Free Online Courses with Certificate | Udacity Free Courses | Eduonix | IP Cybersecurity | Coursera | Premium Certified Courses
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👉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
نمایش بیشتر
شبکه:📈 تحلیل کانال تلگرام Free Online Courses with Certificate | Udacity Free Courses | Eduonix | IP Cybersecurity | Coursera | Premium Certified Courses
کانال Free Online Courses with Certificate | Udacity Free Courses | Eduonix | IP Cybersecurity | Coursera | Premium Certified Courses (@udacityfreecourse) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 47 148 مشترک است و جایگاه 3 791 را در دسته آموزش و رتبه 7 878 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 47 148 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 21 ژوئیه, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -355 و در ۲۴ ساعت گذشته برابر 8 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 1.45% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 0.60% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 682 بازدید دریافت میکند. در اولین روز معمولاً 281 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 2 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند |--, learning, javascript, analytic, certification تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“👉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”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 22 ژوئیه, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته آموزش تبدیل کردهاند.
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پستهای کانال
7 Best GitHub Repositories to Break into Data Analytics and Data Science
If you're diving into data science or data analytics, these repositories will give you the edge you need. Check them out:
1️⃣ 100-Days-Of-ML-Code
🔗 https://github.com/Avik-Jain/100-Days-Of-ML-Code
⭐️ Stars: ~42k
2️⃣ awesome-datascience
🔗 https://github.com/academic/awesome-datascience
⭐️ Stars: ~22.7k
3️⃣ Data-Science-For-Beginners
🔗 https://github.com/microsoft/Data-Science-For-Beginners
⭐️ Stars: ~14.5k
4️⃣ data-science-interviews
🔗 https://github.com/alexeygrigorev/data-science-interviews
⭐️ Stars: ~5.8k
5️⃣ Coding and ML System Design
🔗 https://github.com/weeeBox/coding-and-ml-system-design
⭐️ Stars: ~3.5k
6️⃣ Machine Learning Interviews from MAANG
🔗 https://github.com/arunkumarpillai/Machine-Learning-Interviews
⭐️ Stars: ~8.1k
7️⃣ data-science-ipython-notebooks
🔗 https://github.com/donnemartin/data-science-ipython-notebooks
⭐️ Stars: ~27.2k
Free GitHub Resources: https://whatsapp.com/channel/0029Vawixh9IXnlk7VfY6w43
Join for more: https://t.me/datasciencefun
| 2 |  🚀 𝗔𝗜 & 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲🔥
Learn the most in-demand AI skills from scratch and strengthen your profile with industry-recognized certificates! 🎓
✅ Beginner-Friendly Courses
✅ Learn Online at Your Own Pace
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Perfect for Students, Freshers & Working Professionals looking to build a career in AI/ML. 💼
𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:-
https://pdlink.in/4phANS2
📢 Share this with your friends who want to start their AI career! | 194 |
| 3 |  🚨 6 free online courses by Harvard University, in ML, AI, and Data Science.
𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐰𝐢𝐭𝐡 𝐏𝐲𝐭𝐡𝐨𝐧
🔗 Link
𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞: 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
🔗 Link
𝐇𝐢𝐠𝐡-𝐝𝐢𝐦𝐞𝐧𝐬𝐢𝐨𝐧𝐚𝐥 𝐝𝐚𝐭𝐚 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬
🔗 Link
𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐑
🔗 Link
𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐟𝐨𝐫 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥𝐬
🔗 Link
𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐏𝐲𝐭𝐡𝐨𝐧
🔗 Link | 414 |
| 4 |  📈 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲😍
Data Analytics is one of the most in-demand skills in today’s job market 💻
✅ Beginner Friendly
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𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:-
https://pdlink.in/4wh2ugB
🎯 Don’t miss this opportunity to build high-demand skills! | 410 |
| 5 | ✔️ 10 Books to Understand How Large Language Models Function (2026)
1. Deep Learning
https://deeplearningbook.org
The definitive reference for neural networks, covering backpropagation, architectures, and foundational concepts.
2. Artificial Intelligence: A Modern Approach
https://aima.cs.berkeley.edu
A fundamental perspective on artificial intelligence as a comprehensive system.
3. Speech and Language Processing
https://web.stanford.edu/~jurafsky/slp3/
An in-depth examination of natural language processing, transformers, and linguistics.
4. Machine Learning: A Probabilistic Perspective
https://probml.github.io/pml-book/
An exploration of probabilities, statistics, and the theoretical foundations of machine learning.
5. Understanding Deep Learning
https://udlbook.github.io/udlbook/
A contemporary explanation of deep learning principles with strong intuitive insights.
6. Designing Machine Learning Systems
https://oreilly.com/library/view/designing-machine-learning/9781098107956/
Strategies for deploying models into production environments.
7. Generative Deep Learning
https://github.com/3p5ilon/ML-books/blob/main/generative-deep-learning-teaching-machines-to-paint-write-compose-and-play.pdf
Practical applications of generative models and transformer architectures.
8. Natural Language Processing with Transformers
https://dokumen.pub/natural-language-processing-with-transformers-revised-edition-1098136799-9781098136796-9781098103248.html
Methodologies for constructing natural language processing systems based on transformers.
9. Machine Learning Engineering
https://mlebook.com
Principles of machine learning engineering and operational deployment.
10. The Hundred-Page Machine Learning Book
https://themlbook.com
A highly concentrated foundational overview without extraneous detail. 📚🤖 | 555 |
| 6 |  𝗔𝗜 & 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 (𝗡𝗼 𝗖𝗼𝗱𝗶𝗻𝗴 𝗡𝗲𝗲𝗱𝗲𝗱)
Apply Now👉:- https://pdlink.in/4aYWald
By E&ICT Academy, IIT Roorkee
Batch Closing Soon - 18th July 2026 | 633 |
| 7 | 5 Free Python Courses for Data Science Beginners
1️⃣ Python for Beginners – freeCodeCamp
2️⃣ Python – Kaggle
3️⃣ Python Mini-Projects – freeCodeCamp
4️⃣ Python Tutorial – W3Schools
5️⃣ oops with Python- freeCodeCamp | 637 |
| 8 |  🚀 𝟲 𝗠𝘂𝘀𝘁-𝗧𝗮𝗸𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗼 𝗨𝗽𝗴𝗿𝗮𝗱𝗲 𝗬𝗼𝘂𝗿 𝗥𝗲𝘀𝘂𝗺𝗲 𝗙𝗢𝗥 𝗙𝗥𝗘𝗘
Make your resume stand out to recruiters without spending a single rupee
✅ 100% FREE Learning
✅ Free Certificates
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✅ Self-Paced Learning
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𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:-
https://pdlink.in/3Rmbzp1
🚀 Learn for Free. Get Certified. Upgrade Your Resume. Land Your Dream Job! | 654 |
| 9 |  𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 😍
💫 Know The Tools, Skills & Mindset to Land your first Job
💫Understand the Foundations, tools, skills & the core essentials that you need to excel in the Data Science domain.
Eligibility :- Students ,Freshers & Working Professionals
𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇 :-
https://pdlink.in/4btjs2G
( Limited Slots ..Hurry Up )
Date & Time :- 17th July 2026 , 7:00 PM | 634 |
| 10 | YouTube channels for web development languages:
𝗙𝗿𝗼𝗻𝘁𝗲𝗻𝗱 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀 & 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀
HTML/CSS 🎨 – Kevin Powell
JavaScript 🌐 – The Net Ninja
TypeScript 📘 – Academind
React ⚛️ – Traversy Media
Angular 🔺 – Academind
Vue. js 🟩 – Vue Mastery
𝗕𝗮𝗰𝗸𝗲𝗻𝗱 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀 & 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀
Node. js 🚀 – Traversy Media
PHP 🐘 – PHP Academy
Ruby on Rails 💎 – Drifting Ruby
Django (Python) 🐍 – Corey Schafer
Flask (Python) 🔥 – Pretty Printed
ASP. NET (C#) 🎯 – IAmTimCorey
𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 & 𝗗𝗲𝘃𝗢𝗽𝘀
SQL 🗄️ – DataSimplifier
MongoDB 🍃 – MongoDB Official
Docker 🐳 – TechWorld with Nana
React ❤️ for more | 602 |
| 11 |  🚀 𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 💻🔥
These FREE courses can help you learn Data Analytics, Power BI & Excel skills that companies actually hire for 🚀
✨ What you’ll learn:
✔ Excel + Power BI 📊
✔ Data Cleaning with Power Query
✔ Interactive Dashboards
✔ Modern Analytics Skills
💯 Beginner Friendly + FREE Learning
𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:-
https://pdlink.in/4tkPNyM
🎓 Perfect for Students, Freshers & Career Switchers | 636 |
| 12 | ✅ Coding Interview Acronyms You MUST Know 💻🔥
DSA → Data Structures & Algorithms
CPU → Central Processing Unit
RAM → Random Access Memory
DBMS → Database Management System
RDBMS → Relational Database Management System
ACID → Atomicity, Consistency, Isolation, Durability
OLTP → Online Transaction Processing
OLAP → Online Analytical Processing
TCP → Transmission Control Protocol
IP → Internet Protocol
DNS → Domain Name System
MVC → Model View Controller
MVVM → Model View ViewModel
SDLC → Software Development Life Cycle
CI/CD → Continuous Integration / Continuous Deployment
JWT → JSON Web Token
ORM → Object Relational Mapping
API → Application Programming Interface
REST → Representational State Transfer
SOAP → Simple Object Access Protocol
Big O → Time & Space Complexity Notation
FIFO → First In First Out
LIFO → Last In First Out
💬 Double Tap ❤️ for more! | 931 |
| 13 |  🚀 𝗧𝗼𝗽 𝟱 𝗦𝗸𝗶𝗹𝗹𝘀 𝗧𝗼 𝗠𝗮𝘀𝘁𝗲𝗿 𝗜𝗻 𝟮𝟬𝟮𝟲 – 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘! 🎓
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| 14 | ✅ 🔤 A–Z of SQL Commands 🗄️💻⚡
A – ALTER
Modify an existing table structure (add/modify/drop columns).
B – BEGIN
Start a transaction block.
C – CREATE
Create database objects like tables, views, indexes.
D – DELETE
Remove records from a table.
E – EXISTS
Check if a subquery returns any rows.
F – FETCH
Retrieve rows from a cursor.
G – GRANT
Give privileges to users.
H – HAVING
Filter aggregated results (used with GROUP BY).
I – INSERT
Add new records into a table.
J – JOIN
Combine rows from two or more tables.
K – KEY (PRIMARY KEY / FOREIGN KEY)
Define constraints for uniqueness and relationships.
L – LIMIT
Restrict number of rows returned (MySQL/PostgreSQL).
M – MERGE
Insert/update data conditionally (mainly in SQL Server/Oracle).
N – NULL
Represents missing or unknown data.
O – ORDER BY
Sort query results.
P – PROCEDURE
Stored program in the database.
Q – QUERY
Request for data (general SQL statement).
R – ROLLBACK
Undo changes in a transaction.
S – SELECT
Retrieve data from tables.
T – TRUNCATE
Remove all records from a table quickly.
U – UPDATE
Modify existing records.
V – VIEW
Virtual table based on a query.
W – WHERE
Filter records based on conditions.
X – XML PATH
Generate XML output (mainly SQL Server).
Y – YEAR()
Extract year from a date.
Z – ZONE (AT TIME ZONE)
Convert datetime to specific time zone.
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| 15 |  🚀 𝗣𝗮𝘆 𝗔𝗳𝘁𝗲𝗿 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 - 𝗟𝗮𝘂𝗻𝗰𝗵 𝗬𝗼𝘂𝗿 𝗧𝗲𝗰𝗵 𝗖𝗮𝗿𝗲𝗲𝗿
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| 16 |  🎓 𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗢𝗳𝗳𝗲𝗿𝗶𝗻𝗴 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗶𝗻 𝟮𝟬𝟮𝟲
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| 17 | FREE Resources to Learn Artificial Intelligence 🔥
* Python – python.org/doc
* Math for AI – khanacademy.org/math/statistics‑probability
* Machine Learning – scikit‑learn.org/stable
* Deep Learning – pytorch.org/tutorials
* Generative AI – google.com/ai/learn‑ai‑skills
* NLP (Natural Language Processing) – huggingface.co/learn/nlp‑course
* Reinforcement Learning – openai.com/research
* AI Ethics – resourcelist.ai/ai‑ethics
* AI Research – paperswithcode.com
* AI Projects – kaggle.com/learn/ai
* AI Learning Hub – learn.microsoft.com/en‑us/ai
* GitHub AI List – github.com/mrsaeeddev/free‑ai‑resources
Double Tap ♥️ For More | 749 |
| 18 |  𝗠𝗮𝘀𝘁𝗲𝗿 𝗧𝗵𝗲𝘀𝗲 𝗛𝗶𝗴𝗵-𝗗𝗲𝗺𝗮𝗻𝗱 𝗦𝗸𝗶𝗹𝗹𝘀 𝘁𝗼 𝗟𝗮𝗻𝗱 𝗛𝗶𝗴𝗵-𝗣𝗮𝘆𝗶𝗻𝗴 𝗝𝗼𝗯𝘀 🔥
This guide highlights 3 powerful skills that are opening doors to high-paying roles across tech and business .🎓
Perfect For
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💼 Freshers
📈 Job seekers trying to improve employability
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🚀 Start learning today. Build in-demand skills. Position yourself for better opportunities and bigger career growth. | 766 |
| 19 | 🤖 Artificial Intelligence Roadmap 🧠
|-- Fundamentals
| |-- Mathematics
| | |-- Linear Algebra
| | |-- Calculus
| | |-- Probability & Statistics
| | └─ Discrete Mathematics
| |
| |-- Programming
| | |-- Python
| | |-- R (Optional)
| | └─ Data Structures & Algorithms
| |
| └─ Machine Learning Basics
| |-- Supervised Learning
| |-- Unsupervised Learning
| |-- Reinforcement Learning
| └─ Model Evaluation & Selection
|-- Supervised_Learning
| |-- Regression
| | |-- Linear Regression
| | |-- Polynomial Regression
| | └─ Regularization Techniques
| |
| |-- Classification
| | |-- Logistic Regression
| | |-- Support Vector Machines (SVM)
| | |-- Decision Trees
| | |-- Random Forests
| | └─ Naive Bayes
| |
| └─ Model Evaluation
| |-- Metrics (Accuracy, Precision, Recall, F1-Score)
| |-- Cross-Validation
| └─ Hyperparameter Tuning
|-- Unsupervised_Learning
| |-- Clustering
| | |-- K-Means Clustering
| | |-- Hierarchical Clustering
| | └─ DBSCAN
| |
| └─ Dimensionality Reduction
| |-- Principal Component Analysis (PCA)
| └─ t-distributed Stochastic Neighbor Embedding (t-SNE)
|-- Deep_Learning
| |-- Neural Networks Basics
| | |-- Activation Functions
| | |-- Loss Functions
| | └─ Optimization Algorithms
| |
| |-- Convolutional Neural Networks (CNNs)
| | |-- Image Classification
| | └─ Object Detection
| |
| |-- Recurrent Neural Networks (RNNs)
| | |-- Sequence Modeling
| | └─ Natural Language Processing (NLP)
| |
| └─ Transformers
| |-- Attention Mechanisms
| |-- BERT
| |-- GPT
|-- Reinforcement_Learning
| |-- Markov Decision Processes (MDPs)
| |-- Q-Learning
| |-- Deep Q-Networks (DQN)
| └─ Policy Gradient Methods
|-- Natural_Language_Processing (NLP)
| |-- Text Processing Techniques
| |-- Sentiment Analysis
| |-- Topic Modeling
| |-- Machine Translation
| └─ Language Modeling
|-- Computer_Vision
| |-- Image Processing Fundamentals
| |-- Image Classification
| |-- Object Detection
| |-- Image Segmentation
| └─ Image Generation
|-- Ethical AI & Responsible AI
| |-- Bias Detection and Mitigation
| |-- Fairness in AI
| |-- Privacy Concerns
| └─ Explainable AI (XAI)
|-- Deployment & Production
| |-- Model Deployment Strategies
| |-- Cloud Platforms (AWS, Azure, GCP)
| |-- Model Monitoring
| └─ Version Control
|-- Online_Resources
| |-- Coursera
| |-- Udacity
| |-- fast.ai
| |-- Kaggle
| └─ TensorFlow, PyTorch Documentation
React ❤️ if this helped you! | 746 |
| 20 |  𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗥𝗘𝗘 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀🎓
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Explore Microsoft’s free resources. Build in-demand skills and make your profile stronger. | 608 |
