Learn JavaScript in 14 Days:
Part 1:
๐ป Day 1 - Learn JavaScript Basics:
Start with understanding variables, data types, and basic syntax.
๐ Day 2 - Master Operators and Expressions:
Get comfortable using arithmetic, comparison, and logical operators.
โ๏ธ Day 3 - Dive into Conditional Statements:
Learn how to use if, else if, else, and switch for decision-making.
โป๏ธ Day 4 - Explore Loops:
Understand how for, while, and do-while loops work.
๐ง Day 5 - Work with Functions:
Learn how to define and call functions, pass parameters, and return values.
๐ฆ Day 6 - Introduction to Arrays:
Explore how to create arrays and manipulate them with methods like push(), pop(), and map().
๐ Day 7 - Object Basics:
Learn how to create and work with JavaScript objects, properties, and methods.
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Thanks All For Joiningโค๏ธ๐
Part 1:
๐ป Day 1 - Learn JavaScript Basics:
Start with understanding variables, data types, and basic syntax.
๐ Day 2 - Master Operators and Expressions:
Get comfortable using arithmetic, comparison, and logical operators.
โ๏ธ Day 3 - Dive into Conditional Statements:
Learn how to use if, else if, else, and switch for decision-making.
โป๏ธ Day 4 - Explore Loops:
Understand how for, while, and do-while loops work.
๐ง Day 5 - Work with Functions:
Learn how to define and call functions, pass parameters, and return values.
๐ฆ Day 6 - Introduction to Arrays:
Explore how to create arrays and manipulate them with methods like push(), pop(), and map().
๐ Day 7 - Object Basics:
Learn how to create and work with JavaScript objects, properties, and methods.
Like for part 2 โค๏ธ
Do not forget to React โค๏ธ to this Message for More Content Like this
Thanks All For Joiningโค๏ธ๐
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Basics of Programming ๐โ
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10 Machine Learning Concepts You Must Know
โ Supervised vs Unsupervised Learning โ Understand the foundation of ML tasks
โ Bias-Variance Tradeoff โ Balance underfitting and overfitting
โ Feature Engineering โ The secret sauce to boost model performance
โ Train-Test Split & Cross-Validation โ Evaluate models the right way
โ Confusion Matrix โ Measure model accuracy, precision, recall, and F1
โ Gradient Descent โ The algorithm behind learning in most models
โ Regularization (L1/L2) โ Prevent overfitting by penalizing complexity
โ Decision Trees & Random Forests โ Interpretable and powerful models
โ Support Vector Machines โ Great for classification with clear boundaries
โ Neural Networks โ The foundation of deep learning
React with โค๏ธ for detailed explained
Data Science & Machine Learning Resources: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D
ENJOY LEARNING ๐๐
โ Supervised vs Unsupervised Learning โ Understand the foundation of ML tasks
โ Bias-Variance Tradeoff โ Balance underfitting and overfitting
โ Feature Engineering โ The secret sauce to boost model performance
โ Train-Test Split & Cross-Validation โ Evaluate models the right way
โ Confusion Matrix โ Measure model accuracy, precision, recall, and F1
โ Gradient Descent โ The algorithm behind learning in most models
โ Regularization (L1/L2) โ Prevent overfitting by penalizing complexity
โ Decision Trees & Random Forests โ Interpretable and powerful models
โ Support Vector Machines โ Great for classification with clear boundaries
โ Neural Networks โ The foundation of deep learning
React with โค๏ธ for detailed explained
Data Science & Machine Learning Resources: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D
ENJOY LEARNING ๐๐
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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.
๐ Python Interview ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐
https://t.iss.one/dsabooks
๐ ๐ฃ๐ฟ๐ฒ๐บ๐ถ๐๐บ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐ : https://topmate.io/coding/914624
๐ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ: https://whatsapp.com/channel/0029VaxbzNFCxoAmYgiGTL3Z
Join What's app channel for jobs updates: t.iss.one/getjobss
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.
๐ Python Interview ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐
https://t.iss.one/dsabooks
๐ ๐ฃ๐ฟ๐ฒ๐บ๐ถ๐๐บ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐ : https://topmate.io/coding/914624
๐ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ: https://whatsapp.com/channel/0029VaxbzNFCxoAmYgiGTL3Z
Join What's app channel for jobs updates: t.iss.one/getjobss
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Machine Learning Algorithm
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SQL Cheatsheet ๐
This SQL cheatsheet is designed to be your quick reference guide for SQL programming. Whether youโre a beginner learning how to query databases or an experienced developer looking for a handy resource, this cheatsheet covers essential SQL topics.
1. Database Basics
-
-
2. Tables
- Create Table:
- Drop Table:
- Alter Table:
3. Insert Data
-
4. Select Queries
- Basic Select:
- Select Specific Columns:
- Select with Condition:
5. Update Data
-
6. Delete Data
-
7. Joins
- Inner Join:
- Left Join:
- Right Join:
8. Aggregations
- Count:
- Sum:
- Group By:
9. Sorting & Limiting
- Order By:
- Limit Results:
10. Indexes
- Create Index:
- Drop Index:
11. Subqueries
-
12. Views
- Create View:
- Drop View:
Here you can find SQL Interview Resources๐
https://t.iss.one/DataSimplifier
Share with credits: https://t.iss.one/sqlspecialist
Hope it helps :)
This SQL cheatsheet is designed to be your quick reference guide for SQL programming. Whether youโre a beginner learning how to query databases or an experienced developer looking for a handy resource, this cheatsheet covers essential SQL topics.
1. Database Basics
-
CREATE DATABASE db_name;-
USE db_name;2. Tables
- Create Table:
CREATE TABLE table_name (col1 datatype, col2 datatype);- Drop Table:
DROP TABLE table_name;- Alter Table:
ALTER TABLE table_name ADD column_name datatype;3. Insert Data
-
INSERT INTO table_name (col1, col2) VALUES (val1, val2);4. Select Queries
- Basic Select:
SELECT * FROM table_name;- Select Specific Columns:
SELECT col1, col2 FROM table_name;- Select with Condition:
SELECT * FROM table_name WHERE condition;5. Update Data
-
UPDATE table_name SET col1 = value1 WHERE condition;6. Delete Data
-
DELETE FROM table_name WHERE condition;7. Joins
- Inner Join:
SELECT * FROM table1 INNER JOIN table2 ON table1.col = table2.col;- Left Join:
SELECT * FROM table1 LEFT JOIN table2 ON table1.col = table2.col;- Right Join:
SELECT * FROM table1 RIGHT JOIN table2 ON table1.col = table2.col;8. Aggregations
- Count:
SELECT COUNT(*) FROM table_name;- Sum:
SELECT SUM(col) FROM table_name;- Group By:
SELECT col, COUNT(*) FROM table_name GROUP BY col;9. Sorting & Limiting
- Order By:
SELECT * FROM table_name ORDER BY col ASC|DESC;- Limit Results:
SELECT * FROM table_name LIMIT n;10. Indexes
- Create Index:
CREATE INDEX idx_name ON table_name (col);- Drop Index:
DROP INDEX idx_name;11. Subqueries
-
SELECT * FROM table_name WHERE col IN (SELECT col FROM other_table);12. Views
- Create View:
CREATE VIEW view_name AS SELECT * FROM table_name;- Drop View:
DROP VIEW view_name;Here you can find SQL Interview Resources๐
https://t.iss.one/DataSimplifier
Share with credits: https://t.iss.one/sqlspecialist
Hope it helps :)
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