🖥 Top Programming Languages to learn in 2024 - [Part 1] 🖥


1. JavaScript
- learnjavascript.online
- t.iss.one/javascript_courses/4
- learn-js.org

2. Java
- learnjavaonline.org
- javatpoint.com

3. C#
- learncs.org
- w3schools.com

4. TypeScript
- Typescriptlang.org
- learntypescript.dev

5. Rust
- rust-lang.org
- t.iss.one/Curiousprogrammer/376
- exercism.org

🖥 Top Programming Languages to learn in 2024 - [Part 2] 🖥


6. Go PRogramming
- go.dev
- learn-golang.org

7. Kotlin
- kotlinlang.org
- t.iss.one/codingwithsagar/327

8. Python
- learnpython.org
- t.iss.one/pythonanalyst

9. SQL
- learnsql.com
- t.iss.one/sqlanalyst

10. R Programming
- w3schools.com/r/
- r-coder.com

30-day roadmap to learn Python up to an intermediate level

Week 1: Python Basics
*Day 1-2:*
- Learn about Python, its syntax, and how to install Python on your computer.
- Write your first "Hello, World!" program.
- Understand variables and data types (integers, floats, strings).

*Day 3-4:*
- Explore basic operations (arithmetic, string concatenation).
- Learn about user input and how to use the input() function.
- Practice creating and using variables.

*Day 5-7:*
- Dive into control flow with if statements, else statements, and loops (for and while).
- Work on simple programs that involve conditions and loops.

Week 2: Functions and Modules
*Day 8-9:*
- Study functions and how to define your own functions using def.
- Learn about function arguments and return values.

*Day 10-12:*
- Explore built-in functions and libraries (e.g., len(), random, math).
- Understand how to import modules and use their functions.

*Day 13-14:*
- Practice writing functions for common tasks.
- Create a small project that utilizes functions and modules.

Week 3: Data Structures
*Day 15-17:*
- Learn about lists and their operations (slicing, appending, removing).
- Understand how to work with lists of different data types.

*Day 18-19:*
- Study dictionaries and their key-value pairs.
- Practice manipulating dictionary data.

*Day 20-21:*
- Explore tuples and sets.
- Understand when and how to use each data structure.

Week 4: Intermediate Topics
*Day 22-23:*
- Study file handling and how to read/write files in Python.
- Work on projects involving file operations.

*Day 24-26:*
- Learn about exceptions and error handling.
- Explore object-oriented programming (classes and objects).

*Day 27-28:*
- Dive into more advanced topics like list comprehensions and generators.
- Study Python's built-in libraries for web development (e.g., requests).

*Day 29-30:*
- Explore additional libraries and frameworks relevant to your interests (e.g., NumPy for data analysis, Flask for web development, or Pygame for game development).
- Work on a more complex project that combines your knowledge from the past weeks.

Throughout the 30 days, practice coding daily, and don't hesitate to explore Python's documentation and online resources for additional help. Learning Python is a dynamic process, so adapt the roadmap based on your progress and interests. Good luck with your Python journey!

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Free Resources To Crack Coding Interviews
👇👇

Coding Interview Prep FREE CERTIFIED COURSE

https://www.freecodecamp.org/learn/coding-interview-prep/#take-home-projects

Python Interview Questions and Answers

https://t.iss.one/dsabooks/75

Beginner's guide for DSA

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Cracking the coding interview FREE BOOK

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DSA Interview Questions and Answers

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Cracking the Coding interview: Learn 5 Essential Patterns
[4.5 star ratings out of 5]

https://bit.ly/3GUBk56

Data Science Interview Questions and Answers

https://t.iss.one/datasciencefun/958

Java Interview Questions with Answers

https://t.iss.one/Curiousprogrammer/106

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1. Computer Science
https://pll.harvard.edu/course/cs50-introduction-computer-science

2. JavaScript
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3. Python
https://cs50.harvard.edu/python/2022/

4. Digital Marketing
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1. Data Scientist 📊
2. ML Engineer  🤖
3. Software Engineer 💻
4. Cloud Engineer ☁️
5. Graphic Designer  🛠️
6. Blockchain Specialist 🔗
7. Data Analyst 🗄️
8. Frontend Developer 🖥️
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10. Fullstack Developer 🌐
11. Mobile Developer 📱
12. Data Engineer 🧑‍🎓

💡 Whether you're just starting out or looking to switch roles, these positions offer great opportunities for growth and high earning potential.

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PREPARING FOR AN ONLINE INTERVIEW?

10 basic tips to consider when invited/preparing for an online interview:

1. Get to know the online technology that the interviewer(s) will use. Is it a phone call, WhatsApp, Skype or Zoom interview? If not clear, ask.

2. Familiarize yourself with the online tools that you’ll be using. Understand how Zoom/Skype works and test it well in advance. Test the sound and video quality.

3. Ensure that your internet connection is stable. If using mobile data, make sure it’s adequate to sustain the call to the end.

4. Ensure the lighting and the background is good. Remove background clutter. Isolate yourself in a place where you’ll not have any noise distractions.

5. For Zoom/Skype calls, use your desktop or laptop instead of your phone. They’re more stable especially for video calls.

6. Mute all notifications on your computer/phone to avoid unnecessary distractions.

7. Ensure that your posture is right. Just because it’s a remote interview does not mean you slouch on your couch. Maintain an upright posture.

8. Prepare on the other job specifics just like you would for a face-to-face interview

9. Dress up like you would for a face-to-face interview.

10. Be all set at least 10 minutes to the start of interview.

Python Learning Plan in 2024

|-- Week 1: Introduction to Python
| |-- Python Basics
| | |-- What is Python?
| | |-- Installing Python
| | |-- Introduction to IDEs (Jupyter, VS Code)
| |-- Setting up Python Environment
| | |-- Anaconda Setup
| | |-- Virtual Environments
| | |-- Basic Syntax and Data Types
| |-- First Python Program
| | |-- Writing and Running Python Scripts
| | |-- Basic Input/Output
| | |-- Simple Calculations
|
|-- Week 2: Core Python Concepts
| |-- Control Structures
| | |-- Conditional Statements (if, elif, else)
| | |-- Loops (for, while)
| | |-- Comprehensions
| |-- Functions
| | |-- Defining Functions
| | |-- Function Arguments and Return Values
| | |-- Lambda Functions
| |-- Modules and Packages
| | |-- Importing Modules
| | |-- Standard Library Overview
| | |-- Creating and Using Packages
|
|-- Week 3: Advanced Python Concepts
| |-- Data Structures
| | |-- Lists, Tuples, and Sets
| | |-- Dictionaries
| | |-- Collections Module
| |-- File Handling
| | |-- Reading and Writing Files
| | |-- Working with CSV and JSON
| | |-- Context Managers
| |-- Error Handling
| | |-- Exceptions
| | |-- Try, Except, Finally
| | |-- Custom Exceptions
|
|-- Week 4: Object-Oriented Programming
| |-- OOP Basics
| | |-- Classes and Objects
| | |-- Attributes and Methods
| | |-- Inheritance
| |-- Advanced OOP
| | |-- Polymorphism
| | |-- Encapsulation
| | |-- Magic Methods and Operator Overloading
| |-- Design Patterns
| | |-- Singleton
| | |-- Factory
| | |-- Observer
|
|-- Week 5: Python for Data Analysis
| |-- NumPy
| | |-- Arrays and Vectorization
| | |-- Indexing and Slicing
| | |-- Mathematical Operations
| |-- Pandas
| | |-- DataFrames and Series
| | |-- Data Cleaning and Manipulation
| | |-- Merging and Joining Data
| |-- Matplotlib and Seaborn
| | |-- Basic Plotting
| | |-- Advanced Visualizations
| | |-- Customizing Plots
|
|-- Week 6-8: Specialized Python Libraries
| |-- Web Development
| | |-- Flask Basics
| | |-- Django Basics
| |-- Data Science and Machine Learning
| | |-- Scikit-Learn
| | |-- TensorFlow and Keras
| |-- Automation and Scripting
| | |-- Automating Tasks with Python
| | |-- Web Scraping with BeautifulSoup and Scrapy
| |-- APIs and RESTful Services
| | |-- Working with REST APIs
| | |-- Building APIs with Flask/Django
|
|-- Week 9-11: Real-world Applications and Projects
| |-- Capstone Project
| | |-- Project Planning
| | |-- Data Collection and Preparation
| | |-- Building and Optimizing Models
| | |-- Creating and Publishing Reports
| |-- Case Studies
| | |-- Business Use Cases
| | |-- Industry-specific Solutions
| |-- Integration with Other Tools
| | |-- Python and SQL
| | |-- Python and Excel
| | |-- Python and Power BI
|
|-- Week 12: Post-Project Learning
| |-- Python for Automation
| | |-- Automating Daily Tasks
| | |-- Scripting with Python
| |-- Advanced Python Topics
| | |-- Asyncio and Concurrency
| | |-- Advanced Data Structures
| |-- Continuing Education
| | |-- Advanced Python Techniques
| | |-- Community and Forums
| | |-- Keeping Up with Updates
|
|-- Resources and Community
| |-- Online Courses (Coursera, edX, Udemy)
| |-- Books (Automate the Boring Stuff, Python Crash Course)
| |-- Python Blogs and Podcasts
| |-- GitHub Repositories
| |-- Python Communities (Reddit, Stack Overflow)

Here you can find essential Python Interview Resources👇
https://topmate.io/analyst/907371

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C programming notes

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Python handwriting notes 📝

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✅ @englishlearnerspro - improve your English

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✅ @sqlspecialist - Data Analysts Community

✅ @programming_guide - Coding Books

✅ @udemy_free_courses_with_certi - Free Udemy Courses with Certificate