๐๐๐ญ๐ ๐๐ญ๐ซ๐ฎ๐๐ญ๐ฎ๐ซ๐๐ฌ : ๐๐ฑ๐ฉ๐ฅ๐จ๐ซ๐ ๐ฅ๐ข๐ฌ๐ญ๐ฌ, ๐ญ๐ฎ๐ฉ๐ฅ๐๐ฌ, ๐๐ง๐ ๐๐ข๐๐ญ๐ข๐จ๐ง๐๐ซ๐ข๐๐ฌ
๐๐ข๐ฌ๐ญ๐ฌ:
- Lists are ordered collections of items.
- They are mutable, meaning you can change their content after creation.
- You can have duplicate values in a list.
- Lists are defined using square brackets [ ].
Example:
my_list = [1, 2, 3, 'apple', 'banana', 'cherry']
๐๐ฎ๐ฉ๐ฅ๐๐ฌ:
- Tuples are ordered collections of items, similar to lists.
- However, they are immutable, meaning once created, their content cannot be changed.
- Tuples are defined using parentheses ( ).
- You can have duplicate values in a tuple.
Example:
my_tuple = (1, 2, 3, 'apple', 'banana', 'cherry')
๐๐ข๐๐ญ๐ข๐จ๐ง๐๐ซ๐ข๐๐ฌ:
- Dictionaries are unordered collections of items that are stored as key-value pairs.
- They are mutable.
- Dictionaries are defined using curly braces { }.
- Each key in a dictionary must be unique, but the values can be duplicated.
Example:
my_dict = {'name': 'John', 'age': 30, 'city': 'New York'}
I have curated the best interview resources to crack Python Interviews ๐๐
https://topmate.io/coding/898340
Hope you'll like it
Like this post if you need more resources like this ๐โค๏ธ
๐๐ข๐ฌ๐ญ๐ฌ:
- Lists are ordered collections of items.
- They are mutable, meaning you can change their content after creation.
- You can have duplicate values in a list.
- Lists are defined using square brackets [ ].
Example:
my_list = [1, 2, 3, 'apple', 'banana', 'cherry']
๐๐ฎ๐ฉ๐ฅ๐๐ฌ:
- Tuples are ordered collections of items, similar to lists.
- However, they are immutable, meaning once created, their content cannot be changed.
- Tuples are defined using parentheses ( ).
- You can have duplicate values in a tuple.
Example:
my_tuple = (1, 2, 3, 'apple', 'banana', 'cherry')
๐๐ข๐๐ญ๐ข๐จ๐ง๐๐ซ๐ข๐๐ฌ:
- Dictionaries are unordered collections of items that are stored as key-value pairs.
- They are mutable.
- Dictionaries are defined using curly braces { }.
- Each key in a dictionary must be unique, but the values can be duplicated.
Example:
my_dict = {'name': 'John', 'age': 30, 'city': 'New York'}
I have curated the best interview resources to crack Python Interviews ๐๐
https://topmate.io/coding/898340
Hope you'll like it
Like this post if you need more resources like this ๐โค๏ธ
๐3
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
๐3โค1๐ฅ1
Typical java interview questions sorted by experience
Junior
* Name some of the characteristics of OO programming languages
* What are the access modifiers you know? What does each one do?
* What is the difference between overriding and overloading a method in Java?
* Whatโs the difference between an Interface and an abstract class?
* Can an Interface extend another Interface?
* What does the static word mean in Java?
* Can a static method be overridden in Java?
* What is Polymorphism? What about Inheritance?
* Can a constructor be inherited?
* Do objects get passed by reference or value in Java? Elaborate on that.
* Whatโs the difference between using == and .equals on a string?
* What is the hashCode() and equals() used for?
* What does the interface Serializable do? What about Parcelable in Android?
* Why are Array and ArrayList different? When would you use each?
* Whatโs the difference between an Integer and int?
* What is a ThreadPool? Is it better than using several โsimpleโ threads?
* What the difference between local, instance and class variables?
Mid
* What is reflection?
* What is dependency injection? Can you name a few libraries? (Have you used any?)
* What are strong, soft and weak references in Java?
* What does the keyword synchronized mean?
* Can you have โmemory leaksโ on Java?
* Do you need to set references to null on Java/Android?
* What does it means to say that a String is immutable?
* What are transient and volatile modifiers?
* What is the finalize() method?
* How does the try{} finally{} works?
* What is the difference between instantiation and initialisation of an object?
* When is a static block run?
* Why are Generics are used in Java?
* Can you mention the design patterns you know? Which of those do you normally use?
* Can you mention some types of testing you know?
Senior
* How does Integer.parseInt() works?
* Do you know what is the โdouble check lockingโ problem?
* Do you know the difference between StringBuffer and StringBuilder?
* How is a StringBuilder implemented to avoid the immutable string allocation problem?
* What does Class.forName method do?
* What is Autoboxing and Unboxing?
* Whatโs the difference between an Enumeration and an Iterator?
* What is the difference between fail-fast and fail safe in Java?
* What is PermGen in Java?
* What is a Java priority queue?
* *s performance influenced by using the same number in different types: Int, Double and Float?
* What is the Java Heap?
* What is daemon thread?
* Can a dead thread be restarted?
Source: medium.
Junior
* Name some of the characteristics of OO programming languages
* What are the access modifiers you know? What does each one do?
* What is the difference between overriding and overloading a method in Java?
* Whatโs the difference between an Interface and an abstract class?
* Can an Interface extend another Interface?
* What does the static word mean in Java?
* Can a static method be overridden in Java?
* What is Polymorphism? What about Inheritance?
* Can a constructor be inherited?
* Do objects get passed by reference or value in Java? Elaborate on that.
* Whatโs the difference between using == and .equals on a string?
* What is the hashCode() and equals() used for?
* What does the interface Serializable do? What about Parcelable in Android?
* Why are Array and ArrayList different? When would you use each?
* Whatโs the difference between an Integer and int?
* What is a ThreadPool? Is it better than using several โsimpleโ threads?
* What the difference between local, instance and class variables?
Mid
* What is reflection?
* What is dependency injection? Can you name a few libraries? (Have you used any?)
* What are strong, soft and weak references in Java?
* What does the keyword synchronized mean?
* Can you have โmemory leaksโ on Java?
* Do you need to set references to null on Java/Android?
* What does it means to say that a String is immutable?
* What are transient and volatile modifiers?
* What is the finalize() method?
* How does the try{} finally{} works?
* What is the difference between instantiation and initialisation of an object?
* When is a static block run?
* Why are Generics are used in Java?
* Can you mention the design patterns you know? Which of those do you normally use?
* Can you mention some types of testing you know?
Senior
* How does Integer.parseInt() works?
* Do you know what is the โdouble check lockingโ problem?
* Do you know the difference between StringBuffer and StringBuilder?
* How is a StringBuilder implemented to avoid the immutable string allocation problem?
* What does Class.forName method do?
* What is Autoboxing and Unboxing?
* Whatโs the difference between an Enumeration and an Iterator?
* What is the difference between fail-fast and fail safe in Java?
* What is PermGen in Java?
* What is a Java priority queue?
* *s performance influenced by using the same number in different types: Int, Double and Float?
* What is the Java Heap?
* What is daemon thread?
* Can a dead thread be restarted?
Source: medium.
โค3๐2
Top 10 VS Code Extensions ๐๐จ๐ปโ๐ป
โจ Prettier - Clean, consistent auto-formatting
๐งฉ Bracket Pair Colorizer - Color-coded brackets
โก Live Server - Auto-refresh websites as you code
๐ธ CodeSnap - Snap stunning code screenshots
๐ Aura Theme - Sleek dark mode for your editor
๐๏ธ Material Icon Theme - Colorful file icons, easy nav
๐ค GitHub Copilot - AI code buddy with smart suggestions
๐ ๏ธ ESLint - Catch and fix errors on the fly
๐ Tabnine - Speed up coding with AI autocomplete
๐ Path Intellisense - Auto path imports, zero hassle
React โค๏ธ for more like this
โจ Prettier - Clean, consistent auto-formatting
๐งฉ Bracket Pair Colorizer - Color-coded brackets
โก Live Server - Auto-refresh websites as you code
๐ธ CodeSnap - Snap stunning code screenshots
๐ Aura Theme - Sleek dark mode for your editor
๐๏ธ Material Icon Theme - Colorful file icons, easy nav
๐ค GitHub Copilot - AI code buddy with smart suggestions
๐ ๏ธ ESLint - Catch and fix errors on the fly
๐ Tabnine - Speed up coding with AI autocomplete
๐ Path Intellisense - Auto path imports, zero hassle
React โค๏ธ for more like this
๐4โค3
5 beginner-to-intermediate projects you can build if you're learning Programming & AI
1. AI-Powered Chatbot (Using Python)
Build a simple chatbot that can understand and respond to user inputs. You can use rule-based logic at first, and then explore NLP with libraries like NLTK or spaCy.
Skills: Python, NLP, Regex, Basic ML
Ideas to include:
- Greeting and small talk
- FAQ-based responses
- Sentiment-based replies
You can also integrate it with Telegram or Discord bot
2. Movie Recommendation System
Create a recommendation system based on movie genre, user preferences, or ratings using collaborative filtering or content-based filtering.
Skills: Python, Pandas, Scikit-learn
Ideas to include:
- Use TMDB or MovieLens datasets
- Add filtering by genre
- Include cosine similarity logic
3. AI-Powered Resume Parser
Upload a PDF or DOCX resume and let your app extract name, skills, experience, education, and output it in a structured format.
Skills: Python, NLP, Regex, Flask
Ideas to include:
- File upload option
- Named Entity Recognition (NER) with spaCy
- Save extracted info into a CSV/Database
4. To-Do App with Smart Suggestions
A regular to-do list but with an AI assistant that suggests tasks based on previous entries (e.g., you often add "buy milk" on Mondays? It suggests it.)
Skills: JavaScript/React + AI API (like OpenAI or custom model)
Ideas to include:
- CRUD functionality
- Natural Language date/time parsing
- AI suggestion module
5. Fake News Detector
Given a news headline or article, predict if itโs fake or real. A great application of classification problems.
Skills: Python, NLP, ML (Logistic Regression or TF-IDF + Naive Bayes)
Ideas to include:
- Use datasets from Kaggle
- Preprocess with stopwords, lemmatization
- Display prediction result with probability
React with โค๏ธ if you want me to share source code or free resources to build these projects
Coding Projects: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
Software Developer Jobs: https://whatsapp.com/channel/0029VatL9a22kNFtPtLApJ2L
ENJOY LEARNING ๐๐
1. AI-Powered Chatbot (Using Python)
Build a simple chatbot that can understand and respond to user inputs. You can use rule-based logic at first, and then explore NLP with libraries like NLTK or spaCy.
Skills: Python, NLP, Regex, Basic ML
Ideas to include:
- Greeting and small talk
- FAQ-based responses
- Sentiment-based replies
You can also integrate it with Telegram or Discord bot
2. Movie Recommendation System
Create a recommendation system based on movie genre, user preferences, or ratings using collaborative filtering or content-based filtering.
Skills: Python, Pandas, Scikit-learn
Ideas to include:
- Use TMDB or MovieLens datasets
- Add filtering by genre
- Include cosine similarity logic
3. AI-Powered Resume Parser
Upload a PDF or DOCX resume and let your app extract name, skills, experience, education, and output it in a structured format.
Skills: Python, NLP, Regex, Flask
Ideas to include:
- File upload option
- Named Entity Recognition (NER) with spaCy
- Save extracted info into a CSV/Database
4. To-Do App with Smart Suggestions
A regular to-do list but with an AI assistant that suggests tasks based on previous entries (e.g., you often add "buy milk" on Mondays? It suggests it.)
Skills: JavaScript/React + AI API (like OpenAI or custom model)
Ideas to include:
- CRUD functionality
- Natural Language date/time parsing
- AI suggestion module
5. Fake News Detector
Given a news headline or article, predict if itโs fake or real. A great application of classification problems.
Skills: Python, NLP, ML (Logistic Regression or TF-IDF + Naive Bayes)
Ideas to include:
- Use datasets from Kaggle
- Preprocess with stopwords, lemmatization
- Display prediction result with probability
React with โค๏ธ if you want me to share source code or free resources to build these projects
Coding Projects: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
Software Developer Jobs: https://whatsapp.com/channel/0029VatL9a22kNFtPtLApJ2L
ENJOY LEARNING ๐๐
โค4๐3
Here's the AโZ list of essential Python programming concepts
A - Arguments
B - Built-in Functions
C - Comprehensions
D - Dictionaries
E - Exceptions
F - Functions
G - Generators
H - Higher-Order Functions
I - Iterators
J - Join Method
K - Keyword Arguments
L - Lambda Functions
M - Modules
N - NoneType
O - Object-Oriented Programming
P - PEP8
Q - Queue
R - Range Function
S - Sets
T - Tuples
U - Unpacking
V - Variables
W - While Loop
X - XOR Operation
Y - Yield Keyword
Z - Zip Function
These concepts are foundational to mastering Python and writing clean, efficient, and Pythonic code.
Credits: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
A - Arguments
B - Built-in Functions
C - Comprehensions
D - Dictionaries
E - Exceptions
F - Functions
G - Generators
H - Higher-Order Functions
I - Iterators
J - Join Method
K - Keyword Arguments
L - Lambda Functions
M - Modules
N - NoneType
O - Object-Oriented Programming
P - PEP8
Q - Queue
R - Range Function
S - Sets
T - Tuples
U - Unpacking
V - Variables
W - While Loop
X - XOR Operation
Y - Yield Keyword
Z - Zip Function
These concepts are foundational to mastering Python and writing clean, efficient, and Pythonic code.
Credits: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
โค4๐4
What is Docker ?
1 โข Development
Lets say You created an Application
And that's working fine in your machine
2 โข Production
But in Production it doesn't work properly
Developers experince it a lot
3 โข That is when the Developer's famous words are spoken
Client - Your application is not working ๐ก
Developer - It's working on my Machine ๐
4 โข The Reason could be due to:
โข Dependencies
โข Libraries and versions
โข Framework
โข OS Level features
โข Microservices
That the developers machine has but not there in the production environment
5 โข DOCKER
We need a standardized way to package the application with its dependencies and deploy it on any environment.
Docker is a tool designed to make it easier to create, deploy, and run applications by using containers.
So it will always work the same regardless of its environment
6 โข How Does Docker Work?
Docker packages an application and all its dependencies in a virtual container that can run on any Linux server.
7 โข Each container runs as an isolated process in the user space and take up less space than regular VMs due to their layered architecture.
1 โข Development
Lets say You created an Application
And that's working fine in your machine
2 โข Production
But in Production it doesn't work properly
Developers experince it a lot
3 โข That is when the Developer's famous words are spoken
Client - Your application is not working ๐ก
Developer - It's working on my Machine ๐
4 โข The Reason could be due to:
โข Dependencies
โข Libraries and versions
โข Framework
โข OS Level features
โข Microservices
That the developers machine has but not there in the production environment
5 โข DOCKER
We need a standardized way to package the application with its dependencies and deploy it on any environment.
Docker is a tool designed to make it easier to create, deploy, and run applications by using containers.
So it will always work the same regardless of its environment
6 โข How Does Docker Work?
Docker packages an application and all its dependencies in a virtual container that can run on any Linux server.
7 โข Each container runs as an isolated process in the user space and take up less space than regular VMs due to their layered architecture.
๐7
Want to get started with System design interview preparation, start with these ๐
1. Learn to understand requirements
2. Learn the difference between horizontal and vertical scaling.
3. Study latency and throughput trade-offs and optimization techniques.
4. Understand the CAP Theorem (Consistency, Availability, Partition Tolerance).
5. Learn HTTP/HTTPS protocols, request-response lifecycle, and headers.
6. Understand DNS and how domain resolution works.
7. Study load balancers, their types (Layer 4 and Layer 7), and algorithms.
8. Learn about CDNs, their use cases, and caching strategies.
9. Understand SQL databases (ACID properties, normalization) and NoSQL types (keyโvalue, document, graph).
10. Study caching tools (Redis, Memcached) and strategies (write-through, write-back, eviction policies).
11. Learn about blob storage systems like S3 or Google Cloud Storage.
12. Study sharding and horizontal partitioning of databases.
13. Understand replication (leaderโfollower, multi-leader) and consistency models.
14. Learn failover mechanisms like active-passive and active-active setups.
15. Study message queues like RabbitMQ, Kafka, and SQS.
16. Understand consensus algorithms such as Paxos and Raft.
17. Learn event-driven architectures, Pub/Sub models, and event sourcing.
18. Study distributed transactions (two-phase commit, sagas).
19. Learn rate-limiting techniques (token bucket, leaky bucket algorithms).
20. Study API design principles for REST, GraphQL, and gRPC.
21. Understand microservices architecture, communication, and trade-offs with monoliths.
22. Learn authentication and authorization methods (OAuth, JWT, SSO).
23. Study metrics collection tools like Prometheus or Datadog.
24. Understand logging systems (e.g., ELK stack) and tracing tools (OpenTelemetry, Jaeger).
25.Learn about encryption (data at rest and in transit) and rate-limiting for security.
26. And then practise the most commonly asked questions like URL shorteners, chat systems, ride-sharing apps, search engines, video streaming, and e-commerce websites
Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
1. Learn to understand requirements
2. Learn the difference between horizontal and vertical scaling.
3. Study latency and throughput trade-offs and optimization techniques.
4. Understand the CAP Theorem (Consistency, Availability, Partition Tolerance).
5. Learn HTTP/HTTPS protocols, request-response lifecycle, and headers.
6. Understand DNS and how domain resolution works.
7. Study load balancers, their types (Layer 4 and Layer 7), and algorithms.
8. Learn about CDNs, their use cases, and caching strategies.
9. Understand SQL databases (ACID properties, normalization) and NoSQL types (keyโvalue, document, graph).
10. Study caching tools (Redis, Memcached) and strategies (write-through, write-back, eviction policies).
11. Learn about blob storage systems like S3 or Google Cloud Storage.
12. Study sharding and horizontal partitioning of databases.
13. Understand replication (leaderโfollower, multi-leader) and consistency models.
14. Learn failover mechanisms like active-passive and active-active setups.
15. Study message queues like RabbitMQ, Kafka, and SQS.
16. Understand consensus algorithms such as Paxos and Raft.
17. Learn event-driven architectures, Pub/Sub models, and event sourcing.
18. Study distributed transactions (two-phase commit, sagas).
19. Learn rate-limiting techniques (token bucket, leaky bucket algorithms).
20. Study API design principles for REST, GraphQL, and gRPC.
21. Understand microservices architecture, communication, and trade-offs with monoliths.
22. Learn authentication and authorization methods (OAuth, JWT, SSO).
23. Study metrics collection tools like Prometheus or Datadog.
24. Understand logging systems (e.g., ELK stack) and tracing tools (OpenTelemetry, Jaeger).
25.Learn about encryption (data at rest and in transit) and rate-limiting for security.
26. And then practise the most commonly asked questions like URL shorteners, chat systems, ride-sharing apps, search engines, video streaming, and e-commerce websites
Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
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15 Best Project Ideas for Backend Development : ๐ ๏ธ๐
๐ Beginner Level :
1. ๐ฆ RESTful API for a To-Do App
2. ๐ Contact Form Backend
3. ๐๏ธ File Upload Service
4. ๐ฌ Email Subscription Service
5. ๐งพ Notes App Backend
๐ Intermediate Level :
6. ๐ E-commerce Backend with Cart & Orders
7. ๐ Authentication System (JWT/OAuth)
8. ๐งโ๐คโ๐ง User Management API
9. ๐งพ Invoice Generator API
10. ๐ง Blog CMS Backend
๐ Advanced Level :
11. ๐ง AI Chatbot Backend Integration
12. ๐ Real-Time Stock Tracker using WebSockets
13. ๐ง Music Streaming Server
14. ๐ฌ Real-Time Chat Server
15. โ๏ธ Microservices Architecture for Large Apps
Here you can find more Coding Project Ideas: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
Web Development Jobs: https://whatsapp.com/channel/0029Vb1raTiDjiOias5ARu2p
JavaScript Resources: https://whatsapp.com/channel/0029VavR9OxLtOjJTXrZNi32
ENJOY LEARNING ๐๐
๐ Beginner Level :
1. ๐ฆ RESTful API for a To-Do App
2. ๐ Contact Form Backend
3. ๐๏ธ File Upload Service
4. ๐ฌ Email Subscription Service
5. ๐งพ Notes App Backend
๐ Intermediate Level :
6. ๐ E-commerce Backend with Cart & Orders
7. ๐ Authentication System (JWT/OAuth)
8. ๐งโ๐คโ๐ง User Management API
9. ๐งพ Invoice Generator API
10. ๐ง Blog CMS Backend
๐ Advanced Level :
11. ๐ง AI Chatbot Backend Integration
12. ๐ Real-Time Stock Tracker using WebSockets
13. ๐ง Music Streaming Server
14. ๐ฌ Real-Time Chat Server
15. โ๏ธ Microservices Architecture for Large Apps
Here you can find more Coding Project Ideas: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
Web Development Jobs: https://whatsapp.com/channel/0029Vb1raTiDjiOias5ARu2p
JavaScript Resources: https://whatsapp.com/channel/0029VavR9OxLtOjJTXrZNi32
ENJOY LEARNING ๐๐
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If I wanted to get my opportunity to interview at Google or Amazon for SDE roles in the next 6-8 monthsโฆ
Hereโs exactly how Iโd approach it (Iโve taught this to 100s of students and followed it myself to land interviews at 3+ FAANGs):
โบ Step 1: Learn to Code (from scratch, even if youโre 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 โ pick one)
- FreeCodeCamp on YouTube for beginner-friendly lectures
- Key rule: Donโt just watch. Code along with the video line by line.
Time required: 30โ40 days to get good with loops, conditions, syntax.
โบ Step 2: Start with DSA before jumping to development
Why?
- 90% of tech interviews in top companies focus on Data Structures & Algorithms
- Youโll need time to master it, so start early.
Start with:
- Arrays โ Linked List โ Stacks โ Queues
- You can follow the DSA videos on my channel.
- Practice while learning is a must.
โบ Step 3: Follow a smart topic order
Once youโre 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 โ note down how you solved each question, what tricks worked, and how you optimized it.
โบ Step 4: Start giving contests (donโt wait till youโre โreadyโ)
Most students wait to โfinish DSAโ before attempting contests.
Thatโs 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 โ solve the questions you couldnโt during the contest.
โบ Step 5: Revise smart
Create a โRevision Sheetโ with 100 key problems youโve 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:๐
https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
ENJOY LEARNING ๐๐
Hereโs exactly how Iโd approach it (Iโve taught this to 100s of students and followed it myself to land interviews at 3+ FAANGs):
โบ Step 1: Learn to Code (from scratch, even if youโre 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 โ pick one)
- FreeCodeCamp on YouTube for beginner-friendly lectures
- Key rule: Donโt just watch. Code along with the video line by line.
Time required: 30โ40 days to get good with loops, conditions, syntax.
โบ Step 2: Start with DSA before jumping to development
Why?
- 90% of tech interviews in top companies focus on Data Structures & Algorithms
- Youโll need time to master it, so start early.
Start with:
- Arrays โ Linked List โ Stacks โ Queues
- You can follow the DSA videos on my channel.
- Practice while learning is a must.
โบ Step 3: Follow a smart topic order
Once youโre 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 โ note down how you solved each question, what tricks worked, and how you optimized it.
โบ Step 4: Start giving contests (donโt wait till youโre โreadyโ)
Most students wait to โfinish DSAโ before attempting contests.
Thatโs 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 โ solve the questions you couldnโt during the contest.
โบ Step 5: Revise smart
Create a โRevision Sheetโ with 100 key problems youโve 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:๐
https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
ENJOY LEARNING ๐๐
๐5
Most people learn SQL just enough to pull some data. But if you really understand it, you can analyze massive datasets without touching Excel or Python.
Here are 8 game-changing SQL concepts that will make you a data pro:
๐
1. Stop pulling raw data. Start pulling insights.
The biggest mistake? Running a query that gives you everything and then filtering it later.
Good analysts donโt pull raw data. They shape the data before it even reaches them.
2. โSELECT โ is a rookie move.
Pulling all columns is lazy and slow.
A pro only selects what they need.
โ๏ธ Fewer columns = Faster queries
โ๏ธ Less noise = Clearer insights
The more precise your query, the less time you waste cleaning data.
3. GROUP BY is your best friend.
You donโt need 100,000 rows of transactions. What you need is:
โ๏ธ Sales per region
โ๏ธ Average order size per customer
โ๏ธ Number of signups per month
Grouping turns chaotic data into useful summaries.
4. Joins = Connecting the dots.
Your most important data is split across multiple tables.
Want to know how much each customer spent? You need to join:
โ๏ธ Customer info
โ๏ธ Order history
โ๏ธ Payments
Joins = unlocking hidden insights.
5. Window functions will blow your mind.
They let you:
โ๏ธ Rank customers by total purchases
โ๏ธ Calculate rolling averages
โ๏ธ Compare each row to the overall trend
Itโs like pivot tables, but way more powerful.
6. CTEs will save you from spaghetti SQL.
Instead of writing a 50-line nested query, break it into steps.
CTEs (Common Table Expressions) make your SQL:
โ๏ธ Easier to read
โ๏ธ Easier to debug
โ๏ธ Reusable
Good SQL is clean SQL.
7. Indexes = Speed.
If your queries take forever, your database is probably doing unnecessary work.
Indexes help databases find data faster.
If you work with large datasets, this is a game changer.
SQL isnโt just about pulling data. Itโs about analyzing, transforming, and optimizing it.
Master these 7 concepts, and youโll never look at SQL the same way again.
Join us on WhatsApp: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Here are 8 game-changing SQL concepts that will make you a data pro:
๐
1. Stop pulling raw data. Start pulling insights.
The biggest mistake? Running a query that gives you everything and then filtering it later.
Good analysts donโt pull raw data. They shape the data before it even reaches them.
2. โSELECT โ is a rookie move.
Pulling all columns is lazy and slow.
A pro only selects what they need.
โ๏ธ Fewer columns = Faster queries
โ๏ธ Less noise = Clearer insights
The more precise your query, the less time you waste cleaning data.
3. GROUP BY is your best friend.
You donโt need 100,000 rows of transactions. What you need is:
โ๏ธ Sales per region
โ๏ธ Average order size per customer
โ๏ธ Number of signups per month
Grouping turns chaotic data into useful summaries.
4. Joins = Connecting the dots.
Your most important data is split across multiple tables.
Want to know how much each customer spent? You need to join:
โ๏ธ Customer info
โ๏ธ Order history
โ๏ธ Payments
Joins = unlocking hidden insights.
5. Window functions will blow your mind.
They let you:
โ๏ธ Rank customers by total purchases
โ๏ธ Calculate rolling averages
โ๏ธ Compare each row to the overall trend
Itโs like pivot tables, but way more powerful.
6. CTEs will save you from spaghetti SQL.
Instead of writing a 50-line nested query, break it into steps.
CTEs (Common Table Expressions) make your SQL:
โ๏ธ Easier to read
โ๏ธ Easier to debug
โ๏ธ Reusable
Good SQL is clean SQL.
7. Indexes = Speed.
If your queries take forever, your database is probably doing unnecessary work.
Indexes help databases find data faster.
If you work with large datasets, this is a game changer.
SQL isnโt just about pulling data. Itโs about analyzing, transforming, and optimizing it.
Master these 7 concepts, and youโll never look at SQL the same way again.
Join us on WhatsApp: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
๐5
Best Programming Languages for Hacking:
1. Python
Itโs no surprise that Python tops our list. Referred to as the defacto hacking programing language, Python has indeed played a significant role in the writing of hacking scripts, exploits, and malicious programs.
2. C
C is critical language in the Hacking community. Most of the popular operating systems we have today run on a foundation of C language.
C is an excellent resource in reverse engineering of software and applications. These enable hackers to understand the working of a system or an app.
3. Javascript
For quite some time, Javascript(JS) was a client-side scripting language. With the release of Node.js, Javascript now supports backend development. To hackers, this means a broader field of exploitation.
4. PHP
For a long time now, PHP has dominated the backend of most websites and web applications.
If you are into web hacking, then getting your hands on PHP would be of great advantage.
5. C++
Have you ever thought of cracking corporate(paid) software? Here is your answer. The hacker community has significantly implemented C++ programming language to remove trial periods on paid software and even the operating system.
6. SQL
SQL โ Standard Query Language. It is a programming language used to organize, add, retrieve, remove, or edit data in a database. A lot of systems store their data in databases such as MySQL, MS SQL, and PostgreSQL.
Using SQL, hackers can perform an attack known as SQL injection, which will enable them to access confidential information.
7. Java
Despite what many may say, a lot of backdoor exploits in systems are written in Java. It has also been used by hackers to perform identity thefts, create botnets, and even perform malicious activities on the client system undetected.
1. Python
Itโs no surprise that Python tops our list. Referred to as the defacto hacking programing language, Python has indeed played a significant role in the writing of hacking scripts, exploits, and malicious programs.
2. C
C is critical language in the Hacking community. Most of the popular operating systems we have today run on a foundation of C language.
C is an excellent resource in reverse engineering of software and applications. These enable hackers to understand the working of a system or an app.
3. Javascript
For quite some time, Javascript(JS) was a client-side scripting language. With the release of Node.js, Javascript now supports backend development. To hackers, this means a broader field of exploitation.
4. PHP
For a long time now, PHP has dominated the backend of most websites and web applications.
If you are into web hacking, then getting your hands on PHP would be of great advantage.
5. C++
Have you ever thought of cracking corporate(paid) software? Here is your answer. The hacker community has significantly implemented C++ programming language to remove trial periods on paid software and even the operating system.
6. SQL
SQL โ Standard Query Language. It is a programming language used to organize, add, retrieve, remove, or edit data in a database. A lot of systems store their data in databases such as MySQL, MS SQL, and PostgreSQL.
Using SQL, hackers can perform an attack known as SQL injection, which will enable them to access confidential information.
7. Java
Despite what many may say, a lot of backdoor exploits in systems are written in Java. It has also been used by hackers to perform identity thefts, create botnets, and even perform malicious activities on the client system undetected.
๐1
Interview Coding Patterns
We'll cover multiple patterns asked in coding interviews. These patterns help you recognize how to approach different types of coding problems smartly โ instead of solving each from scratch.
Weโll divide this into multiple parts โ starting from basic and gradually going toward advanced.
Here's what weโll cover in this section:
1. Stock Buy & Sell (Single Transaction)
2. Stock Buy & Sell (Multiple Transactions)
3. Kadaneโs Algorithm (Max Subarray)
4. Sliding Window (Fixed + Variable Size)
5. Two Pointer Technique
6. Prefix Sum
7. HashMap-Based Pattern
8. Binary Search Variants
9. Backtracking Basics
10. Recursion to DP Conversion
11. Sorting-Based Tricks
12. Greedy Patterns
13. Frequency Maps and Counters
14. Stacks and Queues Based Patterns
15. Substring & Subarray Techniques
Access it for free here
๐๐
https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1629
We'll cover multiple patterns asked in coding interviews. These patterns help you recognize how to approach different types of coding problems smartly โ instead of solving each from scratch.
Weโll divide this into multiple parts โ starting from basic and gradually going toward advanced.
Here's what weโll cover in this section:
1. Stock Buy & Sell (Single Transaction)
2. Stock Buy & Sell (Multiple Transactions)
3. Kadaneโs Algorithm (Max Subarray)
4. Sliding Window (Fixed + Variable Size)
5. Two Pointer Technique
6. Prefix Sum
7. HashMap-Based Pattern
8. Binary Search Variants
9. Backtracking Basics
10. Recursion to DP Conversion
11. Sorting-Based Tricks
12. Greedy Patterns
13. Frequency Maps and Counters
14. Stacks and Queues Based Patterns
15. Substring & Subarray Techniques
Access it for free here
๐๐
https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1629
โค2๐2
7 Powerful AI Project Ideas to Build Your Portfolio
โ AI Chatbot โ Create a custom chatbot using NLP libraries like spaCy, Rasa, or GPT API
โ Fake News Detector โ Classify real vs fake news using Natural Language Processing and machine learning
โ Image Classifier โ Build a CNN to identify objects (e.g., cats vs dogs, handwritten digits)
โ Resume Screener โ Automate shortlisting candidates using keyword extraction and scoring logic
โ Text Summarizer โ Generate short summaries from long documents using Transformer models
โ AI-Powered Recommendation System โ Suggest products, movies, or courses based on user preferences
โ Voice Assistant Clone โ Build a basic version of Alexa or Siri with speech recognition and response generation
These projects are not just for learningโtheyโll also impress recruiters!
#ai #projects
โ AI Chatbot โ Create a custom chatbot using NLP libraries like spaCy, Rasa, or GPT API
โ Fake News Detector โ Classify real vs fake news using Natural Language Processing and machine learning
โ Image Classifier โ Build a CNN to identify objects (e.g., cats vs dogs, handwritten digits)
โ Resume Screener โ Automate shortlisting candidates using keyword extraction and scoring logic
โ Text Summarizer โ Generate short summaries from long documents using Transformer models
โ AI-Powered Recommendation System โ Suggest products, movies, or courses based on user preferences
โ Voice Assistant Clone โ Build a basic version of Alexa or Siri with speech recognition and response generation
These projects are not just for learningโtheyโll also impress recruiters!
#ai #projects
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