Guys, Big Announcement!
We’ve officially crossed 4 Lakh followers on this journey together — and it’s time to step up now! ❤️
I’m launching a Coding Interview Prep Series — designed for everyone from beginners to those polishing their skills for FAANG-level interviews.
This will be a structured, step-by-step journey — with short explanations, real coding examples, and mini-challenges after every topic to build real muscle memory.
Here’s what’s coming in the next few weeks:
Week 1: The Very Basics
- What is an Algorithm?
- What is Data Structure?
- Understanding Time Complexity (Big O Notation - made simple!)
- Basic Math for Coding Interviews
- Problem Solving Approach (How to break down a question)
Week 2: Arrays & Strings — Your Building Blocks
- Introduction to Arrays and Strings
- Common Operations (Insert, Delete, Search)
- Two Pointer Techniques (Easy to Medium problems)
- Sliding Window Problems (Optimization techniques)
- String Manipulation Tricks for Interviews
Week 3: Hashing & Recursion
- HashMaps and HashSets (Power tools for coders!)
- Solving Problems using Hashing
- Introduction to Recursion
- Base Case and Recursive Case (Explained like a 5-year-old)
- Classic Recursion Problems
Week 4: Linked Lists, Stacks & Queues
- Singly vs Doubly Linked List
- Stack Operations and Problems (Valid Parentheses, Min Stack)
- Queue and Deque Concepts (with real examples)
- When to Use Stack vs Queue in Interviews
Week 5: Trees & Graphs Essentials
- Binary Trees and BST Basics
- Tree Traversals (Inorder, Preorder, Postorder)
- Graph Representations (Adjacency List, Matrix)
- Breadth-First Search (BFS) and Depth-First Search (DFS) explained simply
Week 6: Sorting, Searching & Interview Patterns
- Core Sorting Algorithms (Selection, Bubble, Insertion)
- Advanced Sorting (Merge Sort, Quick Sort)
- Binary Search Patterns (Find First, Last Occurrence, etc.)
- Mastering Interview Patterns (Two Sum, Three Sum, Subarray Sum, etc.)
Week 7: Dynamic Programming & Advanced Problem Solving
- What is Dynamic Programming (DP)?
- Top-Down vs Bottom-Up Approach
- Memoization and Tabulation Explained
- Classic DP Problems (Fibonacci, 0/1 Knapsack, Longest Subsequence)
Week 8: Real-World Mock Interviews
- Solving Medium to Hard Problems
- Tackling FAANG-level Interview Questions
- Tips to Handle Pressure in Coding Rounds
- Building the Right Mindset for Success
React with ❤️ if you're ready for this new coding series
You can join our WhatsApp channel to access it for free: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
We’ve officially crossed 4 Lakh followers on this journey together — and it’s time to step up now! ❤️
I’m launching a Coding Interview Prep Series — designed for everyone from beginners to those polishing their skills for FAANG-level interviews.
This will be a structured, step-by-step journey — with short explanations, real coding examples, and mini-challenges after every topic to build real muscle memory.
Here’s what’s coming in the next few weeks:
Week 1: The Very Basics
- What is an Algorithm?
- What is Data Structure?
- Understanding Time Complexity (Big O Notation - made simple!)
- Basic Math for Coding Interviews
- Problem Solving Approach (How to break down a question)
Week 2: Arrays & Strings — Your Building Blocks
- Introduction to Arrays and Strings
- Common Operations (Insert, Delete, Search)
- Two Pointer Techniques (Easy to Medium problems)
- Sliding Window Problems (Optimization techniques)
- String Manipulation Tricks for Interviews
Week 3: Hashing & Recursion
- HashMaps and HashSets (Power tools for coders!)
- Solving Problems using Hashing
- Introduction to Recursion
- Base Case and Recursive Case (Explained like a 5-year-old)
- Classic Recursion Problems
Week 4: Linked Lists, Stacks & Queues
- Singly vs Doubly Linked List
- Stack Operations and Problems (Valid Parentheses, Min Stack)
- Queue and Deque Concepts (with real examples)
- When to Use Stack vs Queue in Interviews
Week 5: Trees & Graphs Essentials
- Binary Trees and BST Basics
- Tree Traversals (Inorder, Preorder, Postorder)
- Graph Representations (Adjacency List, Matrix)
- Breadth-First Search (BFS) and Depth-First Search (DFS) explained simply
Week 6: Sorting, Searching & Interview Patterns
- Core Sorting Algorithms (Selection, Bubble, Insertion)
- Advanced Sorting (Merge Sort, Quick Sort)
- Binary Search Patterns (Find First, Last Occurrence, etc.)
- Mastering Interview Patterns (Two Sum, Three Sum, Subarray Sum, etc.)
Week 7: Dynamic Programming & Advanced Problem Solving
- What is Dynamic Programming (DP)?
- Top-Down vs Bottom-Up Approach
- Memoization and Tabulation Explained
- Classic DP Problems (Fibonacci, 0/1 Knapsack, Longest Subsequence)
Week 8: Real-World Mock Interviews
- Solving Medium to Hard Problems
- Tackling FAANG-level Interview Questions
- Tips to Handle Pressure in Coding Rounds
- Building the Right Mindset for Success
React with ❤️ if you're ready for this new coding series
You can join our WhatsApp channel to access it for free: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
❤4👍2
🔰 Javascript cheat sheet
This is the latest Javascript cheat sheet. Save it and share with your friends.
It contain variables, data types, operators, functions, conditional statements, loops and DOM manipulation
This is the latest Javascript cheat sheet. Save it and share with your friends.
It contain variables, data types, operators, functions, conditional statements, loops and DOM manipulation
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𝗧𝗵𝗲 𝗯𝗲𝘀𝘁 𝗰𝗼𝗱𝗶𝗻𝗴 𝗹𝗲𝘀𝘀𝗼𝗻 𝘆𝗼𝘂’𝗹𝗹 𝗿𝗲𝗰𝗲𝗶𝘃𝗲 𝘁𝗼𝗱𝗮𝘆:
Master the fundamentals of programming—they are the backbone of every great software you’ll ever build.
-> Variables store your data. Know what you’re holding and why—it’s the first step to clean, readable logic.
-> Conditions & Loops shape the behavior of your code. They allow your programs to make decisions and repeat tasks—smartly and efficiently.
-> Functions are your code’s superpower. Reuse logic, stay DRY (Don’t Repeat Yourself), and build clean, modular systems.'
-> Debugging isn’t a chore—it’s a chance to become a better thinker. Every bug fixed is a lesson learned.
In a world full of users, become a creator. Code to solve, not just to build.
Learn, write, break, fix—and grow.
Always follow best practices:
- Meaningful variable names
- Writing readable, maintainable code
- Testing early and often
One bad habit can cost you hours. One good habit can save you days.
Master the fundamentals of programming—they are the backbone of every great software you’ll ever build.
-> Variables store your data. Know what you’re holding and why—it’s the first step to clean, readable logic.
-> Conditions & Loops shape the behavior of your code. They allow your programs to make decisions and repeat tasks—smartly and efficiently.
-> Functions are your code’s superpower. Reuse logic, stay DRY (Don’t Repeat Yourself), and build clean, modular systems.'
-> Debugging isn’t a chore—it’s a chance to become a better thinker. Every bug fixed is a lesson learned.
In a world full of users, become a creator. Code to solve, not just to build.
Learn, write, break, fix—and grow.
Always follow best practices:
- Meaningful variable names
- Writing readable, maintainable code
- Testing early and often
One bad habit can cost you hours. One good habit can save you days.
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Top 9 Http Methods-
GET 🧐 - Retrieve data from a resource.
HEAD 🎧 - Retrieve the headers of a resource.
POST 📮 - Submit data to a resource.
PUT 📥 - Update an existing resource or create a new resource.
DELETE 🗑️ - Remove a resource.
CONNECT 🔗 - Establish a network connection for a resource.
OPTIONS ⚙️ - Describe communication options for the target resource.
TRACE 🕵️♂️ - Retrieve a diagnostic trace of the request.
PATCH 🩹 - Apply a partial update to a resource.
GET 🧐 - Retrieve data from a resource.
HEAD 🎧 - Retrieve the headers of a resource.
POST 📮 - Submit data to a resource.
PUT 📥 - Update an existing resource or create a new resource.
DELETE 🗑️ - Remove a resource.
CONNECT 🔗 - Establish a network connection for a resource.
OPTIONS ⚙️ - Describe communication options for the target resource.
TRACE 🕵️♂️ - Retrieve a diagnostic trace of the request.
PATCH 🩹 - Apply a partial update to a resource.
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🚀 Key Skills for Aspiring Tech Specialists
📊 Data Analyst:
- Proficiency in SQL for database querying
- Advanced Excel for data manipulation
- Programming with Python or R for data analysis
- Statistical analysis to understand data trends
- Data visualization tools like Tableau or PowerBI
- Data preprocessing to clean and structure data
- Exploratory data analysis techniques
🧠 Data Scientist:
- Strong knowledge of Python and R for statistical analysis
- Machine learning for predictive modeling
- Deep understanding of mathematics and statistics
- Data wrangling to prepare data for analysis
- Big data platforms like Hadoop or Spark
- Data visualization and communication skills
- Experience with A/B testing frameworks
🏗 Data Engineer:
- Expertise in SQL and NoSQL databases
- Experience with data warehousing solutions
- ETL (Extract, Transform, Load) process knowledge
- Familiarity with big data tools (e.g., Apache Spark)
- Proficient in Python, Java, or Scala
- Knowledge of cloud services like AWS, GCP, or Azure
- Understanding of data pipeline and workflow management tools
🤖 Machine Learning Engineer:
- Proficiency in Python and libraries like scikit-learn, TensorFlow
- Solid understanding of machine learning algorithms
- Experience with neural networks and deep learning frameworks
- Ability to implement models and fine-tune their parameters
- Knowledge of software engineering best practices
- Data modeling and evaluation strategies
- Strong mathematical skills, particularly in linear algebra and calculus
🧠 Deep Learning Engineer:
- Expertise in deep learning frameworks like TensorFlow or PyTorch
- Understanding of Convolutional and Recurrent Neural Networks
- Experience with GPU computing and parallel processing
- Familiarity with computer vision and natural language processing
- Ability to handle large datasets and train complex models
- Research mindset to keep up with the latest developments in deep learning
🤯 AI Engineer:
- Solid foundation in algorithms, logic, and mathematics
- Proficiency in programming languages like Python or C++
- Experience with AI technologies including ML, neural networks, and cognitive computing
- Understanding of AI model deployment and scaling
- Knowledge of AI ethics and responsible AI practices
- Strong problem-solving and analytical skills
🔊 NLP Engineer:
- Background in linguistics and language models
- Proficiency with NLP libraries (e.g., NLTK, spaCy)
- Experience with text preprocessing and tokenization
- Understanding of sentiment analysis, text classification, and named entity recognition
- Familiarity with transformer models like BERT and GPT
- Ability to work with large text datasets and sequential data
🌟 Embrace the world of data and AI, and become the architect of tomorrow's technology!
📊 Data Analyst:
- Proficiency in SQL for database querying
- Advanced Excel for data manipulation
- Programming with Python or R for data analysis
- Statistical analysis to understand data trends
- Data visualization tools like Tableau or PowerBI
- Data preprocessing to clean and structure data
- Exploratory data analysis techniques
🧠 Data Scientist:
- Strong knowledge of Python and R for statistical analysis
- Machine learning for predictive modeling
- Deep understanding of mathematics and statistics
- Data wrangling to prepare data for analysis
- Big data platforms like Hadoop or Spark
- Data visualization and communication skills
- Experience with A/B testing frameworks
🏗 Data Engineer:
- Expertise in SQL and NoSQL databases
- Experience with data warehousing solutions
- ETL (Extract, Transform, Load) process knowledge
- Familiarity with big data tools (e.g., Apache Spark)
- Proficient in Python, Java, or Scala
- Knowledge of cloud services like AWS, GCP, or Azure
- Understanding of data pipeline and workflow management tools
🤖 Machine Learning Engineer:
- Proficiency in Python and libraries like scikit-learn, TensorFlow
- Solid understanding of machine learning algorithms
- Experience with neural networks and deep learning frameworks
- Ability to implement models and fine-tune their parameters
- Knowledge of software engineering best practices
- Data modeling and evaluation strategies
- Strong mathematical skills, particularly in linear algebra and calculus
🧠 Deep Learning Engineer:
- Expertise in deep learning frameworks like TensorFlow or PyTorch
- Understanding of Convolutional and Recurrent Neural Networks
- Experience with GPU computing and parallel processing
- Familiarity with computer vision and natural language processing
- Ability to handle large datasets and train complex models
- Research mindset to keep up with the latest developments in deep learning
🤯 AI Engineer:
- Solid foundation in algorithms, logic, and mathematics
- Proficiency in programming languages like Python or C++
- Experience with AI technologies including ML, neural networks, and cognitive computing
- Understanding of AI model deployment and scaling
- Knowledge of AI ethics and responsible AI practices
- Strong problem-solving and analytical skills
🔊 NLP Engineer:
- Background in linguistics and language models
- Proficiency with NLP libraries (e.g., NLTK, spaCy)
- Experience with text preprocessing and tokenization
- Understanding of sentiment analysis, text classification, and named entity recognition
- Familiarity with transformer models like BERT and GPT
- Ability to work with large text datasets and sequential data
🌟 Embrace the world of data and AI, and become the architect of tomorrow's technology!
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DSA (Data Structures and Algorithms) Essential Topics for Interviews
1️⃣ Arrays and Strings
Basic operations (insert, delete, update)
Two-pointer technique
Sliding window
Prefix sum
Kadane’s algorithm
Subarray problems
2️⃣ Linked List
Singly & Doubly Linked List
Reverse a linked list
Detect loop (Floyd’s Cycle)
Merge two sorted lists
Intersection of linked lists
3️⃣ Stack & Queue
Stack using array or linked list
Queue and Circular Queue
Monotonic Stack/Queue
LRU Cache (LinkedHashMap/Deque)
Infix to Postfix conversion
4️⃣ Hashing
HashMap, HashSet
Frequency counting
Two Sum problem
Group Anagrams
Longest Consecutive Sequence
5️⃣ Recursion & Backtracking
Base cases and recursive calls
Subsets, permutations
N-Queens problem
Sudoku solver
Word search
6️⃣ Trees & Binary Trees
Traversals (Inorder, Preorder, Postorder)
Height and Diameter
Balanced Binary Tree
Lowest Common Ancestor (LCA)
Serialize & Deserialize Tree
7️⃣ Binary Search Trees (BST)
Search, Insert, Delete
Validate BST
Kth smallest/largest element
Convert BST to DLL
8️⃣ Heaps & Priority Queues
Min Heap / Max Heap
Heapify
Top K elements
Merge K sorted lists
Median in a stream
9️⃣ Graphs
Representations (adjacency list/matrix)
DFS, BFS
Cycle detection (directed & undirected)
Topological Sort
Dijkstra’s & Bellman-Ford algorithm
Union-Find (Disjoint Set)
10️⃣ Dynamic Programming (DP)
0/1 Knapsack
Longest Common Subsequence
Matrix Chain Multiplication
DP on subsequences
Memoization vs Tabulation
11️⃣ Greedy Algorithms
Activity selection
Huffman coding
Fractional knapsack
Job scheduling
12️⃣ Tries
Insert and search a word
Word search
Auto-complete feature
13️⃣ Bit Manipulation
XOR, AND, OR basics
Check if power of 2
Single Number problem
Count set bits
Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
ENJOY LEARNING 👍👍
1️⃣ Arrays and Strings
Basic operations (insert, delete, update)
Two-pointer technique
Sliding window
Prefix sum
Kadane’s algorithm
Subarray problems
2️⃣ Linked List
Singly & Doubly Linked List
Reverse a linked list
Detect loop (Floyd’s Cycle)
Merge two sorted lists
Intersection of linked lists
3️⃣ Stack & Queue
Stack using array or linked list
Queue and Circular Queue
Monotonic Stack/Queue
LRU Cache (LinkedHashMap/Deque)
Infix to Postfix conversion
4️⃣ Hashing
HashMap, HashSet
Frequency counting
Two Sum problem
Group Anagrams
Longest Consecutive Sequence
5️⃣ Recursion & Backtracking
Base cases and recursive calls
Subsets, permutations
N-Queens problem
Sudoku solver
Word search
6️⃣ Trees & Binary Trees
Traversals (Inorder, Preorder, Postorder)
Height and Diameter
Balanced Binary Tree
Lowest Common Ancestor (LCA)
Serialize & Deserialize Tree
7️⃣ Binary Search Trees (BST)
Search, Insert, Delete
Validate BST
Kth smallest/largest element
Convert BST to DLL
8️⃣ Heaps & Priority Queues
Min Heap / Max Heap
Heapify
Top K elements
Merge K sorted lists
Median in a stream
9️⃣ Graphs
Representations (adjacency list/matrix)
DFS, BFS
Cycle detection (directed & undirected)
Topological Sort
Dijkstra’s & Bellman-Ford algorithm
Union-Find (Disjoint Set)
10️⃣ Dynamic Programming (DP)
0/1 Knapsack
Longest Common Subsequence
Matrix Chain Multiplication
DP on subsequences
Memoization vs Tabulation
11️⃣ Greedy Algorithms
Activity selection
Huffman coding
Fractional knapsack
Job scheduling
12️⃣ Tries
Insert and search a word
Word search
Auto-complete feature
13️⃣ Bit Manipulation
XOR, AND, OR basics
Check if power of 2
Single Number problem
Count set bits
Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
ENJOY LEARNING 👍👍
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Evolution of Programming Languages 🖥️
🔰Programming Languages🔰
1. JAVA:
More than 85% android apps are created using JAVA. It is also used in big (big means big) websites. It is a portable programming language which makes it easy to use on multi platforms.
2. Java Script:
Its a browser/client side language. It makes the webpage more interactive. Like for example when you enter a comment on Facebook then the whole page doesn’t load., just that comment is added. This kind of functionalities are added into webpages with JavaScript. Javascript brought about a revolution in webapps.
3. Assembly Language:
The most low level programming language because its nothing more than machine code written in human readable form. Its hard to write and you need to have deep understanding of computers to use this because you are really talking with it. Its very fast in terms of execution.
4. C:
Its a low level language too that’s why its fast. It is used to program operating system, computer games and software which need to be fast. It is hard to write but gives you more control of your computer.
5. C++ :
Its C with more features and those features make it more complex.
6. Perl:
A language which was developed to create small scripts easily . Programming in Perl is easy and efficient but the programs are comparatively slower.
7. Python:
Perl was made better and named Python. Its easy, efficient and flexible. You can automate things with python in a go.
8. Ruby:
Its similar to Python but it became popular when they created a web application development framework named Rails which lets developers to write their web application conveniently.
9. HTML and CSS:
HTML and CSS are languages not programming languages because they are just used display things on a website. They do not do any actual processing. HTML is used to create the basic structure of the website and then CSS is used to make it look good.
10. PHP:
It is used to process things in a website. It is server-sided language as it doesn’t get executed in user browser, but on the server. It can be used to generate dynamic webpage content.
11. SQL:
This is not exactly a programming language. It is used to interact with databases.
➡️ This list could be long because there are too many programming language but I introduced you to the popular ones.
❓Which Language Should Be Your First Programming Language?
✅ Suggestions..
1. Getting Started
Learn HTML & CSS. They are easy and will give you a basic idea of how programming works. You will be able to create your own webpages. After HTML you can go with PHP and SQL, so will have a good grasp over web designing and then you can go with python, C or Java. I assure you that PHP, HTML and SQL will be definitely useful in your hacking journey.
2. Understanding Computer And Programming Better
C..The classic C! C is one of the most foundational languages. If you learn C, you will have a deep knowledge of Computers and you will have a greater understanding of programming too, that will make you a better programmer. You will spend most of your time compiling though (just trying to crack a joke).
3. Too Eager To Create Programs?
Python! Python is very easy to learn and you can create a program which does something instead of programming calculators. Well Python doesn’t start you from the basics but with if you know python, you will be able to understand other languages better. One benefit of python is that you don’t need to compile the script to run it, just write one and run it.
React ❤️ for more
🔰Programming Languages🔰
1. JAVA:
More than 85% android apps are created using JAVA. It is also used in big (big means big) websites. It is a portable programming language which makes it easy to use on multi platforms.
2. Java Script:
Its a browser/client side language. It makes the webpage more interactive. Like for example when you enter a comment on Facebook then the whole page doesn’t load., just that comment is added. This kind of functionalities are added into webpages with JavaScript. Javascript brought about a revolution in webapps.
3. Assembly Language:
The most low level programming language because its nothing more than machine code written in human readable form. Its hard to write and you need to have deep understanding of computers to use this because you are really talking with it. Its very fast in terms of execution.
4. C:
Its a low level language too that’s why its fast. It is used to program operating system, computer games and software which need to be fast. It is hard to write but gives you more control of your computer.
5. C++ :
Its C with more features and those features make it more complex.
6. Perl:
A language which was developed to create small scripts easily . Programming in Perl is easy and efficient but the programs are comparatively slower.
7. Python:
Perl was made better and named Python. Its easy, efficient and flexible. You can automate things with python in a go.
8. Ruby:
Its similar to Python but it became popular when they created a web application development framework named Rails which lets developers to write their web application conveniently.
9. HTML and CSS:
HTML and CSS are languages not programming languages because they are just used display things on a website. They do not do any actual processing. HTML is used to create the basic structure of the website and then CSS is used to make it look good.
10. PHP:
It is used to process things in a website. It is server-sided language as it doesn’t get executed in user browser, but on the server. It can be used to generate dynamic webpage content.
11. SQL:
This is not exactly a programming language. It is used to interact with databases.
➡️ This list could be long because there are too many programming language but I introduced you to the popular ones.
❓Which Language Should Be Your First Programming Language?
✅ Suggestions..
1. Getting Started
Learn HTML & CSS. They are easy and will give you a basic idea of how programming works. You will be able to create your own webpages. After HTML you can go with PHP and SQL, so will have a good grasp over web designing and then you can go with python, C or Java. I assure you that PHP, HTML and SQL will be definitely useful in your hacking journey.
2. Understanding Computer And Programming Better
C..The classic C! C is one of the most foundational languages. If you learn C, you will have a deep knowledge of Computers and you will have a greater understanding of programming too, that will make you a better programmer. You will spend most of your time compiling though (just trying to crack a joke).
3. Too Eager To Create Programs?
Python! Python is very easy to learn and you can create a program which does something instead of programming calculators. Well Python doesn’t start you from the basics but with if you know python, you will be able to understand other languages better. One benefit of python is that you don’t need to compile the script to run it, just write one and run it.
React ❤️ for more
❤4👍4
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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
Coding Jobs: https://whatsapp.com/channel/0029VatL9a22kNFtPtLApJ2L
❯ 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
Coding Jobs: https://whatsapp.com/channel/0029VatL9a22kNFtPtLApJ2L
❤5👍2