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Age of Programming Languages👨🏻‍💻 🦅 Swift (10 years old) (2014) 🚀 Kotlin (12 years old) (2011) 🦀 Rust (13 years old) (2010) 🐹 Go (14 years old) (2009) 🔷 TypeScript (11 years old) (2012) 🎸 C# (23 years old) (2000) 💎 Ruby (28 years old) (1995) ☕ Java (28 years old) (1995) 🌐 JavaScript (28 years old) (1995) 🐘 PHP (29 years old) (1994) 🐍 Python (33 years old) (1991) 🐪 Perl (36 years old) (1987) 🚀 C++ (38 years old) (1985) 📱 Objective-C (39 years old) (1984) 🔍 Prolog (51 years old) (1972) 🗣️ Smalltalk (51 years old) (1972) 🖥️ C (51 years old) (1972) 📝 Pascal (53 years old) (1970) 🎓 BASIC (59 years old) (1964) 💼 COBOL (64 years old) (1959) 🤖 Lisp (65 years old) (1958) 📜 Fortran (66 years old) (1957) Join for more https://telegram.me/sign2tech

SQL Essentials for Quick Revision 🚀 SELECT Retrieve data from one or more tables. 🎯 WHERE Clause Filter records based on specific conditions. 🔄 ORDER BY Sort query results in ascending (ASC) or descending (DESC) order. 📊 Aggregation Functions MIN, MAX, AVG, COUNT: Summarize data. Window Functions: Perform calculations across a dataset without grouping rows. 🔑 GROUP BY Group data based on one or more columns and apply aggregate functions. 🔗 JOINS INNER JOIN: Fetch matching rows from both tables. LEFT JOIN: All rows from the left table and matching rows from the right. RIGHT JOIN: All rows from the right table and matching rows from the left. FULL JOIN: Combine rows when there is a match in either table. SELF JOIN: Join a table with itself. 🧩 Common Table Expressions (CTE) Simplify complex queries with temporary result sets. Quick SQL Revision Notes 📌 Master these concepts for interviews and projects! Join for more https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q https://telegram.me/sign2tech

Everyone's talking about #ChatGPT. But 90% of you are missing out on the AI revolution. Here are the top AI tools you NEED to know about. 1. Krisp: Krisp's AI removes background voices, noises, and echo from your calls, giving you peace of call Link: https://krisp.ai/ 2. Beatoven: Create unique royalty-free music that elevates your story Link: https://www.beatoven.ai/ 3. Cleanvoice: Automatically edit your podcast episodes Link: https://cleanvoice.ai/ 4. Podcastle: Studio quality recording, right from your computer Link: https://podcastle.ai/ 5. Flair: Design branded content in a flash Link: https://flair.ai/ 6. Illustroke: Create killer vector images from text prompts Link: https://illustroke.com/ 7. Patterned: Generate the exact patterns you need for and design Link: https://www.patterned.ai/ 8. Stockimg: Generate the perfect stock photo you need, every time Link: https://stockimg.ai/ 9. Copy: AI Generated copy, that actually increases conversion Link:https://www.copy.ai/ 10. CopyMonkey: Create Amazon listings in seconds Link: http://copymonkey.ai/ 11. Ocoya: Create and schedule social media content 10x faster Link: https://www.ocoya.com/ 12. Unbounce Smart Copy: Write high-performing cold emails at scale Link: https://unbounce.com/ 13. Vidyo: Make short-form vids from long-form content in just a few clicks Link: https://vidyo.ai/ 14. Maverick: Generate personalized videos at scale Link:https://lnkd.in/dmrkz_ah 15. Quickchat: AI chatbots that automate customer service charts Link: https://www.quickchat.ai/ 16. Puzzle: Build an AI-powered knowledge base for your team and customers Link: https://www.puzzlelabs.ai/ 17. Soundraw: Stop searching for the song you need. Create it. Link: https://soundraw.io/ 18. Cleanup: Remove any wanted object, defect, people, or text from your pictures in seconds Link: https://cleanup.pictures/ 19. Resumeworded: Improve your re… Read in full →

Excel vs SQL vs Python (pandas): 1️⃣ Filtering Data ↳ Excel: =FILTER(A2:D100, B2:B100>50) (Excel 365 users) ↳ SQL: SELECT * FROM table WHERE column > 50; ↳ Python: df_filtered = df[df['column'] > 50] 2️⃣ Sorting Data ↳ Excel: Data → Sort (or =SORT(A2:A100, 1, TRUE)) ↳ SQL: SELECT * FROM table ORDER BY column ASC; ↳ Python: df_sorted = df.sort_values(by="column") 3️⃣ Counting Rows ↳ Excel: =COUNTA(A:A) ↳ SQL: SELECT COUNT(*) FROM table; ↳ Python: row_count = len(df) 4️⃣ Removing Duplicates ↳ Excel: Data → Remove Duplicates ↳ SQL: SELECT DISTINCT * FROM table; ↳ Python: df_unique = df.drop_duplicates() 5️⃣ Joining Tables ↳ Excel: Power Query → Merge Queries (or VLOOKUP/XLOOKUP) ↳ SQL: SELECT * FROM table1 JOIN table2 ON table1.id = table2.id; ↳ Python: df_merged = pd.merge(df1, df2, on="id") 6️⃣ Ranking Data ↳ Excel: =RANK.EQ(A2, $A$2:$A$100) ↳ SQL: SELECT column, RANK() OVER (ORDER BY column DESC) AS rank FROM table; ↳ Python: df["rank"] = df["column"].rank(method="min", ascending=False) 7️⃣ Moving Average Calculation ↳ Excel: =AVERAGE(B2:B4) (manually for rolling window) ↳ SQL: SELECT date, AVG(value) OVER (ORDER BY date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS moving_avg FROM table; ↳ Python: df["moving_avg"] = df["value"].rolling(window=3).mean() 8️⃣ Running Total ↳ Excel: =SUM($B$2:B2) (drag down) ↳ SQL: SELECT date, SUM(value) OVER (ORDER BY date) AS running_total FROM table; ↳ Python: df["running_total"] = df["value"].cumsum() Join for more https://telegram.me/sign2tech https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q

🔐 Key Python Libraries for Data Science: Numpy: Core for numerical operations and array handling. SciPy: Complements Numpy with scientific computing features like optimization. Pandas: Crucial for data manipulation, offering powerful DataFrames. Matplotlib: Versatile plotting library for creating various visualizations. Keras: High-level neural networks API for quick deep learning prototyping. TensorFlow: Popular open-source ML framework for building and training models. Scikit-learn: Efficient tools for data mining and statistical modeling. Seaborn: Enhances data visualization with appealing statistical graphics. Statsmodels: Focuses on estimating and testing statistical models. NLTK: Library for working with human language data. These libraries empower data scientists across tasks, from preprocessing to advanced machine learning. Join for More https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q https://telegram.me/sign2tech

💥Different Tools and their use cases 1. Selenium: 🌐 Automation testing that scales effortlessly. 2. Postman: 🔗 Simplify your API testing journey. 3. Appium: 📱 Master mobile app testing like a pro. 4. JIRA: 🐛 Track bugs & collaborate with ease. 5. JMeter: ⚡️ Unleash the power of performance testing. 6. TestRail: 🧾 Organize and manage your test cases seamlessly. 7. Cypress: 🕵️‍♀️ Take UI automation to the next level with modern tools. 8. SoapUI: 🛠 Comprehensive API testing and service virtualization. 9. Katalon Studio: 🔍 A versatile web, API, and mobile testing tool. 10. QTest: 📋 A reliable tool for test management and execution. 11. BrowserStack: 🌐 Test across multiple browsers and devices. 12. TestComplete: 🤖 Build reliable automated UI tests quickly. 13. Robot Framework: 🛠 Open-source automation for everyone. 14. LoadRunner: 🚀 Performance testing for heavy loads and stress tests. 15. Bugzilla: 🐞 Lightweight yet powerful bug tracking tool. 16. Ranorex: 🎯 User-friendly desktop, web, and mobile application automation. 17. Cucumber: 🥒 Simplify behavior-driven testing (BDD). 18. TestLink: 🖇 Manage test cases and requirements effectively. 19. Zephyr: 📊 Integrate testing into your Agile workflow seamlessly. 20. Charles Proxy: 🕵️ Debug and monitor HTTP/HTTPS traffic effortlessly.

95% of the companies ask the same SQL questions 😱 Check the questions list below 🔻 1.) Explain order of execution of SQL. 2.) What is difference between where and having? 3.) What is the use of group by? 4.) Explain all types of joins in SQL? 5.) What are triggers in SQL? 6.) What is stored procedure in SQL 7.) Explain all types of window functions? (Mainly rank, row_num, dense_rank, lead & lag) 8.) What is difference between Delete and Truncate? 9.) What is difference between DML, DDL and DCL? 10.) What are aggregate function and when do we use them? explain with few example. 11.) Which is faster between CTE and Subquery? 12.) What are constraints and types of Constraints? 13.) Types of Keys? 14.) Different types of Operators ? 15.) Difference between Group By and Where? 16.) What are Views? 17.) What are different types of constraints? 18.) What is difference between varchar and nvarchar? 19.) Similar for char and nchar? 20.) What are index and their types? 21.) What is an index? Explain its different types. 22.) List the different types of relationships in SQL. 23.) Differentiate between UNION and UNION ALL. 24.) How many types of clauses in SQL? 25.) What is the difference between UNION and UNION ALL in SQL? 26.) What are the various types of relationships in SQL? 27.) Difference between Primary Key and Secondary Key? 28.) What is the difference between where and having? 29.) Find the second highest salary of an employee? 30.) Write retention query in SQL? 31.) Write year-on-year growth in SQL? 32.) Write a query for cumulative sum in SQL? 33.) Difference between Function and Store procedure ? 34.) Do we use variable in views? 35.) What are the limitations of views? Follow our Community❤️🌻 https://telegram.me/sign2tech https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q

25 Papers That Completely Transformed the Computer World. 1. Dynamo - Amazon’s Highly Available Key Value Store 2. Google File System: Insights into a highly scalable file system 3. Scaling Memcached at Facebook: A look at the complexities of Caching 4. BigTable: The design principles behind a distributed storage system 5. Borg - Large Scale Cluster Management at Google 6. Cassandra: A look at the design and architecture of a distributed NoSQL database 7. Attention Is All You Need: Into a new deep learning architecture known as the transformer 8. Kafka: Internals of the distributed messaging platform 9. FoundationDB: A look at how a distributed database 10. Amazon Aurora: To learn how Amazon provides high-availability and performance 11. Spanner: Design and architecture of Google’s globally distributed databas 12. MapReduce: A detailed look at how MapReduce enables parallel processing of massive volumes of data 13. Shard Manager: Understanding the generic shard management framework 14. Dapper: Insights into Google’s distributed systems tracing infrastructure 15. Flink: A detailed look at the unified architecture of stream and batch processing 16. A Comprehensive Survey on Vector Databases 17. Zanzibar: A look at the design, implementation and deployment of a global system for managing access control lists at Google 18. Monarch: Architecture of Google’s in-memory time series database 19. Thrift: Explore the design choices behind Facebook’s code-generation tool 20. Bitcoin: The ground-breaking introduction to the peer-to-peer electronic cash system 21. WTF - Who to Follow Service at Twitter: Twitter’s (now X) user recommendation system 22. MyRocks: LSM-Tree Database Storage Engine 23. GoTo Considered Harmful 24. Raft Consensus Algorithm: To learn about the more understandable consensus algorithm 25. Time Clocks and Ordering of Events: The extremely important paper that explains the concept of time and event ordering in a distributed system … Read in full →

Placement toh ho kar rahegi! Padhai nahi rukni chahiye! Keep studying, stay focused! Your hard work will pay off! Reaction🙃😍

GET, POST, PUT... Common HTTP “verbs” in one figure. 1. HTTP GET This retrieves a resource from the server. It is idempotent. Multiple identical requests return the same result. 2. HTTP PUT This updates or Creates a resource. It is idempotent. Multiple identical requests will update the same resource. 3. HTTP POST This is used to create new resources. It is not idempotent, making two identical POST will duplicate the resource creation. 4. HTTP DELETE This is used to delete a resource. It is idempotent. Multiple identical requests will delete the same resource. 5. HTTP PATCH The PATCH method applies partial modifications to a resource. 6. HTTP HEAD The HEAD method asks for a response identical to a GET request but without the response body. 7. HTTP CONNECT The CONNECT method establishes a tunnel to the server identified by the target resource. 8. HTTP OPTIONS This describes the communication options for the target resource. 9. HTTP TRACE This performs a message loop-back test along the path to the target resource.

Top 10 Github Repositories For Web Developer 1. Web Developer-Roadmap : https://github.com/kamranahmedse/developer-roadmap 2. 30-Seconds-Of-Code : https://github.com/30-seconds/30-seconds-of-code 3. Awesome-Cheatsheets : https://github.com/LeCoupa/awesome-cheatsheets 4. CSS-Protips : https://github.com/AllThingsSmitty/css-protips 5. 33-JS-Concepts : https://github.com/leonardomso/33-js-concepts 6. You-Dont-Know-JS : https://github.com/getify/You-Dont-Know-JS/tree/2nd-ed 7. Front-End-Checklist : https://github.com/thedaviddias/Front-End-Checklist 8. Javascript-Questions : https://github.com/lydiahallie/javascript-questions 9. Clean-Code-Javascript : https://github.com/ryanmcdermott/clean-code-javascript Follow our Community❤️🌻 https://telegram.me/sign2tech