GitLab ➟ Hosting Code Repos, CI/CD
❯ Figma ➟ UI/UX Design, Prototyping
❯ Jira ➟ Agile Project Management
❯ Slack/Discord ➟ Team Communication
❯ Notion ➟ Docs, Notes, Knowledge Base
❯ Trello ➟ Task Management
❯ Zsh + Oh My Zsh ➟ Advanced Terminal Experience
❯ Linux Terminal ➟ DevOps, Shell Scripting
❯ Homebrew (macOS) ➟ Package Manager
❯ Anaconda ➟ Python & Data Science Environments
❯ Pandas ➟ Data Manipulation in Python
❯ NumPy ➟ Numerical Computation
❯ Jupyter Notebooks ➟ Interactive Python Coding
❯ Chrome DevTools ➟ Web Debugging
❯ Firebase ➟ Backend as a Service
❯ Heroku ➟ Easy App Deployment
❯ Netlify ➟ Deploy Frontend Sites
❯ Vercel ➟ Full-Stack Deployment for Next.js
❯ Nginx ➟ Web Server, Load Balancer
❯ MongoDB ➟ NoSQL Database
❯ PostgreSQL ➟ Advanced Relational Database
❯ Redis ➟ Caching & Fast Storage
❯ Elasticsearch ➟ Search & Analytics Engine
❯ Sentry ➟ Error Monitoring
❯ Jenkins ➟ Automate CI/CD Pipelines
❯ AWS/GCP/Azure ➟ Cloud Services & Deployment
❯ Swagger ➟ API Documentation
❯ SASS/SCSS ➟ CSS Preprocessors
❯ Tailwind CSS ➟ Utility-First CSS Framework
React ❤️ if you found this helpful
Coding Jobs: https://whatsapp.com/channel/0029VatL9a22kNFtPtLApJ2L
❤7
Python Functions 👆
❤2
Fullstack Developer Skills & Technologies
❤2
Complete roadmap to learn Python and Data Structures & Algorithms (DSA) in 2 months
### Week 1: Introduction to Python
Day 1-2: Basics of Python
- Python setup (installation and IDE setup)
- Basic syntax, variables, and data types
- Operators and expressions
Day 3-4: Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)
Day 5-6: Functions and Modules
- Function definitions, parameters, and return values
- Built-in functions and importing modules
Day 7: Practice Day
- Solve basic problems on platforms like HackerRank or LeetCode
### Week 2: Advanced Python Concepts
Day 8-9: Data Structures in Python
- Lists, tuples, sets, and dictionaries
- List comprehensions and generator expressions
Day 10-11: Strings and File I/O
- String manipulation and methods
- Reading from and writing to files
Day 12-13: Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance, polymorphism, encapsulation
Day 14: Practice Day
- Solve intermediate problems on coding platforms
### Week 3: Introduction to Data Structures
Day 15-16: Arrays and Linked Lists
- Understanding arrays and their operations
- Singly and doubly linked lists
Day 17-18: Stacks and Queues
- Implementation and applications of stacks
- Implementation and applications of queues
Day 19-20: Recursion
- Basics of recursion and solving problems using recursion
- Recursive vs iterative solutions
Day 21: Practice Day
- Solve problems related to arrays, linked lists, stacks, and queues
### Week 4: Fundamental Algorithms
Day 22-23: Sorting Algorithms
- Bubble sort, selection sort, insertion sort
- Merge sort and quicksort
Day 24-25: Searching Algorithms
- Linear search and binary search
- Applications and complexity analysis
Day 26-27: Hashing
- Hash tables and hash functions
- Collision resolution techniques
Day 28: Practice Day
- Solve problems on sorting, searching, and hashing
### Week 5: Advanced Data Structures
Day 29-30: Trees
- Binary trees, binary search trees (BST)
- Tree traversals (in-order, pre-order, post-order)
Day 31-32: Heaps and Priority Queues
- Understanding heaps (min-heap, max-heap)
- Implementing priority queues using heaps
Day 33-34: Graphs
- Representation of graphs (adjacency matrix, adjacency list)
- Depth-first search (DFS) and breadth-first search (BFS)
Day 35: Practice Day
- Solve problems on trees, heaps, and graphs
### Week 6: Advanced Algorithms
Day 36-37: Dynamic Programming
- Introduction to dynamic programming
- Solving common DP problems (e.g., Fibonacci, knapsack)
Day 38-39: Greedy Algorithms
- Understanding greedy strategy
- Solving problems using greedy algorithms
Day 40-41: Graph Algorithms
- Dijkstra’s algorithm for shortest path
- Kruskal’s and Prim’s algorithms for minimum spanning tree
Day 42: Practice Day
- Solve problems on dynamic programming, greedy algorithms, and advanced graph algorithms
### Week 7: Problem Solving and Optimization
Day 43-44: Problem-Solving Techniques
- Backtracking, bit manipulation, and combinatorial problems
Day 45-46: Practice Competitive Programming
- Participate in contests on platforms like Codeforces or CodeChef
Day 47-48: Mock Interviews and Coding Challenges
- Simulate technical interviews
- Focus on time management and optimization
Day 49: Review and Revise
- Go through notes and previously solved problems
- Identify weak areas and work on them
### Week 8: Final Stretch and Project
Day 50-52: Build a Project
- Use your knowledge to build a substantial project in Python involving DSA concepts
Day 53-54: Code Review and Testing
- Refactor your project code
- Write tests for your project
Day 55-56: Final Practice
- Solve problems from previous contests or new challenging problems
Day 57-58: Documentation and Presentation
- Document your project and prepare a presentation or a detailed report
Day 59-60: Reflection and Future Plan
- Reflect on what you've learned
- Plan your next steps (advanced topics, more projects, etc.)
Best DSA RESOURCES: https://topmate.io/coding/886874
Credits: https://news.1rj.ru/str/free4unow_backup
ENJOY LEARNING 👍👍
### Week 1: Introduction to Python
Day 1-2: Basics of Python
- Python setup (installation and IDE setup)
- Basic syntax, variables, and data types
- Operators and expressions
Day 3-4: Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)
Day 5-6: Functions and Modules
- Function definitions, parameters, and return values
- Built-in functions and importing modules
Day 7: Practice Day
- Solve basic problems on platforms like HackerRank or LeetCode
### Week 2: Advanced Python Concepts
Day 8-9: Data Structures in Python
- Lists, tuples, sets, and dictionaries
- List comprehensions and generator expressions
Day 10-11: Strings and File I/O
- String manipulation and methods
- Reading from and writing to files
Day 12-13: Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance, polymorphism, encapsulation
Day 14: Practice Day
- Solve intermediate problems on coding platforms
### Week 3: Introduction to Data Structures
Day 15-16: Arrays and Linked Lists
- Understanding arrays and their operations
- Singly and doubly linked lists
Day 17-18: Stacks and Queues
- Implementation and applications of stacks
- Implementation and applications of queues
Day 19-20: Recursion
- Basics of recursion and solving problems using recursion
- Recursive vs iterative solutions
Day 21: Practice Day
- Solve problems related to arrays, linked lists, stacks, and queues
### Week 4: Fundamental Algorithms
Day 22-23: Sorting Algorithms
- Bubble sort, selection sort, insertion sort
- Merge sort and quicksort
Day 24-25: Searching Algorithms
- Linear search and binary search
- Applications and complexity analysis
Day 26-27: Hashing
- Hash tables and hash functions
- Collision resolution techniques
Day 28: Practice Day
- Solve problems on sorting, searching, and hashing
### Week 5: Advanced Data Structures
Day 29-30: Trees
- Binary trees, binary search trees (BST)
- Tree traversals (in-order, pre-order, post-order)
Day 31-32: Heaps and Priority Queues
- Understanding heaps (min-heap, max-heap)
- Implementing priority queues using heaps
Day 33-34: Graphs
- Representation of graphs (adjacency matrix, adjacency list)
- Depth-first search (DFS) and breadth-first search (BFS)
Day 35: Practice Day
- Solve problems on trees, heaps, and graphs
### Week 6: Advanced Algorithms
Day 36-37: Dynamic Programming
- Introduction to dynamic programming
- Solving common DP problems (e.g., Fibonacci, knapsack)
Day 38-39: Greedy Algorithms
- Understanding greedy strategy
- Solving problems using greedy algorithms
Day 40-41: Graph Algorithms
- Dijkstra’s algorithm for shortest path
- Kruskal’s and Prim’s algorithms for minimum spanning tree
Day 42: Practice Day
- Solve problems on dynamic programming, greedy algorithms, and advanced graph algorithms
### Week 7: Problem Solving and Optimization
Day 43-44: Problem-Solving Techniques
- Backtracking, bit manipulation, and combinatorial problems
Day 45-46: Practice Competitive Programming
- Participate in contests on platforms like Codeforces or CodeChef
Day 47-48: Mock Interviews and Coding Challenges
- Simulate technical interviews
- Focus on time management and optimization
Day 49: Review and Revise
- Go through notes and previously solved problems
- Identify weak areas and work on them
### Week 8: Final Stretch and Project
Day 50-52: Build a Project
- Use your knowledge to build a substantial project in Python involving DSA concepts
Day 53-54: Code Review and Testing
- Refactor your project code
- Write tests for your project
Day 55-56: Final Practice
- Solve problems from previous contests or new challenging problems
Day 57-58: Documentation and Presentation
- Document your project and prepare a presentation or a detailed report
Day 59-60: Reflection and Future Plan
- Reflect on what you've learned
- Plan your next steps (advanced topics, more projects, etc.)
Best DSA RESOURCES: https://topmate.io/coding/886874
Credits: https://news.1rj.ru/str/free4unow_backup
ENJOY LEARNING 👍👍
❤5
Python CheatSheet 📚 ✅
1. Basic Syntax
- Print Statement:
- Comments:
2. Data Types
- Integer:
- Float:
- String:
- List:
- Tuple:
- Dictionary:
3. Control Structures
- If Statement:
- For Loop:
- While Loop:
4. Functions
- Define Function:
- Lambda Function:
5. Exception Handling
- Try-Except Block:
6. File I/O
- Read File:
- Write File:
7. List Comprehensions
- Basic Example:
- Conditional Comprehension:
8. Modules and Packages
- Import Module:
- Import Specific Function:
9. Common Libraries
- NumPy:
- Pandas:
- Matplotlib:
10. Object-Oriented Programming
- Define Class:
11. Virtual Environments
- Create Environment:
- Activate Environment:
- Windows:
- macOS/Linux:
12. Common Commands
- Run Script:
- Install Package:
- List Installed Packages:
This Python checklist serves as a quick reference for essential syntax, functions, and best practices to enhance your coding efficiency!
Checklist for Data Analyst: https://dataanalytics.beehiiv.com/p/data
Here you can find essential Python Interview Resources👇
https://news.1rj.ru/str/DataSimplifier
Like for more resources like this 👍 ♥️
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
1. Basic Syntax
- Print Statement:
print("Hello, World!")- Comments:
# This is a comment2. Data Types
- Integer:
x = 10- Float:
y = 10.5- String:
name = "Alice"- List:
fruits = ["apple", "banana", "cherry"]- Tuple:
coordinates = (10, 20)- Dictionary:
person = {"name": "Alice", "age": 25}3. Control Structures
- If Statement:
if x > 10:
print("x is greater than 10")
- For Loop:
for fruit in fruits:
print(fruit)
- While Loop:
while x < 5:
x += 1
4. Functions
- Define Function:
def greet(name):
return f"Hello, {name}!"
- Lambda Function:
add = lambda a, b: a + b5. Exception Handling
- Try-Except Block:
try:
result = 10 / 0
except ZeroDivisionError:
print("Cannot divide by zero.")
6. File I/O
- Read File:
with open('file.txt', 'r') as file:
content = file.read()
- Write File:
with open('file.txt', 'w') as file:
file.write("Hello, World!")
7. List Comprehensions
- Basic Example:
squared = [x**2 for x in range(10)]- Conditional Comprehension:
even_squares = [x**2 for x in range(10) if x % 2 == 0]8. Modules and Packages
- Import Module:
import math- Import Specific Function:
from math import sqrt9. Common Libraries
- NumPy:
import numpy as np- Pandas:
import pandas as pd- Matplotlib:
import matplotlib.pyplot as plt10. Object-Oriented Programming
- Define Class:
class Dog:
def __init__(self, name):
self.name = name
def bark(self):
return "Woof!"
11. Virtual Environments
- Create Environment:
python -m venv myenv- Activate Environment:
- Windows:
myenv\Scripts\activate- macOS/Linux:
source myenv/bin/activate12. Common Commands
- Run Script:
python noscript.py- Install Package:
pip install package_name- List Installed Packages:
pip listThis Python checklist serves as a quick reference for essential syntax, functions, and best practices to enhance your coding efficiency!
Checklist for Data Analyst: https://dataanalytics.beehiiv.com/p/data
Here you can find essential Python Interview Resources👇
https://news.1rj.ru/str/DataSimplifier
Like for more resources like this 👍 ♥️
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
❤5