10 GitHub Repositories for Python Projects

🔹 The Ultimate Project-Based Python Learning Hub
‣ Top GitHub repo with 230k+ stars of hands-on tutorials.
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🔹 Endless Python Project Ideas & Resources
‣ Tons of creative ideas to sharpen your coding skills.
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🔹 Real Python’s Hands-On Learning Materials
‣ Bonus content and exercises from Real Python tutorials.
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🔹 Curated Project Tutorials for Every Learner
‣ Project-based learning with AI/ML tutorials included.
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🔹 Awesome Jupyter: Notebooks, Libraries & More
‣ Boost your Jupyter Notebook skills and workflow.
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🔹 Python Mini-Projects for Quick Wins
‣ Fun mini-games and small apps for fast practice.
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🔹 100 Practical Python Projects Challenge
‣ Track your progress across 100 real Python projects.
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🔹 Data Science Projects for Python Enthusiasts
‣ Beginner-friendly data science project ideas.
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🔹 Showcase of Awesome Python Projects
‣ Collection of cool Python projects with guides.
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🔹 Python Script Projects from Beginner to Advanced
‣ Step-by-step script projects for all levels.
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𝗔𝗜 & 𝗠𝗟 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲😍

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The key to starting your coding career:

❌It's not your degree
❌It's not your job experience

It's how you apply these principles:

1. Learn by building real projects
2. Create a portfolio that shows your skills
3. Share your work and connect with others

No one starts a coding expert, but everyone can become one.

If you're looking for a career in coding, start by:

⟶ Watching tutorials
⟶ Reading developer blogs
⟶ Doing internships or freelance gigs
⟶ Building projects (even small ones!)
⟶ Learning from senior developers

You'll be amazed at how fast you’ll grow and how quickly you’ll feel confident writing code.

So, start today and let your coding journey begin!

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𝗧𝗼𝗽 𝗠𝗡𝗖𝘀 𝗛𝗶𝗿𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁𝘀 ,𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗔𝗻𝗮𝗹𝘆𝘀𝘁𝘀 & 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀😍 
 
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Roadmap to become a Programmer:

📂 Learn Programming Fundamentals (Logic, Syntax, Flow)
∟📂 Choose a Language (Python / Java / C++)
∟📂 Learn Data Structures & Algorithms
∟📂 Learn Problem Solving (LeetCode / HackerRank)
∟📂 Learn OOPs & Design Patterns
∟📂 Learn Version Control (Git & GitHub)
∟📂 Learn Debugging & Testing
∟📂 Work on Real-World Projects
∟📂 Contribute to Open Source
∟✅ Apply for Job / Internship

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Oldest Programming Languages Still in Use Today 🕰️

📜 Fortran (1957) – Still used in scientific computing
🤖 Lisp (1958) – Powering AI since the start
💼 COBOL (1959) – Running banks & ATMs
🖥 C (1972) – The godfather of modern languages
🗣 Prolog (1972) – Logic programming OG

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𝗣𝗿𝗲𝗺𝗶𝘂𝗺 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 | Microsoft & AWS included😍

- Microsoft Courses
- IT/Software
- Data Science & ML
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- Management
- Cyber Security
- Cloud Computing

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Prep for jobs with AI mock interviews & resume builder

✅ Coding Portfolio Tips 🚀

A Coding portfolio is your proof of skill — it shows recruiters that you don’t just “know” concepts, but you can apply them to solve real problems. Here's how to build an impressive one:

🔹 What to Include in Your Portfolio

• Diverse Projects: Choose projects that showcase different programming languages, frameworks, and problem-solving skills.
• Real-World Applications: Focus on projects that address practical needs or simulate real-world scenarios.
• Clear Documentation: Include well-written README files explaining the project's purpose, how to run it, and any dependencies.
• Code Quality: Write clean, well-commented, and maintainable code.
• Testing: Include unit tests or integration tests to demonstrate the reliability of your code.

🔹 Where to Host Your Portfolio

• GitHub: The standard for code hosting, version control, and collaboration.
• Pin your best projects to the top of your profile.
• Organize your repositories with meaningful names and descriptions.
• Personal Website: Create a dedicated website to showcase your projects and skills.
• Include project descriptions, live demos (if applicable), and links to your GitHub repositories.
• Consider adding a blog to document your learning journey and share your coding insights.
• Other Platforms:
• CodePen/CodeSandbox: Great for front-end projects or showcasing individual components.
• HackerRank/LeetCode: Display your problem-solving abilities through your coding challenges.

🔹 Tips for Impact

• Contribute to open-source projects.
• Build projects that solve your own problems or address a niche need.
• Write blog posts about the challenges you faced and the solutions you implemented.
• Get feedback from other developers and iterate on your work.
• Showcase your passion for coding.

✅ Goal: When a recruiter opens your profile, they should instantly see your value as a practical and skilled coder.

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Data Science Interview Questions

1. What are the different subsets of SQL?

Data Definition Language (DDL) – It allows you to perform various operations on the database such as CREATE, ALTER, and DELETE objects.
Data Manipulation Language(DML) – It allows you to access and manipulate data. It helps you to insert, update, delete and retrieve data from the database.
Data Control Language(DCL) – It allows you to control access to the database. Example – Grant, Revoke access permissions.

2. List the different types of relationships in SQL.

There are different types of relations in the database:
One-to-One – This is a connection between two tables in which each record in one table corresponds to the maximum of one record in the other.
One-to-Many and Many-to-One – This is the most frequent connection, in which a record in one table is linked to several records in another.
Many-to-Many – This is used when defining a relationship that requires several instances on each sides.
Self-Referencing Relationships – When a table has to declare a connection with itself, this is the method to employ.

3. How to create empty tables with the same structure as another table?

To create empty tables:
Using the INTO operator to fetch the records of one table into a new table while setting a WHERE clause to false for all entries, it is possible to create empty tables with the same structure. As a result, SQL creates a new table with a duplicate structure to accept the fetched entries, but nothing is stored into the new table since the WHERE clause is active.

4. What is Normalization and what are the advantages of it?

Normalization in SQL is the process of organizing data to avoid duplication and redundancy. Some of the advantages are:
Better Database organization
More Tables with smaller rows
Efficient data access
Greater Flexibility for Queries
Quickly find the information
Easier to implement Security

🧠 Top 7 Core CS Subjects to Master for Tech Interviews (2025 Edition) 💡💻

✅ Data Structures & Algorithms 
Arrays, Trees, Graphs, HashMaps, Linked Lists, Heaps

✅ Operating Systems 
Processes, Threads, Scheduling, Deadlocks, Memory Management

✅ DBMS (Databases) 
Normalization, Transactions, SQL vs NoSQL, Indexing, Joins

✅ Computer Networks 
OSI Model, TCP/IP, DNS, HTTP/HTTPS, Sockets

✅ Object-Oriented Programming (OOP) 
Encapsulation, Inheritance, Polymorphism, SOLID Principles

✅ System Design (HLD/LLD) 
Load balancing, caching, database sharding, scalability

✅ Programming Languages 
Deep understanding of your primary language (C++, Java, Python, etc.)

🎯 These are non-negotiable for top tech roles & product-based companies.

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