React ♥️ for more resources

𝟱 𝗙𝗥𝗘𝗘 𝗖𝘆𝗯𝗲𝗿 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍

Break into the world of Cybersecurity without spending a dime!🚀

These 5 beginner-friendly courses are your gateway to mastering essential skills and advancing your career👨‍💻📌

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🌮 Data Analyst Vs Data Engineer Vs Data Scientist 🌮


Skills required to become data analyst
👉 Advanced Excel, Oracle/SQL
👉 Python/R

Skills required to become data engineer
👉 Python/ Java.
👉 SQL, NoSQL technologies like Cassandra or MongoDB
👉 Big data technologies like Hadoop, Hive/ Pig/ Spark

Skills required to become data Scientist
👉 In-depth knowledge of tools like R/ Python/ SAS.
👉 Well versed in various machine learning algorithms like scikit-learn, karas and tensorflow
👉 SQL and NoSQL

Bonus skill required: Data Visualization (PowerBI/ Tableau) & Statistics

𝗧𝗼𝗽 𝗣𝘆𝘁𝗵𝗼𝗻 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝟮𝟬𝟮𝟱 — 𝗥𝗲𝗰𝗲𝗻𝘁𝗹𝘆 𝗔𝘀𝗸𝗲𝗱 𝗯𝘆 𝗠𝗡𝗖𝘀😍

📌 Preparing for Python Interviews in 2025?🗣

If you’re aiming for roles in data analysis, backend development, or automation, Python is your key weapon—and so is preparing with the right questions.💻✨️

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𝟱 𝗙𝗿𝗲𝗲 𝗠𝗜𝗧 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗵𝗮𝘁 𝗘𝘃𝗲𝗿𝘆 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿 𝗦𝗵𝗼𝘂𝗹𝗱 𝗦𝘁𝗮𝗿𝘁 𝗪𝗶𝘁𝗵😍

💻 Want to Learn Coding but Don’t Know Where to Start?🎯

Whether you’re a student, career switcher, or complete beginner, this curated list is your perfect launchpad into tech💻🚀

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Top 10 programming languages & frameworks for beginner web developers:

1. HTML/CSS – Basics of web structure & styling
2. JavaScript – Adds interactivity
3. Python – Backend & versatility
4. PHP – Server-side noscripting
5. SQL – Database management
6. Ruby on Rails – Easy backend framework
7. Node.js – JavaScript backend runtime
8. React – Popular frontend library
9. Angular – Framework for building dynamic UIs
10. Bootstrap – Simplifies responsive design

Web Development Best Resources: https://topmate.io/coding/930165

ENJOY LEARNING 👍👍

10 Things you need to become an AI/ML engineer:

1. Framing machine learning problems
2. Weak supervision and active learning
3. Processing, training, deploying, inference pipelines
4. Offline evaluation and testing in production
5. Performing error analysis. Where to work next
6. Distributed training. Data and model parallelism
7. Pruning, quantization, and knowledge distillation
8. Serving predictions. Online and batch inference
9. Monitoring models and data distribution shifts
10. Automatic retraining and evaluation of models

𝟰 𝗙𝗿𝗲𝗲 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗪𝗲𝗯𝘀𝗶𝘁𝗲𝘀 𝘁𝗼 𝗦𝗵𝗮𝗿𝗽𝗲𝗻 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗦𝗸𝗶𝗹𝗹𝘀 𝗶𝗻 𝟮𝟬𝟮𝟱😍

🎯 Want to Sharpen Your Data Analytics Skills with Hands-On Practice?📊

Watching tutorials can only take you so far—practical application is what truly builds confidence and prepares you for the real world🚀

𝐋𝐢𝐧𝐤👇:-

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Start practicing what actually gets you hired✅️

Important skills every self-taught developer should master:

💻 HTML, CSS & JavaScript — the foundation of web development

⚙️ Git & GitHub — track changes and collaborate effectively

🧠 Problem-solving — break down and debug complex issues

🗄️ Basic SQL — manage and query data efficiently

🧩 APIs — fetch and use data from external sources

🧱 Frameworks — like React, Flask, or Django to build faster

🧼 Clean Code — write readable, maintainable code

📦 Package Managers — like npm or pip for managing libraries

🚀 Deployment — host your projects for the world to see

𝟱 𝗙𝗿𝗲𝗲 𝗠𝗜𝗧 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗵𝗮𝘁 𝗪𝗶𝗹𝗹 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿😍

📊 Want to Learn Data Analytics but Hate the High Price Tags?💰📌

Good news: MIT is offering free, high-quality data analytics courses through their OpenCourseWare platform💻🎯

𝐋𝐢𝐧𝐤👇:-

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All The Best 🎊