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 46 545 مشترک است و جایگاه 3 822 را در دسته آموزش و رتبه 7 942 را در منطقه الهند دارد.
📊 شاخص‌های مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 46 545 مشترک جذب کرده است.
بر اساس آخرین داده‌ها در تاریخ 09 اکتبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -273 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 1.68% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 0.54% واکنش نسبت به کل مشترکان کسب می‌کند.
- دسترسی پست‌ها: هر پست به طور میانگین 783 بازدید دریافت می‌کند. در اولین روز معمولاً 250 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 10 اکتبر, 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.
46 545
مشترکین
-824 ساعت
-487 روز
-27330 روز
در حال بارگیری داده...
کانال‌های مشابه
هیچ داده‌ای
مشکلی وجود دارد؟ لطفاً صفحه را تازه کنید یا با مدیر پشتیبانی ما تماس بگیرید.
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| تاریخ | رشد مشترکین | اشارات | کانال‌ها | |
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پست‌های کانال
🇮🇳 𝗚𝗢𝗩𝗘𝗥𝗡𝗠𝗘𝗡𝗧 𝗢𝗙 𝗜𝗡𝗗𝗜𝗔 — 𝗔𝗜𝗖𝗧𝗘 𝗜𝗡𝗧𝗘𝗥𝗡𝗦𝗛𝗜𝗣𝗦 𝟮𝟬𝟮𝟲 🚀
Students and freshers can explore internship opportunities through the AICTE Internship Portal across multiple domains:
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🔗 𝗖𝗵𝗲𝗰𝗸 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀 & 𝗔𝗽𝗽𝗹𝘆 👇
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📢 Share this opportunity with your friends and classmates!
| 2 |  🎓 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘄𝗶𝘁𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲𝘀! 🚀🔥
Upgrade your resume with Microsoft learning opportunities. Explore courses covering some of today's most in-demand tech skills!
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🔥 Share with friends looking to upskill in 2026! | 374 |
| 3 |  🚀𝗣𝗮𝘆 𝗔𝗳𝘁𝗲𝗿 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 | 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮 𝗙𝘂𝗹𝗹𝘀𝘁𝗮𝗰𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗪𝗜𝘁𝗵 𝗚𝗲𝗻𝗔𝗜
Start a high-paying tech career—even without prior coding experience
🏆 𝗣𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀:
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| 4 |  𝗠𝗮𝘀𝘁𝗲𝗿 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘! 🔥
Learn Power BI through these FREE learning resources
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📊 Interactive Dashboards
📈 Data Visualization
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𝗦𝘁𝗮𝗿𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘
https://pdlink.in/4hznwlu
💫Perfect for Students • Freshers • Data Analyst Aspirants • Working Professionals | 467 |
| 5 | ✅ Programming Important Terms You Should Know 💻🚀
Programming is the backbone of tech, and knowing the right terms can boost your learning and career.
🧠 Core Programming Concepts
• Programming: Writing instructions for a computer to perform tasks.
• Algorithm: Step-by-step procedure to solve a problem.
• Flowchart: Visual representation of a program’s logic.
• Syntax: Rules that define how code must be written.
• Compilation: Converting source code into machine code.
• Interpretation: Executing code line-by-line without compiling first.
⚙️ Basic Programming Elements
• Variable: Storage location for data.
• Constant: Fixed value that cannot change.
• Data Type: Type of data (int, float, string, boolean).
• Operator: Symbol performing operations (+, -, **, /, ==).
• Expression: Combination of variables, operators, and values.
• Statement: A single line of instruction in a program.
🔄 Control Flow Concepts
• Conditional Statements: Execute code based on conditions (if, else).
• Loops: Repeat a block of code (for, while).
• Break Statement: Exit a loop early.
• Continue Statement: Skip the current loop iteration.
• Switch Case: Multi-condition decision structure.
📦 Functions & Modular Programming
• Function: Reusable block of code performing a task.
• Parameter: Input passed to a function.
• Return Value: Output returned by a function.
• Module: File containing reusable functions or classes.
• Library: Collection of pre-written code.
🧩 Object-Oriented Programming (OOP)
• Class: Blueprint for creating objects.
• Object: Instance of a class.
• Encapsulation: Bundling data and methods together.
• Inheritance: One class acquiring properties of another.
• Polymorphism: Same function behaving differently in different contexts.
• Abstraction: Hiding complex implementation details.
📊 Data Structures
• Array: Collection of elements stored sequentially.
• List: Ordered collection that can change size.
• Stack: Last In First Out (LIFO) structure.
• Queue: First In First Out (FIFO) structure.
• Hash Table / Dictionary: Key-value data storage.
• Tree: Hierarchical data structure.
• Graph: Network of connected nodes.
⚡ Advanced Programming Concepts
• Recursion: Function calling itself.
• Concurrency: Multiple tasks running simultaneously.
• Multithreading: Multiple threads within a program.
• Memory Management: Allocation and deallocation of memory.
• Garbage Collection: Automatic memory cleanup.
• Exception Handling: Handling runtime errors using try, catch, except.
🌐 Software Development Concepts
• Framework: Pre-built structure for building applications.
• API: Interface allowing different software to communicate.
• Version Control: Tracking code changes using tools like Git.
• Debugging: Finding and fixing code errors.
• Testing: Verifying that code works correctly.
Double Tap ♥️ For Detailed Explanation of Each Topic | 1 010 |
| 6 |  𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗧𝗼 𝗟𝗲𝗮𝗿𝗻 𝗔𝗜 𝗶𝗻 𝟮𝟬𝟮𝟲🚀
Explore 6 free resources covering AI fundamentals, tools, deep learning, research and real-world applications.
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🔗 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 👇
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| 7 | ✅ FREE Tools to Learn Coding & Practice Skills 💻🚀
Perfect for beginners, students & self-taught devs!
1️⃣ freeCodeCamp
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🛠 Bonus Tip: Use AI tools like ChatGPT or Claude to debug, learn, and generate starter code on the fly.
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| 8 |  🎓 𝗛𝗔𝗥𝗩𝗔𝗥𝗗 𝗨𝗡𝗜𝗩𝗘𝗥𝗦𝗜𝗧𝗬 𝗙𝗥𝗘𝗘 𝗢𝗡𝗟𝗜𝗡𝗘 𝗖𝗢𝗨𝗥𝗦𝗘𝗦 😍
Dreaming of learning from one of the world’s most prestigious universities? Explore Harvard’s online courses and build valuable, career-ready skills from home!
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| 9 | Important Topics You Should Know to Learn Python 👇
Lists, Strings, Tuples, Dictionaries, Sets – Learn the core data structures in Python.
Boolean, Arithmetic, and Comparison Operators – Understand how Python evaluates conditions.
Operations on Data Structures – Append, delete, insert, reverse, sort, and manipulate collections efficiently.
Reading and Extracting Data – Learn how to access, modify, and extract values from lists and dictionaries.
Conditions and Loops – Master if, elif, else, for, while, break, and continue statements.
Range and Enumerate – Efficiently loop through sequences with indexing.
Functions – Create functions with and without parameters, and understand *args and **kwargs.
Classes & Object-Oriented Programming – Work with init methods, global/local variables, and concepts like inheritance and encapsulation.
File Handling – Read, write, and manipulate files in Python.
Free Resources to learn Python👇👇
👉 Free Python course by Google
https://developers.google.com/edu/python
👉 Freecodecamp Python course
https://www.freecodecamp.org/learn/data-analysis-with-python/#
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https://bit.ly/3FOOQHh
👉Python Cheatsheet
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👉 Kaggle
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https://kaggle.com/learn/python
👉 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹𝘀 𝗶𝗻 𝗣𝘆𝘁𝗵𝗼𝗻
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👉 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻
https://freecodecamp.org/learn/scientific-computing-with-python/
👉 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻
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👉 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻
https://freecodecamp.org/learn/machine-learning-with-python/
ENJOY LEARNING 👍👍 | 728 |
| 10 |  𝗟𝗲𝘃𝗲𝗹 𝗨𝗽 𝗬𝗼𝘂𝗿 𝗦𝗸𝗶𝗹𝗹𝘀 𝘄𝗶𝘁𝗵 𝗧𝗵𝗲𝘀𝗲 𝗚𝗮𝗺𝗲-𝗖𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝗖𝗼𝘂𝗿𝘀𝗲𝘀!
Looking to learn practical, in-demand skills? These courses cover Generative AI, Cybersecurity, AI tools and Digital Marketing.
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𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝘁𝗵𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 :-
https://pdlink.in/4z3vOYU
Save this post and share with your friends | 624 |
| 11 | SQL (Structured Query Language) is a standard programming language used to manage and manipulate relational databases. Here are some key concepts to understand the basics of SQL:
1. Database: A database is a structured collection of data organized in tables, which consist of rows and columns.
2. Table: A table is a collection of related data organized in rows and columns. Each row represents a record, and each column represents a specific attribute or field.
3. Query: A SQL query is a request for data or information from a database. Queries are used to retrieve, insert, update, or delete data in a database.
4. CRUD Operations: CRUD stands for Create, Read, Update, and Delete. These are the basic operations performed on data in a database using SQL:
- Create (INSERT): Adds new records to a table.
- Read (SELECT): Retrieves data from one or more tables.
- Update (UPDATE): Modifies existing records in a table.
- Delete (DELETE): Removes records from a table.
5. Data Types: SQL supports various data types to define the type of data that can be stored in each column of a table, such as integer, text, date, and decimal.
6. Constraints: Constraints are rules enforced on data columns to ensure data integrity and consistency. Common constraints include:
- Primary Key: Uniquely identifies each record in a table.
- Foreign Key: Establishes a relationship between two tables.
- Unique: Ensures that all values in a column are unique.
- Not Null: Specifies that a column cannot contain NULL values.
7. Joins: Joins are used to combine rows from two or more tables based on a related column between them. Common types of joins include INNER JOIN, LEFT JOIN (or LEFT OUTER JOIN), RIGHT JOIN (or RIGHT OUTER JOIN), and FULL JOIN (or FULL OUTER JOIN).
8. Aggregate Functions: SQL provides aggregate functions to perform calculations on sets of values. Common aggregate functions include SUM, AVG, COUNT, MIN, and MAX.
9. Group By: The GROUP BY clause is used to group rows that have the same values into summary rows. It is often used with aggregate functions to perform calculations on grouped data.
10. Order By: The ORDER BY clause is used to sort the result set of a query based on one or more columns in ascending or descending order.
Understanding these basic concepts of SQL will help you write queries to interact with databases effectively. Practice writing SQL queries and experimenting with different commands to become proficient in using SQL for database management and manipulation.
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| 18 | 🔥 A-Z Data Science Road Map
1. 📊 Math and Statistics
- Descriptive statistics
- Probability
- Distributions
- Hypothesis testing
- Correlation
- Regression basics
2. 🐍 Python Basics
- Variables
- Data types
- Loops
- Conditionals
- Functions
- Modules
3. 🐼 Core Python for Data Science
- NumPy
- Pandas
- DataFrames
- Missing values
- Merging
- GroupBy
- Visualization
4. 📈 Data Visualization
- Matplotlib
- Seaborn
- Plotly
- Histograms, boxplots, heatmaps
- Dashboards
5. 🧹 Data Wrangling
- Cleaning
- Outlier detection
- Feature engineering
- Encoding
- Scaling
6. 🔍 Exploratory Data Analysis (EDA)
- Univariate analysis
- Bivariate analysis
- Stats summary
- Correlation analysis
7. 💾 SQL for Data Science
- SELECT
- WHERE
- GROUP BY
- JOINS
- CTEs
- Window functions
8. 🤖 Machine Learning Basics
- Supervised vs unsupervised
- Train test split
- Cross validation
- Metrics
9. 🎯 Supervised Learning
- Linear regression
- Logistic regression
- Decision trees
- Random forest
- Gradient boosting
- SVM
- KNN
10. 💡 Unsupervised Learning
- K-Means
- Hierarchical clustering
- PCA
- Dimensionality reduction
11. ⭐ Model Evaluation
- Accuracy
- Precision
- Recall
- F1
- ROC AUC
- MSE, RMSE, MAE
12. 🛠️ Feature Engineering
- One hot encoding
- Binning
- Scaling
- Interaction terms
13. ⏳ Time Series
- Trends
- Seasonality
- ARIMA
- Prophet
- Forecasting steps
14. 🧠 Deep Learning Basics
- Neural networks
- Activation functions
- Loss functions
- Backprop basics
15. 🚀 Deep Learning Libraries
- TensorFlow
- Keras
- PyTorch
16. 💬 NLP
- Tokenization
- Stemming
- Lemmatization
- TF-IDF
- Word embeddings
17. 🌐 Big Data Tools
- Hadoop
- Spark
- PySpark
18. ⚙️ Data Engineering Basics
- ETL
- Pipelines
- Scheduling
- Cloud concepts
19. ☁️ Cloud Platforms
- AWS (S3, Lambda, SageMaker)
- GCP (BigQuery)
- Azure ML
20. 📦 MLOps
- Model deployment
- CI/CD
- Monitoring
- Docker
- APIs (FastAPI, Flask)
21. 📊 Dashboards
- Power BI
- Tableau
- Streamlit
22. 🏗️ Real-World Projects
- Classification
- Regression
- Time series
- NLP
- Recommendation systems
23. 🧑💻 Version Control
- Git
- GitHub
- Branching
- Pull requests
24. 🗣️ Soft Skills
- Problem framing
- Business communication
- Storytelling
25. 📝 Interview Prep
- SQL practice
- Python challenges
- ML theory
- Case studies
------------------- END -------------------
✅ Good Resources To Learn Data Science
1. 📚 Documentation
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- NumPy docs: numpy.org
- Scikit-learn docs: scikit-learn.org
- PyTorch: pytorch.org
2. 📺 Free Learning Channels
- FreeCodeCamp: youtube.com/c/FreeCodeCamp
- Data School: youtube.com/dataschool
- Krish Naik: YouTube
- WhatsApp channel
- StatQuest: YouTube
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