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SQL Learning plan in 2025 |-- Week 1: Introduction to SQL |   |-- SQL Basics |   |   |-- What is SQL? |   |   |-- History and Evolution of SQL |   |   |-- Relational Databases |   |-- Setting up for SQL |   |   |-- Installing MySQL/PostgreSQL |   |   |-- Setting up a Database |   |   |-- Basic SQL Syntax |   |-- First SQL Queries |   |   |-- SELECT Statements |   |   |-- WHERE Clauses |   |   |-- Basic Filtering | |-- Week 2: Intermediate SQL |   |-- Advanced SELECT Queries |   |   |-- ORDER BY |   |   |-- LIMIT |   |   |-- Aliases |   |-- Joining Tables |   |   |-- INNER JOIN |   |   |-- LEFT JOIN |   |   |-- RIGHT JOIN |   |   |-- FULL OUTER JOIN |   |-- Aggregations |   |   |-- COUNT, SUM, AVG, MIN, MAX |   |   |-- GROUP BY |   |   |-- HAVING Clauses | |-- Week 3: Advanced SQL Techniques |   |-- Subqueries |   |   |-- Basic Subqueries |   |   |-- Correlated Subqueries |   |-- Window Functions |   |   |-- ROW_NUMBER, RANK, DENSE_RANK |   |   |-- NTILE, LEAD, LAG |   |-- Advanced Joins |   |   |-- Self Joins |   |   |-- Cross Joins |   |-- Data Types and Functions |   |   |-- Date Functions |   |   |-- String Functions |   |   |-- Numeric Functions | |-- Week 4: Database Design and Normalization |   |-- Database Design Principles |   |   |-- ER Diagrams |   |   |-- Relationships and Cardinality |   |-- Normalization |   |   |-- First Normal Form (1NF) |   |   |-- Second Normal Form (2NF) |   |   |-- Third Normal Form (3NF) |   |-- Indexes and Performance Tuning |   |   |-- Creating Indexes |   |   |-- Understanding Execution Plans |   |   |-- Optimizing Queries | |-- Week 5: Stored Procedures and Functions |   |-- Stored Procedures |   |   |-- Creating Stored Procedures |   |   |-- Parameters in Stored Procedures |   |   |-- Error Handling |   |-- Functions |   |   |-- Scalar Functions |   |   |-- Table-Valued Functions |   |   |-- System Functions | |-- Week 6: Transactions and Concurrency |   |-- Transactions |   |   |-- ACID Properties |   |   |-- COMMIT and ROLLBACK |   |   |-- Savepoints |   |-- Concurrency Control |   |   |-- Locking Mechanisms |   |   |-- Isolation Levels |   |   |-- Deadlocks and How to Avoid Them | |-- Week 7-8: Advanced SQL Topics |   |-- Triggers |   |   |-- Creating and Using Triggers |   |   |-- AFTER and BEFORE Triggers |   |   |-- INSTEAD OF Triggers |   |-- Views |   |   |-- Creating Views |   |   |-- Updating Views |   |   |-- Indexed Views |   |-- Security |   |   |-- User Management |   |   |-- Roles and Permissions |   |   |-- SQL Injection Prevention | |-- Week 9-11: Real-world Applications and Projects |   |-- Capstone Project |   |   |-- Designing a Database Schema |   |   |-- Implementing the Schema |   |   |-- Writing Complex Queries |   |   |-- Optimizing and Tuning |   |-- ETL Processes |   |   |-- Data Extraction |   |   |-- Data Transformation |   |   |-- Data Loading |   |-- Data Analysis and Reporting |   |   |-- Creating Reports |   |   |-- Data Visualization with SQL |   |   |-- Integration with BI Tools | |-- Week 12: Post-Project Learning |   |-- Database Administration |   |   |-- Backup and Restore |   |   |-- Maintenance Plans |   |   |-- Performance Monitoring |   |-- SQL in the Cloud |   |   |-- AWS RDS |   |   |-- Google Cloud SQL |   |   |-- Azure SQL Database |   |-- Continuing Education |   |   |-- Advanced SQL Topics |   |   |-- Research Papers |   |   |-- New Developments in SQL | |-- Resources and Community |   |-- Online Courses (Coursera, Udacity) |   |-- Books (SQL for Data Analysis, Learning SQL) |   |-- SQL Blogs and Resources |   |-- GitHub Repositories Like this post if you need more 👍❤️ Hope it helps :)

Hidden Code for Android ⭐️ ❌*#06#-IMEI number the ❌*#0*#-Enter the service menu ❌*#*#4636#*#*-Phone information, usage statistics and battery ❌*#*#34971539#*#*-Detailed camera information 🌟*#*#273282*255*663282*#*#*-Immediate backup of all media files ❌*#*#197328640#*#*-Enable test mode for service ❌*#*#232339#*#*-Wireless LAN tests ❌*#*#0842#*#*-Backlight/vibration test ❌*#*#2664#*#*-Test the touch screen ❌*#*#1111#*#*-FTA software version (1234 in the same code will give PDA and Firmware version) ❌*#12580*369#-Software and hardware info ❌*#9090#-Diagnostic configuration ❌*#872564#-USB logging control ❌*#9900#-System dump mode ❌*#301279#-HSDPA/HSUPA Control Menu ❌*#7465625#-View phone lock status ❌*#*#7780#*#*-Reset the/data partition to factory state ❌*2767*3855#-Format device to factory state (will delete everything on the phone) ❌##7764726-Hidden service ⭐️ Give Reactions 🙌

🆒Complete Roadmap to Become Bug Hunter ⁉️ 📈 1. Learn the Basics of Web Security - Study OWASP Top 10: These are the most critical security risks for web applications. Learn about vulnerabilities like XSS, SQLi, Broken Access Control, etc. - Understand HTTP and APIs: Know how HTTP works (requests, responses, status codes, etc.) and get familiar with how APIs are built and secured. - Learn How Web Apps Work: Understand the basic architecture of web applications (frontend, backend, databases). 📈 2. Start Bug Bounty Hunting - Join Platforms: Sign up on platforms like [HackerOne], [Bugcrowd], or [Open Bug Bounty]. - Participate in Programs: Look for beginner-friendly programs or public bug bounty programs with clear scope and guidelines. - Read Reports: Study public write-ups from experienced hunters to see how they approach finding and exploiting vulnerabilities. 📈 3. Hone Your Vulnerability HuTo become a successful bug bounty hunter, focus on a structured learning path and skill-building process. Here’s a simplified roadmap to get you started: - Learn Burp Suite: This is the most common tool for web vulnerability hunting. Start with the free version and learn to use it effectively for manual testing. - Automate with Scripts and Tools: Learn to automate some tasks using tools like ffuf, sqlmap, and nmap to help with enumeration and scanning. - Master Exploitation Techniques : Focus on exploiting bugs like IDOR (Insecure Direct Object Reference), CSRF (Cross-Site Request Forgery), and RCE (Remote Code Execution). 📈4. Practice Continuously - Try Labs and CTFs : Practice on platforms like [TryHackMe] and [Hack The Box]. These provide hands-on challenges to sharpen your skills. - Bug Bounty Platforms: Actively participate in bug bounty platforms and hunt for bugs in real-world applications. 📈 5. Document Your Findings - Write Clear Reports: When you find a bug, ensure your report is clear, concise, and provides steps to reproduce the vulnerability - Share Write-ups: Writing about your findings on platforms like Medium or starting a blog will help you build a reputation in the community. 📈6. Stay Updated - Follow Researchers: Keep up with the latest techniques and tools by following well-known bug bounty hunters on Twitter or subscribing to security blogs. - Experiment with New Tools: New tools and techniques emerge regularly, so stay up-to-date by experimenting with the latest tools in your hunts. 📈 7. Keep Patience and Perseverance - Bug bounty hunting can be competitive and time-consuming. The key to success is persistence and constantly learning from both your failures and successes. This was the Full Guide to Become Bug Hunter 🎉 ☄️ Give 💯+ Reactions

DSA INTERVIEW QUESTIONS AND ANSWERS 1. What is the difference between file structure and storage structure? The difference lies in the memory area accessed. Storage structure refers to the data structure in the memory of the computer system, whereas file structure represents the storage structure in the auxiliary memory. 2. Are linked lists considered linear or non-linear Data Structures? Linked lists are considered both linear and non-linear data structures depending upon the application they are used for. When used for access strategies, it is considered as a linear data-structure. When used for data storage, it is considered a non-linear data structure. 3. How do you reference all of the elements in a one-dimension array? All of the elements in a one-dimension array can be referenced using an indexed loop as the array subscript so that the counter runs from 0 to the array size minus one. 4. What are dynamic Data Structures? Name a few. They are collections of data in memory that expand and contract to grow or shrink in size as a program runs. This enables the programmer to control exactly how much memory is to be utilized.Examples are the dynamic array, linked list, stack, queue, and heap. 5. What is a Dequeue? It is a double-ended queue, or a data structure, where the elements can be inserted or deleted at both ends (FRONT and REAR). 6. What operations can be performed on queues? enqueue() adds an element to the end of the queue dequeue() removes an element from the front of the queue init() is used for initializing the queue isEmpty tests for whether or not the queue is empty The front is used to get the value of the first data item but does not remove it The rear is used to get the last item from a queue. 7. What is the merge sort? How does it work? Merge sort is a divide-and-conquer algorithm for sorting the data. It works by merging and sorting adjacent data to create bigger sorted lists, which are then merged recursively to form even bigger sorted lists until you have one single sorted list. 8.How does the Selection sort work? Selection sort works by repeatedly picking the smallest number in ascending order from the list and placing it at the beginning. This process is repeated moving toward the end of the list or sorted subarray. Scan all items and find the smallest. Switch over the position as the first item. Repeat the selection sort on the remaining N-1 items. We always iterate forward (i from 0 to N-1) and swap with the smallest element (always i). Time complexity: best case O(n2); worst O(n2) Space complexity: worst O(1) 9. What are the applications of graph Data Structure? Transport grids where stations are represented as vertices and routes as the edges of the graph Utility graphs of power or water, where vertices are connection points and edge the wires or pipes connecting them Social network graphs to determine the flow of information and hotspots (edges and vertices) Neural networks where vertices represent neurons and edge the synapses between them 10. What is an AVL tree? An AVL (Adelson, Velskii, and Landi) tree is a height balancing binary search tree in which the difference of heights of the left and right subtrees of any node is less than or equal to one. This controls the height of the binary search tree by not letting it get skewed. This is used when working with a large data set, with continual pruning through insertion and deletion of data. 11. Differentiate NULL and VOID ? Null is a value, whereas Void is a data type identifier Null indicates an empty value for a variable, whereas void indicates pointers that have no initial size Null means it never existed; Void means it existed but is not in effect All the best 👍👍

30-day roadmap to learn Python up to an intermediate level Week 1: Python Basics *Day 1-2:* - Learn about Python, its syntax, and how to install Python on your computer. - Write your first "Hello, World!" program. - Understand variables and data types (integers, floats, strings). *Day 3-4:* - Explore basic operations (arithmetic, string concatenation). - Learn about user input and how to use the input() function. - Practice creating and using variables. *Day 5-7:* - Dive into control flow with if statements, else statements, and loops (for and while). - Work on simple programs that involve conditions and loops. Week 2: Functions and Modules *Day 8-9:* - Study functions and how to define your own functions using def. - Learn about function arguments and return values. *Day 10-12:* - Explore built-in functions and libraries (e.g., len(), random, math). - Understand how to import modules and use their functions. *Day 13-14:* - Practice writing functions for common tasks. - Create a small project that utilizes functions and modules. Week 3: Data Structures *Day 15-17:* - Learn about lists and their operations (slicing, appending, removing). - Understand how to work with lists of different data types. *Day 18-19:* - Study dictionaries and their key-value pairs. - Practice manipulating dictionary data. *Day 20-21:* - Explore tuples and sets. - Understand when and how to use each data structure. Week 4: Intermediate Topics *Day 22-23:* - Study file handling and how to read/write files in Python. - Work on projects involving file operations. *Day 24-26:* - Learn about exceptions and error handling. - Explore object-oriented programming (classes and objects). *Day 27-28:* - Dive into more advanced topics like list comprehensions and generators. - Study Python's built-in libraries for web development (e.g., requests). *Day 29-30:* - Explore additional libraries and frameworks relevant to your interests (e.g., NumPy for data analysis, Flask for web development, or Pygame for game development). - Work on a more complex project that combines your knowledge from the past weeks. Throughout the 30 days, practice coding daily, and don't hesitate to explore Python's documentation and online resources for additional help. Learning Python is a dynamic process, so adapt the roadmap based on your progress and interests. ENJOY LEARNING 👍👍