YouTube & WhatsApp Channels for Free Learning 🚀

👉 Introduction to Prog & CS:
https://youtu.be/zOjov-2OZ0E?si=gEbFC3o18x5enhWe

👉 OS:
https://youtu.be/3obEP8eLsCw?si=SSTwuiMWSc4KtGhy

👉 PowerBi:
https://youtu.be/UXhGRVTndQA?si=r9rpqRgbwy3LSxEZ

https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c

👉SQL
https://youtu.be/VCZxODefTIs?si=U0rn-L8CUB6_WfVk

https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v

👉 Data Analytics:
https://youtu.be/PSNXoAs2FtQ?si=yTzjpW2lP3qbVy22

https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02

👉 Python:
https://youtu.be/LHBE6Q9XlzI?si=9R_HmHaD7uGFWOvk
https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L

👉 Web Development:
https://youtube.com/playlist?list=PLu0W_9lII9agq5TrH9XLIKQvv0iaF2X3w&si=sbUzknTFsSo2RHh4

https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z

👉 Java:
https://youtube.com/playlist?list=PLsyeobzWxl7pe_IiTfNyr55kwJPWbgxB5&si=TUQALbuysZfeLknX

https://whatsapp.com/channel/0029VamdH5mHAdNMHMSBwg1s

👉 DBMS:
https://youtu.be/dl00fOOYLOM?si=w7THW7f8qdmztsd6

👉 DSA:
https://youtube.com/playlist?list=PLgUwDviBIf0oF6QL8m22w1hIDC1vJ_BHz&si=2zY8MHinpZN6S-Ox

https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X

👉 C++:
https://youtu.be/8jLOx1hD3_o?si=kD5OHquB7uN7J2eG

👉 Ethical Hacking:
https://youtu.be/cKEf8H9cQGM?si=xzL7ogRnnJCyhZlc

https://whatsapp.com/channel/0029VancSnGG8l5KQYOOyL1T

👉 Data Science:
https://youtu.be/gDZ6czwuQ18?si=Nmj950IQBRHPVocQ

https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y

👉 Machine Learning:
https://youtu.be/LvC68w9JS4Y?si=rXnXfmZVg0a7Ijpz

Join for more: https://news.1rj.ru/str/crackingthecodinginterview

ENJOY LEARNING 👍 👍

𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗛𝗶𝗿𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁𝘀/𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗔𝗻𝗮𝗹𝘆𝘀𝘁𝘀 😍

Companies Hiring:- 
- Goldman Sachs
- S&P Global
- Google 
- JP Morgan
- Pepsico
- PwC
Salary Range :- 5 To 24LPA

Job Location :- PAN India

𝐀𝐩𝐩𝐥𝐲 𝐧𝐨𝐰👇:- 

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Apply before the link expires💫

Hey guys!

I’ve been getting a lot of requests from you all asking for solid Data Analytics projects that can help you boost resume and build real skills.

So here you go —

These aren’t just “for practice,” they’re portfolio-worthy projects that show recruiters you’re ready for real-world work.

1. Sales Performance Dashboard

Tools: Excel / Power BI / Tableau
You’ll take raw sales data and turn it into a clean, interactive dashboard. Show key metrics like revenue, profit, top products, and regional trends.
Skills you build: Data cleaning, slicing & filtering, dashboard creation, business storytelling.

2. Customer Churn Analysis

Tools: Python (Pandas, Seaborn)

Work with a telecom or SaaS dataset to identify which customers are likely to leave and why.

Skills you build: Exploratory data analysis, visualization, correlation, and basic machine learning.


3. E-commerce Product Insights using SQL

Tools: SQL + Power BI

Analyze product categories, top-selling items, and revenue trends from a sample e-commerce dataset.

Skills you build: Joins, GROUP BY, aggregation, data modeling, and visual storytelling.


4. HR Analytics Dashboard

Tools: Excel / Power BI

Dive into employee data to find patterns in attrition, hiring trends, average salaries by department, etc.

Skills you build: Data summarization, calculated fields, visual formatting, DAX basics.


5. Movie Trends Analysis (Netflix or IMDb Dataset)

Tools: Python (Pandas, Matplotlib)

Explore trends across genres, ratings, and release years. Great for people who love entertainment and want to show creativity.

Skills you build: Data wrangling, time-series plots, filtering techniques.


6. Marketing Campaign Analysis

Tools: Excel / Power BI / SQL

Analyze data from a marketing campaign to measure ROI, conversion rates, and customer engagement. Identify which channels or strategies worked best and suggest improvements.

Skills you build: Data blending, KPI calculation, segmentation, and actionable insights.


7. Financial Expense Analysis & Budget Forecasting

Tools: Excel / Power BI / Python

Work on a company’s expense data to analyze spending patterns, categorize expenses, and create a forecasting model to predict future budgets.

Skills you build: Time series analysis, forecasting, budgeting, and financial storytelling.


Pick 2–3 projects. Don’t just show the final visuals — explain your process on LinkedIn or GitHub. That’s what sets you apart.

Like for more useful content ❤️

𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗦𝘁𝗲𝗽 𝗕𝘆 𝗦𝘁𝗲𝗽 𝟲-𝗠𝗼𝗻𝘁𝗵 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗥𝗼𝗮𝗱𝗺𝗮𝗽😍

🎯 What You’ll Learn:-
✅ HTML, CSS, JavaScript
✅ React, Node.js, Express.js
✅ MongoDB, REST APIs
✅ Git, GitHub, Deployment
✅ AWS, Google Cloud & more

This 6-month step-by-step roadmap takes you from absolute beginner to job-ready developer — using only free resources! 💻

𝐋𝐢𝐧𝐤👇:-

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Start today and build a portfolio that gets you hired!✅️

𝟲 𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗧𝗼 𝗖𝗵𝗮𝗻𝗴𝗲 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗜𝗻 𝟮𝟬𝟮𝟱 😍

🎯 Want to switch careers or upgrade your skills — without spending a single rupee?

Check out 6 handpicked, beginner-friendly courses in high-demand fields like Data Science, Web Development, Digital Marketing, Project Management, and more. 🚀

𝐋𝐢𝐧𝐤👇:-

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💥 Start learning today and build the skills top companies want!✅️

𝗟𝗲𝗮𝗿𝗻 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 𝘄𝗶𝘁𝗵 𝗛𝗮𝗿𝘃𝗮𝗿𝗱 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆😍

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Harvard University is offering a goldmine of free courses that make top-tier education accessible to anyone, anywhere👨‍💻✨️

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Are you from a Circuit Branch with coding experience and based in Bengaluru, Chennai, Hyderabad, or Pune?

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Python Roadmap for 2025: Complete Guide

1. Python Fundamentals
1.1 Variables, constants, and comments.
1.2 Data types: int, float, str, bool, complex.
1.3 Input and output (input(), print(), formatted strings).
1.4 Python syntax: Indentation and code structure.

2. Operators
2.1 Arithmetic: +, -, *, /, %, //, **.
2.2 Comparison: ==, !=, <, >, <=, >=.
2.3 Logical: and, or, not.
2.4 Bitwise: &, |, ^, ~, <<, >>.
2.5 Identity: is, is not.
2.6 Membership: in, not in.

3. Control Flow
3.1 Conditional statements: if, elif, else.
3.2 Loops: for, while.
3.3 Loop control: break, continue, pass.

4. Data Structures
4.1 Lists: Indexing, slicing, methods (append(), pop(), sort(), etc.).
4.2 Tuples: Immutability, packing/unpacking.
4.3 Dictionaries: Key-value pairs, methods (get(), items(), etc.).
4.4 Sets: Unique elements, set operations (union, intersection).
4.5 Strings: Immutability, methods (split(), strip(), replace()).

5. Functions
5.1 Defining functions with def.
5.2 Arguments: Positional, keyword, default, *args, **kwargs.
5.3 Anonymous functions (lambda).
5.4 Recursion.

6. Modules and Packages
6.1 Importing: import, from ... import.
6.2 Standard libraries: math, os, sys, random, datetime, time.
6.3 Installing external libraries with pip.

7. File Handling
7.1 Open and close files (open(), close()).
7.2 Read and write (read(), write(), readlines()).
7.3 Using context managers (with open(...)).

8. Object-Oriented Programming (OOP)
8.1 Classes and objects.
8.2 Methods and attributes.
8.3 Constructor (init).
8.4 Inheritance, polymorphism, encapsulation.
8.5 Special methods (str, repr, etc.).

9. Error and Exception Handling
9.1 try, except, else, finally.
9.2 Raising exceptions (raise).
9.3 Custom exceptions.

10. Comprehensions
10.1 List comprehensions.
10.2 Dictionary comprehensions.
10.3 Set comprehensions.

11. Iterators and Generators
11.1 Creating iterators using iter() and next().
11.2 Generators with yield.
11.3 Generator expressions.

12. Decorators and Closures
12.1 Functions as first-class citizens.
12.2 Nested functions.
12.3 Closures.
12.4 Creating and applying decorators.

13. Advanced Topics
13.1 Context managers (with statement).
13.2 Multithreading and multiprocessing.
13.3 Asynchronous programming with async and await.
13.4 Python's Global Interpreter Lock (GIL).

14. Python Internals
14.1 Mutable vs immutable objects.
14.2 Memory management and garbage collection.
14.3 Python's name == "main" mechanism.

15. Libraries and Frameworks
15.1 Data Science: NumPy, Pandas, Matplotlib, Seaborn.
15.2 Web Development: Flask, Django, FastAPI.
15.3 Testing: unittest, pytest.
15.4 APIs: requests, http.client.
15.5 Automation: selenium, os.
15.6 Machine Learning: scikit-learn, TensorFlow, PyTorch.

16. Tools and Best Practices
16.1 Debugging: pdb, breakpoints.

16.2 Code style: PEP 8 guidelines.
16.3 Virtual environments: venv.
16.4 Version control: Git + GitHub.

👇 Python Interview 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀
https://news.1rj.ru/str/dsabooks

📘 𝗣𝗿𝗲𝗺𝗶𝘂𝗺 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 : https://topmate.io/coding/914624

📙 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲: https://whatsapp.com/channel/0029VaxbzNFCxoAmYgiGTL3Z

Join What's app channel for jobs updates: t.me/getjobss

5 Algorithms you must know as a data scientist 👩‍💻 🧑‍💻

1. Dimensionality Reduction
- PCA, t-SNE, LDA

2. Regression models
- Linesr regression, Kernel-based regression models, Lasso Regression, Ridge regression, Elastic-net regression

3. Classification models
- Binary classification- Logistic regression, SVM
- Multiclass classification- One versus one, one versus many
- Multilabel classification

4. Clustering models
- K Means clustering, Hierarchical clustering, DBSCAN, BIRCH models

5. Decision tree based models
- CART model, ensemble models(XGBoost, LightGBM, CatBoost)

Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624

Join our WhatsApp channel: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D

Like if you need similar content 😄👍

𝟳 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗨𝗽𝗴𝗿𝗮𝗱𝗲 𝗬𝗼𝘂𝗿 𝗥𝗲𝘀𝘂𝗺𝗲 𝗶𝗻 𝟮𝟬𝟮𝟱 𝗮𝗻𝗱 𝗦𝘁𝗮𝗻𝗱 𝗢𝘂𝘁😍

🚀 Want to Make Your Resume Stand Out in 2025?✨️

If you’re aiming to boost your chances in job interviews or want to upgrade your resume with powerful, in-demand skills — start with these 7 free online courses👨‍💻📌

𝐋𝐢𝐧𝐤👇:-

https://pdlink.in/3SJ91OV

Empower yourself and take your career to the next level! ✅

🔰 DevOps Roadmap for Beginners 2025

├── 🧠 What is DevOps? Principles & Culture
├── 🧪 Mini Task: Set up Local CI Pipeline with Shell Scripts
├── ⚙️ Linux Basics: Commands, Shell Scripting
├── 📁 Version Control: Git, GitHub, GitLab
├── 🧪 Mini Task: Automate Deployment via GitHub Actions
├── 📦 Package Managers & Artifact Repositories (npm, pip, DockerHub)
├── 🐳 Docker Essentials: Images, Containers, Volumes, Networks
├── 🧪 Mini Project: Dockerize a MERN App
├── ☁️ CI/CD Concepts & Tools (Jenkins, GitHub Actions)
├── 🧪 Mini Project: CI/CD Pipeline for React App
├── 🧩 Infrastructure as Code: Terraform / Ansible Basics
├── 📈 Monitoring & Logging: Prometheus, Grafana, ELK Stack
├── 🔐 Secrets Management & Security Basics (Vault, .env)
├── 🌐 Web Servers: Nginx, Apache (Reverse Proxy, Load Balancer)
├── ☁️ Cloud Providers: AWS (EC2, S3, IAM), GCP, Azure Overview

React with ♥️ if you want me to explain each topic in detail

#devops

𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 😍 

4 Steps to Kickstart Your Career in Data Science

Master Essential Tools: Get started with Python, SQL, and machine learning fundamentals.

Create a Job-Ready Portfolio: Learn how to showcase your skills to recruiters.

Eligibility :- Students,Freshers & Woking Professionals 

𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐅𝐨𝐫 𝐅𝐑𝐄𝐄 👇:-

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(Limited Slots ..HurryUp🏃‍♂️ ) 

𝐃𝐚𝐭𝐞 & 𝐓𝐢𝐦𝐞:-  June 13 2025, at 7 PM

Top 20 Web Development Technologies 🌐

1. 🟨 JavaScript — 98% usage

2. 🔵 TypeScript — 78% adoption

3. 🟢 Node.js — 75% backend choice

4. ⚛️ React — 70% frontend framework

5. 🅰️ Angular — 55% enterprise use

6. 💚 Vue.js — 49% growing popularity

7. 🐍 Python — 48% for full-stack

8. 💎 Ruby on Rails — 45% rapid development

9. 🐘 PHP — 43% widespread use

10. ☕ Java — 40% enterprise solutions

11. 🦀 Rust — 38% performance-critical apps

12. 🎯 Dart — 35% with Flutter for web

13. 🔷 GraphQL — 33% API queries

14. 🍃 MongoDB — 30% NoSQL database

15. 🐳 Docker — 28% containerization

16. ☁️ AWS — 25% cloud services

17. 🔶 Svelte — 22% compile-time framework

18. 🔷 Next.js — 20% React framework

19. 🟣 Blazor — 18% .NET web apps

20. 🟢 Deno — 15% secure runtime