Free Online Courses with Certificate | Udacity Free Courses | Eduonix | IP Cybersecurity | Coursera | Premium Certified Courses
👉Udacity, Microsoft, Edx, Google and Eduonix courses for free 👉Get premium Free courses from top websites 👉We also provide discount coupon codes for premium Udacity courses to help you as much as we can For promotions: @love_data
Показати більше📈 Аналітичний огляд Telegram-каналу Free Online Courses with Certificate | Udacity Free Courses | Eduonix | IP Cybersecurity | Coursera | Premium Certified Courses
Канал Free Online Courses with Certificate | Udacity Free Courses | Eduonix | IP Cybersecurity | Coursera | Premium Certified Courses (@udacityfreecourse) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 47 343 підписників, посідаючи 3 747 місце в категорії Освіта та 7 900 місце у регіоні Індія.
📊 Показники аудиторії та динаміка
З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 47 343 підписників.
За останніми даними від 30 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на -343, а за останні 24 години на 4, загальне охоплення залишається високим.
- Статус верифікації: Не верифікований
- Рівень залученості (ER): Середній показник залученості аудиторії становить 1.31%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.65% реакцій від загальної кількості підписників.
- Охоплення публікацій: В середньому кожен допис отримує 622 переглядів. Протягом першої доби публікація в середньому набирає 308 переглядів.
- Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 2.
- Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як |--, learning, javascript, analytic, certification.
📝 Опис та контентна політика
Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“👉Udacity, Microsoft, Edx, Google and Eduonix courses for free
👉Get premium Free courses from top websites
👉We also provide discount coupon codes for premium Udacity courses to help you as much as we can
For promotions: @love_data”
Завдяки високій частоті оновлень (останні дані отримано 01 липня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.
Триває завантаження даних...
| Дата | Залучення підписників | Згадування | Канали | |
| 01 липня | +6 |
| 2 | Complete roadmap to learn Python for data analysis
Step 1: Fundamentals of Python
1. Basics of Python Programming
- Introduction to Python
- Data types (integers, floats, strings, booleans)
- Variables and constants
- Basic operators (arithmetic, comparison, logical)
2. Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)
- List comprehensions
3. Functions and Modules
- Defining functions
- Function arguments and return values
- Importing modules
- Built-in functions vs. user-defined functions
4. Data Structures
- Lists, tuples, sets, dictionaries
- Manipulating data structures (add, remove, update elements)
Step 2: Advanced Python
1. File Handling
- Reading from and writing to files
- Working with different file formats (txt, csv, json)
2. Error Handling
- Try, except blocks
- Handling exceptions and errors gracefully
3. Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance and polymorphism
- Encapsulation
Step 3: Libraries for Data Analysis
1. NumPy
- Understanding arrays and array operations
- Indexing, slicing, and iterating
- Mathematical functions and statistical operations
2. Pandas
- Series and DataFrames
- Reading and writing data (csv, excel, sql, json)
- Data cleaning and preparation
- Merging, joining, and concatenating data
- Grouping and aggregating data
3. Matplotlib and Seaborn
- Data visualization with Matplotlib
- Plotting different types of graphs (line, bar, scatter, histogram)
- Customizing plots
- Advanced visualizations with Seaborn
Step 4: Data Manipulation and Analysis
1. Data Wrangling
- Handling missing values
- Data transformation
- Feature engineering
2. Exploratory Data Analysis (EDA)
- Descriptive statistics
- Data visualization techniques
- Identifying patterns and outliers
3. Statistical Analysis
- Hypothesis testing
- Correlation and regression analysis
- Probability distributions
Step 5: Advanced Topics
1. Time Series Analysis
- Working with datetime objects
- Time series decomposition
- Forecasting models
2. Machine Learning Basics
- Introduction to machine learning
- Supervised vs. unsupervised learning
- Using Scikit-Learn for machine learning
- Building and evaluating models
3. Big Data and Cloud Computing
- Introduction to big data frameworks (e.g., Hadoop, Spark)
- Using cloud services for data analysis (e.g., AWS, Google Cloud)
Step 6: Practical Projects
1. Hands-on Projects
- Analyzing datasets from Kaggle
- Building interactive dashboards with Plotly or Dash
- Developing end-to-end data analysis projects
2. Collaborative Projects
- Participating in data science competitions
- Contributing to open-source projects
👨💻 FREE Resources to Learn & Practice Python
1. https://www.freecodecamp.org/learn/data-analysis-with-python/#data-analysis-with-python-course
2. https://www.hackerrank.com/domains/python
3. https://www.hackerearth.com/practice/python/getting-started/numbers/practice-problems/
4. https://t.me/PythonInterviews
5. https://www.w3schools.com/python/python_exercises.asp
6. https://t.me/pythonfreebootcamp/134
7. https://t.me/pythonanalyst
8. https://pythonbasics.org/exercises/
9. https://t.me/pythondevelopersindia/300
10. https://www.geeksforgeeks.org/python-programming-language/learn-python-tutorial
11. https://t.me/pythonspecialist/33
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| 5 | Don't pay for AI courses!
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*Double Tap ❤️ For More* | 410 |
| 6 | 💻 𝗠𝗮𝘀𝘁𝗲𝗿 𝗦𝗤𝗟 𝗙𝗢𝗥 𝗙𝗥𝗘𝗘 | 𝟱 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗪𝗲𝗯𝘀𝗶𝘁𝗲𝘀 𝗧𝗼 𝗟𝗲𝗮𝗿𝗻 𝗦𝗤𝗟 🚀
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| 7 | 🚀 𝗡𝗩𝗜𝗗𝗜𝗔 𝗙𝗥𝗘𝗘 𝗔𝗜 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 | 𝗟𝗲𝗮𝗿𝗻 𝗙𝗿𝗼𝗺 𝗔𝗜 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗟𝗲𝗮𝗱𝗲𝗿𝘀
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🔗 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:
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🚀 Start Learning Today. Earn Your Certificate. Build Your Future in AI! | 499 |
| 8 | FREE Resources to Learn Data Science 🔥
* Python – python.org/doc
* NumPy – numpy.org/doc
* Pandas – pandas.pydata.org/docs
* Matplotlib – matplotlib.org
* Seaborn – seaborn.pydata.org
* SQL – sqlzoo.net (or sqlbolt.com)
* Statistics – khanacademy.org/math/statistics-probability
* Machine Learning – scikit-learn.org/stable
* Deep Learning – pytorch.org/tutorials
* Google Data Analytics – coursera.org/learn/google-data-analytics (audit free)
* Kaggle Learn – kaggle.com/learn
* Portfolio Projects – kaggle.com/datasets
Double Tap ♥️ For More | 470 |
| 9 | 𝗧𝗖𝗦 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗢𝗻 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 - 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘😍
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🔗 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:
https://pdlink.in/4jGFBw0
🚀 Start Learning Today. Upskill for Free. Get Career Ready! | 522 |
| 10 | 📊 𝗙𝗥𝗘𝗘 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 | 𝗡𝗼 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗡𝗲𝗲𝗱𝗲𝗱! 🚀
Want to start a career in Data Analytics but don't know where to begin?
These 5 FREE beginner-friendly courses will help you learn the most in-demand data skills and build a strong foundation.
🔗 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:
https://pdlink.in/3SOk64h
🚀 Start Learning Today. Build Your Portfolio. Land Your Dream Data Job! | 498 |
| 11 | 📊 𝗙𝗥𝗘𝗘 𝗧𝗮𝘁𝗮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 | 𝗪𝗶𝘁𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲 🚀
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🔗 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:
https://pdlink.in/4eybW8J
🚀 Upskill Today. Build Your Portfolio. Get Career Ready! | 595 |
| 12 | 10 Python Libraries for Building LLM Applications
🔹 1. Transformers
Core library for loading, fine-tuning, and running LLMs with ease.
👉 Learn more: https://huggingface.co/docs/transformers
🔹 2. LangChain
Connect prompts, tools, APIs, and models into powerful workflows.
👉 Learn more: https://docs.langchain.com
🔹 3. LlamaIndex
Bring your own data into LLMs for smarter, grounded responses (RAG).
👉 Learn more: https://docs.llamaindex.ai
🔹 4. vLLM
High-performance LLM serving with faster inference and better scaling.
👉 Learn more: https://docs.vllm.ai
🔹 5. Unsloth
Efficient fine-tuning with LoRA & QLoRA — even on limited hardware.
👉 Learn more: https://github.com/unslothai/unsloth
🔹 6. CrewAI
Build multi-agent systems where AI agents collaborate on tasks.
👉 Learn more: https://docs.crewai.com
🔹 7. AutoGPT
Create goal-driven autonomous agents with step-by-step execution.
👉 Learn more: https://github.com/Significant-Gravitas/AutoGPT
🔹 8. LangGraph
Design advanced, stateful workflows with branching logic.
👉 Learn more: https://docs.langchain.com/langgraph
🔹 9. DeepEval
Test and evaluate LLM outputs for accuracy and reliability.
👉 Learn more: https://github.com/confident-ai/deepeval
🔹 10. OpenAI Python SDK
Quickly integrate powerful AI features without managing infrastructure.
👉 Learn more: https://platform.openai.com/docs
❤️ Follow for more | 582 |
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🔗 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:
https://pdlink.in/4g5sKFa
Share with yours friends who wants to start a career in Data Analytics | 527 |
| 14 | 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝟭𝟬𝟬+ 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗔𝘇𝘂𝗿𝗲, 𝗔𝗜, 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 & 𝗠𝗼𝗿𝗲 🚀
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🚀 Learn. Practice. Upskill. Get Career Ready | 510 |
| 15 | If I wanted to get my opportunity to interview at Google or Amazon for SDE roles in the next 6-8 months…
Here’s exactly how I’d approach it (I’ve taught this to 100s of students and followed it myself to land interviews at 3+ FAANGs):
► Step 1: Learn to Code (from scratch, even if you’re from non-CS background)
I helped my sister go from zero coding knowledge (she studied Biology and Electrical Engineering) to landing a job at Microsoft.
We started with:
- A simple programming language (C++, Java, Python — pick one)
- FreeCodeCamp on YouTube for beginner-friendly lectures
- Key rule: Don’t just watch. Code along with the video line by line.
Time required: 30–40 days to get good with loops, conditions, syntax.
► Step 2: Start with DSA before jumping to development
Why?
- 90% of tech interviews in top companies focus on Data Structures & Algorithms
- You’ll need time to master it, so start early.
Start with:
- Arrays → Linked List → Stacks → Queues
- You can follow the DSA videos on my channel.
- Practice while learning is a must.
► Step 3: Follow a smart topic order
Once you’re done with basics, follow this path:
1. Searching & Sorting
2. Recursion & Backtracking
3. Greedy
4. Sliding Window & Two Pointers
5. Trees & Graphs
6. Dynamic Programming
7. Tries, Heaps, and Union Find
Make revision notes as you go — note down how you solved each question, what tricks worked, and how you optimized it.
► Step 4: Start giving contests (don’t wait till you’re “ready”)
Most students wait to “finish DSA” before attempting contests.
That’s a huge mistake.
Contests teach you:
- Time management under pressure
- Handling edge cases
- Thinking fast
Platforms: LeetCode Weekly/ Biweekly, Codeforces, AtCoder, etc.
And after every contest, do upsolving — solve the questions you couldn’t during the contest.
► Step 5: Revise smart
Create a “Revision Sheet” with 100 key problems you’ve solved and want to reattempt.
Every 2-3 weeks, pick problems randomly and solve again without seeing solutions.
This trains your recall + improves your clarity.
Coding Projects:👇
https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
ENJOY LEARNING 👍👍 | 573 |
| 16 | 🎓 𝗚𝗼𝗼𝗴𝗹𝗲 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝟮𝟬𝟮𝟲 🚀
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🔗 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:
https://pdlink.in/4vjLGVq
⏳ Start Learning Today & Upgrade Your Career! | 628 |
| 17 | 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://t.me/crackingthecodinginterview
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| 20 | Tools & Tech Every Developer Should Know ⚒️👨🏻💻
❯ VS Code ➟ Lightweight, Powerful Code Editor
❯ Postman ➟ API Testing, Debugging
❯ Docker ➟ App Containerization
❯ Kubernetes ➟ Scaling & Orchestrating Containers
❯ Git ➟ Version Control, Team Collaboration
❯ GitHub/GitLab ➟ Hosting Code Repos, CI/CD
❯ Figma ➟ UI/UX Design, Prototyping
❯ Jira ➟ Agile Project Management
❯ Slack/Discord ➟ Team Communication
❯ Notion ➟ Docs, Notes, Knowledge Base
❯ Trello ➟ Task Management
❯ Zsh + Oh My Zsh ➟ Advanced Terminal Experience
❯ Linux Terminal ➟ DevOps, Shell Scripting
❯ Homebrew (macOS) ➟ Package Manager
❯ Anaconda ➟ Python & Data Science Environments
❯ Pandas ➟ Data Manipulation in Python
❯ NumPy ➟ Numerical Computation
❯ Jupyter Notebooks ➟ Interactive Python Coding
❯ Chrome DevTools ➟ Web Debugging
❯ Firebase ➟ Backend as a Service
❯ Heroku ➟ Easy App Deployment
❯ Netlify ➟ Deploy Frontend Sites
❯ Vercel ➟ Full-Stack Deployment for Next.js
❯ Nginx ➟ Web Server, Load Balancer
❯ MongoDB ➟ NoSQL Database
❯ PostgreSQL ➟ Advanced Relational Database
❯ Redis ➟ Caching & Fast Storage
❯ Elasticsearch ➟ Search & Analytics Engine
❯ Sentry ➟ Error Monitoring
❯ Jenkins ➟ Automate CI/CD Pipelines
❯ AWS/GCP/Azure ➟ Cloud Services & Deployment
❯ Swagger ➟ API Documentation
❯ SASS/SCSS ➟ CSS Preprocessors
❯ Tailwind CSS ➟ Utility-First CSS Framework
React ❤️ if you found this helpful
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