tgindex

Python Projects & Free Books

описание

Python Interview Projects & Free Courses Admin: @Coderfun

← к каналу@pythonfreebootcamp
40 848
подписчиков
Охват к подписчикам
6,3%
ERR
Реакции к просмотрам
0,11%
58 на 20 постов
Пересылки к просмотрам
0,48%
244
Постов в день
0,0
всего 20

Где отзываются чаще

доля реакций к просмотрам
  • 31 июл.🐍 Python Roadmap 1️⃣ Basics: 📝📜 Syntax, Variables, Data Types 2️⃣ Control Flow: 🔄🤖 If-Else, Loops, Functions 3️⃣ Data Structures: 🗂️🔢 Lists, Tuples, Dictionaries, Sets 4️⃣ OOP in Python: 📦🎭 Classes, Inheritance, Decorators 5️⃣ File Handling: 📄📂 Read/Write, JSON, CSV 6️⃣ Modules & Libraries: 📦🚀 NumPy, Pandas, Matplotlib 7️⃣ Web Development: 🌍🔧 Flask, Django, FastAPI 8️⃣ Automation & Scripting: 🤖🛠️ Web Scraping, Selenium, Bash Scripting 9️⃣ Machine Learning: 🧠📈 TensorFlow, Scikit-learn, PyTorch 🔟 Projects & Practice: 📂🎯 Create apps, scripts, and contribute to open source React ❤️ for more0,60%
  • 23 июл.✅ Complete Roadmap to Learn Python Programming 🐍💻 Week 1: Python Basics • Install Python and VS Code • Learn variables, data types, input, output • Practice arithmetic and string operations • Write 10 small programs Example: Calculator, temperature converter Week 2: Control Flow • Learn if, else, elif • Learn for and while loops • Use break and continue • Solve 20 logic problems Example: Number guessing game Week 3: Data Structures • Lists, tuples, sets, dictionaries • Indexing, slicing, methods • Loop through collections • Solve real problems Example: Student marks analysis Week 4: Functions and Modules • Define functions • Use parameters and return values • Learn lambda functions • Import built-in modules Example: Reusable math utility Week 5: Strings and File Handling • String methods and formatting • Read and write files • Handle CSV and text files • Build small file-based programs Example: Log file analyzer Week 6: Error Handling and Debugging • Learn try, except, finally • Understand common errors • Use print and debugger • Fix broken programs Example: Robust input validator Week 7: Object-Oriented Programming • Classes and objects • Constructors and methods • Inheritance and encapsulation • Build simple class-based apps Example: Bank account system Week 8: Standard Libraries • datetime, math, random • os and sys basics • Work with JSON • Write utility scripts Example: Automated folder organizer Week 9: Working with External Packages • Learn pip and virtual environments • Use requests library • Basic API calls • Handle API responses Example: Weather app using API Week 10: Data Handling Basics • Intro to NumPy • Intro to Pandas • Read CSV and Excel files • Basic data cleaning Example: Sales data summary Week 11: Mini Projects • Build 2 small projects • Focus on logic and structure • Write clean, readable code Examples: • To-do list app • Expense tracker Week 12: Final Project and Revision • Build one end-to-end project • Revise core concepts • Practice interview-style questions Example projects: • Simple automation tool • Data analysis mini project Daily Rule for You: • Code at least 60 minutes • Solve 5 problems daily • Rewrite old code weekly Double Tap ♥️ For Detailed Explanation0,38%
  • 6 июл.15 Best Project Ideas for Python : 🐍 🚀 Beginner Level: 1. Simple Calculator 2. To-Do List 3. Number Guessing Game 4. Dice Rolling Simulator 5. Word Counter 🌟 Intermediate Level: 6. Weather App 7. URL Shortener 8. Movie Recommender System 9. Chatbot 10. Image Caption Generator 🌌 Advanced Level: 11. Stock Market Analysis 12. Autonomous Drone Control 13. Music Genre Classification 14. Real-Time Object Detection 15. Natural Language Processing (NLP) Sentiment Analysis0,28%
  • 18 июл.🔰 Comprehensions in python with example0,27%
  • 2 июн.Python Basics Arrays & Loops 🐍 Essential you need to start strong 💪0,19%
  • 29 июн.🐍 𝐏𝐲𝐭𝐡𝐨𝐧 𝐟𝐞𝐥𝐭 𝐢𝐦𝐩𝐨𝐬𝐬𝐢𝐛𝐥𝐞 𝐚𝐭 𝐟𝐢𝐫𝐬𝐭, 𝐛𝐮𝐭 𝐭𝐡𝐞𝐬𝐞 𝟗 𝐬𝐭𝐞𝐩𝐬 𝐜𝐡𝐚𝐧𝐠𝐞𝐝 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠! . . 1️⃣ 𝐌𝐚𝐬𝐭𝐞𝐫𝐞𝐝 𝐭𝐡𝐞 𝐁𝐚𝐬𝐢𝐜𝐬: Started with foundational Python concepts like variables, loops, functions, and conditional statements. 2️⃣ 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐝 𝐄𝐚𝐬𝐲 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Focused on beginner-friendly problems on platforms like LeetCode and HackerRank to build confidence. 3️⃣ 𝐅𝐨𝐥𝐥𝐨𝐰𝐞𝐝 𝐏𝐲𝐭𝐡𝐨𝐧-𝐒𝐩𝐞𝐜𝐢𝐟𝐢𝐜 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬: Studied essential problem-solving techniques for Python, like list comprehensions, dictionary manipulations, and lambda functions. 4️⃣ 𝐋𝐞𝐚𝐫𝐧𝐞𝐝 𝐊𝐞𝐲 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬: Explored popular libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. 5️⃣ 𝐅𝐨𝐜𝐮𝐬𝐞𝐝 𝐨𝐧 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬: Built small projects like a to-do app, calculator, or data visualization dashboard to apply concepts. 6️⃣ 𝐖𝐚𝐭𝐜𝐡𝐞𝐝 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: Followed creators like CodeWithHarry and Shradha Khapra for in-depth Python tutorials. 7️⃣ 𝐃𝐞𝐛𝐮𝐠𝐠𝐞𝐝 𝐑𝐞𝐠𝐮𝐥𝐚𝐫𝐥𝐲: Made it a habit to debug and analyze code to understand errors and optimize solutions. 8️⃣ 𝐉𝐨𝐢𝐧𝐞𝐝 𝐌𝐨𝐜𝐤 𝐂𝐨𝐝𝐢𝐧𝐠 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬: Participated in coding challenges to simulate real-world problem-solving scenarios. 9️⃣ 𝐒𝐭𝐚𝐲𝐞𝐝 𝐂𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐭: Practiced daily, worked on diverse problems, and never skipped Python for more than a day. I have curated the best interview resources to crack Python Interviews 👇👇 https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L Hope you'll like it Like this post if you need more resources like this 👍❤️ #Python0,17%
  • 22 маяHey guys, Here are some best Telegram Channels for free education 👇👇 Data Science Projects Free Courses with Certificate Web Development Free Resources Data Science & Machine Learning Programming Free Books Data Analysis Books Python Free Courses Ethical Hacking & Cyber Security English Speaking & Communication Stock Marketing & Investment Banking Coding Projects Jobs & Internship Opportunities Crack your coding Interviews Udemy Free Courses with Certificate Free access to all the Paid Channels 👇👇 https://t.me/addlist/4q2PYC0pH_VjZDk5 Do react with ♥️ if you need more content like this ENJOY LEARNING 👍👍0,14%
  • 7 авг.Roadmap to become a data analyst 1. Foundation Skills: •Strengthen Mathematics: Focus on statistics relevant to data analysis. •Excel Basics: Master fundamental Excel functions and formulas. 2. SQL Proficiency: •Learn SQL Basics: Understand SELECT statements, JOINs, and filtering. •Practice Database Queries: Work with databases to retrieve and manipulate data. 3. Excel Advanced Techniques: •Data Cleaning in Excel: Learn to handle missing data and outliers. •PivotTables and PivotCharts: Master these powerful tools for data summarization. 4. Data Visualization with Excel: •Create Visualizations: Learn to build charts and graphs in Excel. •Dashboard Creation: Understand how to design effective dashboards. 5. Power BI Introduction: •Install and Explore Power BI: Familiarize yourself with the interface. •Import Data: Learn to import and transform data using Power BI. 6. Power BI Data Modeling: •Relationships: Understand and establish relationships between tables. •DAX (Data Analysis Expressions): Learn the basics of DAX for calculations. 7. Advanced Power BI Features: •Advanced Visualizations: Explore complex visualizations in Power BI. •Custom Measures and Columns: Utilize DAX for customized data calculations. 8. Integration of Excel, SQL, and Power BI: •Importing Data from SQL to Power BI: Practice connecting and importing data. •Excel and Power BI Integration: Learn how to use Excel data in Power BI. 9. Business Intelligence Best Practices: •Data Storytelling: Develop skills in presenting insights effectively. •Performance Optimization: Optimize reports and dashboards for efficiency. 10. Build a Portfolio: •Showcase Excel Projects: Highlight your data analysis skills using Excel. •Power BI Projects: Feature Power BI dashboards and reports in your portfolio. 11. Continuous Learning and Certification: •Stay Updated: Keep track of new features in Excel, SQL, and Power BI. •Consider Certifications: Obtain relevant certifications to validate your skills.0,12%
  • 14 апр.🔰 Python List Slicing0,12%
  • 22 июн.🔰 Python functions0,12%
  • 2 июл.7 GitHub repos to master AI engineering in 2026 👇 1/ Awesome Artificial Intelligence: https://github.com/owainlewis/awesome-artificial-intelligence 2/ Awesome LLM Apps: https://github.com/Shubhamsaboo/awesome-llm-apps 3/ 100 Days of ML Code: https://github.com/avik-jain/100-Days-of-ML-Code 4/ System Prompts and AI Tools: https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools 5/ AI Agents for Beginners: https://github.com/microsoft/ai-agents-for-beginners 6/ Microsoft Gen AI for Beginners: https://github.com/microsoft/ai-for-beginners 7/ Learn Agentic AI: https://github.com/panaversity/learn-agentic-ai0,10%
  • 15 июн.If you work with Python, remember a simple rule: do not modify a list while iterating over it. 🐍🛑 This can lead to unexpected results because the iterator does not track structural changes. Here is an example that looks logical but works incorrectly: 🤔 items = [1, 2, 2, 3, 4] for item in items: if item == 2: items.remove(item) print(items) # Output: [1, 2, 3, 4] It seems that all 2s should disappear, but one remains. ❓ Why? After removing an element, the list shifts, but the loop moves on — as a result, some values are simply skipped. 🔄🚫 How to do it correctly — iterate over a copy: ✅ for item in items[:]: if item == 2: items.remove(item) print(items) # Output: [1, 3, 4] Even better — use list comprehension: 🚀 items = [x for x in items if x != 2] Conclusion: 🏁 do not modify a collection during iteration. This can lead to skipped elements, duplication, or even errors during execution. 🛠️🚧 #Python #Coding #Programming #Debugging #TechTips #PythonTips0,06%