Top 9 websites for practicing algorithms and Data structure.
⛓ https://www.hackerrank.com/
⛓ https://leetcode.com/
⛓ https://www.codewars.com/
⛓ https://www.hackerearth.com/for-developers
⛓ https://coderbyte.com/
⛓ https://www.coursera.org/browse/computer-science/algorithms
⛓ https://www.codechef.com/
⛓ https://codeforces.com/
⛓ https://www.geeksforgeeks.org/
⛓ https://www.hackerrank.com/
⛓ https://leetcode.com/
⛓ https://www.codewars.com/
⛓ https://www.hackerearth.com/for-developers
⛓ https://coderbyte.com/
⛓ https://www.coursera.org/browse/computer-science/algorithms
⛓ https://www.codechef.com/
⛓ https://codeforces.com/
⛓ https://www.geeksforgeeks.org/
❤1
💻 Want to Clear Your Next Java Developer Interview?
Prepare these topics to ace your next Java interview! 🚀
𝐓𝐨𝐩𝐢𝐜 𝟏: 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐅𝐥𝐨𝐰 𝐚𝐧𝐝 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞
🔹 Describe your project and its architecture.
🔹 Challenges faced and your role in the project.
🔹 Tech stack used and the reasoning behind it.
🔹 Problem-solving, collaboration, and lessons learned.
🔹 Reflect on what you'd do differently.
𝐓𝐨𝐩𝐢𝐜 𝟐: 𝐂𝐨𝐫𝐞 𝐉𝐚𝐯𝐚
🔹 String concepts (hashcode, equals).
🔹 Immutability, OOPS concepts.
🔹 Serialization, Collection Framework.
🔹 Exception handling, multithreading.
🔹 Java Memory Model, garbage collection.
𝐓𝐨𝐩𝐢𝐜 𝟑: 𝐉𝐚𝐯𝐚 𝟖/𝟏𝟏/𝟏𝟕 Features
🔹 Java 8 features: Lambda expressions, Stream API, Optional API.
🔹 Functional interfaces, default/static methods.
🔹 Pattern matching, text blocks, modules.
𝐓𝐨𝐩𝐢𝐜 𝟒: 𝐒𝐩𝐫𝐢𝐧𝐠 & 𝐒𝐩𝐫𝐢𝐧𝐠 𝐁𝐨𝐨𝐭
🔹 Dependency Injection, IOC, Spring MVC.
🔹 Bean lifecycle, scopes, profiles.
🔹 REST API, CRUD, AOP, Exception handling.
🔹 JWT, OAuth, actuators, WebFlux.
🔹 Microservices, Spring Cloud, JPA.
𝐓𝐨𝐩𝐢𝐜 𝟓: 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 (𝐒𝐐𝐋/𝐍𝐨𝐒𝐐𝐋)
🔹 JPA repositories, entity relationships.
🔹 SQL queries (e.g., Nth highest salary).
🔹 Relational and non-relational DB concepts.
🔹 Joins, indexing, stored procedures.
𝐓𝐨𝐩𝐢𝐜 𝟔: 𝐂𝐨𝐝𝐢𝐧𝐠
🔹 DSA-based questions.
🔹 Sorting/searching with Java APIs.
🔹 Stream API coding questions.
𝐓𝐨𝐩𝐢𝐜 𝟕: 𝐃𝐞𝐯𝐎𝐩𝐬 & 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭
🔹 Familiarize yourself with tools like Jenkins, Kubernetes, Kafka, and cloud technologies.
𝐓𝐨𝐩𝐢𝐜 𝟖: 𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬
🔹 Master design patterns like singleton, factory, observer, etc.
✨ Nail your interview with confidence! ✨
#JavaInterview #JavaDeveloper
Prepare these topics to ace your next Java interview! 🚀
𝐓𝐨𝐩𝐢𝐜 𝟏: 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐅𝐥𝐨𝐰 𝐚𝐧𝐝 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞
🔹 Describe your project and its architecture.
🔹 Challenges faced and your role in the project.
🔹 Tech stack used and the reasoning behind it.
🔹 Problem-solving, collaboration, and lessons learned.
🔹 Reflect on what you'd do differently.
𝐓𝐨𝐩𝐢𝐜 𝟐: 𝐂𝐨𝐫𝐞 𝐉𝐚𝐯𝐚
🔹 String concepts (hashcode, equals).
🔹 Immutability, OOPS concepts.
🔹 Serialization, Collection Framework.
🔹 Exception handling, multithreading.
🔹 Java Memory Model, garbage collection.
𝐓𝐨𝐩𝐢𝐜 𝟑: 𝐉𝐚𝐯𝐚 𝟖/𝟏𝟏/𝟏𝟕 Features
🔹 Java 8 features: Lambda expressions, Stream API, Optional API.
🔹 Functional interfaces, default/static methods.
🔹 Pattern matching, text blocks, modules.
𝐓𝐨𝐩𝐢𝐜 𝟒: 𝐒𝐩𝐫𝐢𝐧𝐠 & 𝐒𝐩𝐫𝐢𝐧𝐠 𝐁𝐨𝐨𝐭
🔹 Dependency Injection, IOC, Spring MVC.
🔹 Bean lifecycle, scopes, profiles.
🔹 REST API, CRUD, AOP, Exception handling.
🔹 JWT, OAuth, actuators, WebFlux.
🔹 Microservices, Spring Cloud, JPA.
𝐓𝐨𝐩𝐢𝐜 𝟓: 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 (𝐒𝐐𝐋/𝐍𝐨𝐒𝐐𝐋)
🔹 JPA repositories, entity relationships.
🔹 SQL queries (e.g., Nth highest salary).
🔹 Relational and non-relational DB concepts.
🔹 Joins, indexing, stored procedures.
𝐓𝐨𝐩𝐢𝐜 𝟔: 𝐂𝐨𝐝𝐢𝐧𝐠
🔹 DSA-based questions.
🔹 Sorting/searching with Java APIs.
🔹 Stream API coding questions.
𝐓𝐨𝐩𝐢𝐜 𝟕: 𝐃𝐞𝐯𝐎𝐩𝐬 & 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭
🔹 Familiarize yourself with tools like Jenkins, Kubernetes, Kafka, and cloud technologies.
𝐓𝐨𝐩𝐢𝐜 𝟖: 𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬
🔹 Master design patterns like singleton, factory, observer, etc.
✨ Nail your interview with confidence! ✨
#JavaInterview #JavaDeveloper
👍1
Complete Syllabus for Data Analytics interview:
SQL:
1. Basic
- SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING
- Basic JOINS (INNER, LEFT, RIGHT, FULL)
- Creating and using simple databases and tables
2. Intermediate
- Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
- Subqueries and nested queries
- Common Table Expressions (WITH clause)
- CASE statements for conditional logic in queries
3. Advanced
- Advanced JOIN techniques (self-join, non-equi join)
- Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag)
- optimization with indexing
- Data manipulation (INSERT, UPDATE, DELETE)
Python:
1. Basic
- Syntax, variables, data types (integers, floats, strings, booleans)
- Control structures (if-else, for and while loops)
- Basic data structures (lists, dictionaries, sets, tuples)
- Functions, lambda functions, error handling (try-except)
- Modules and packages
2. Pandas & Numpy
- Creating and manipulating DataFrames and Series
- Indexing, selecting, and filtering data
- Handling missing data (fillna, dropna)
- Data aggregation with groupby, summarizing data
- Merging, joining, and concatenating datasets
3. Basic Visualization
- Basic plotting with Matplotlib (line plots, bar plots, histograms)
- Visualization with Seaborn (scatter plots, box plots, pair plots)
- Customizing plots (sizes, labels, legends, color palettes)
- Introduction to interactive visualizations (e.g., Plotly)
Excel:
1. Basic
- Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.)
- Introduction to charts and basic data visualization
- Data sorting and filtering
- Conditional formatting
2. Intermediate
- Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF)
- PivotTables and PivotCharts for summarizing data
- Data validation tools
- What-if analysis tools (Data Tables, Goal Seek)
3. Advanced
- Array formulas and advanced functions
- Data Model & Power Pivot
- Advanced Filter
- Slicers and Timelines in Pivot Tables
- Dynamic charts and interactive dashboards
Power BI:
1. Data Modeling
- Importing data from various sources
- Creating and managing relationships between different datasets
- Data modeling basics (star schema, snowflake schema)
2. Data Transformation
- Using Power Query for data cleaning and transformation
- Advanced data shaping techniques
- Calculated columns and measures using DAX
3. Data Visualization and Reporting - Creating interactive reports and dashboards
- Visualizations (bar, line, pie charts, maps)
- Publishing and sharing reports, scheduling data refreshes
Statistics Fundamentals: Mean, Median, Mode, Standard Deviation, Variance, Probability Distributions, Hypothesis Testing, P-values, Confidence Intervals, Correlation, Simple Linear Regression, Normal Distribution, Binomial Distribution, Poisson Distribution.
Like for more 😄❤️
SQL:
1. Basic
- SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING
- Basic JOINS (INNER, LEFT, RIGHT, FULL)
- Creating and using simple databases and tables
2. Intermediate
- Aggregate functions (COUNT, SUM, AVG, MAX, MIN)
- Subqueries and nested queries
- Common Table Expressions (WITH clause)
- CASE statements for conditional logic in queries
3. Advanced
- Advanced JOIN techniques (self-join, non-equi join)
- Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag)
- optimization with indexing
- Data manipulation (INSERT, UPDATE, DELETE)
Python:
1. Basic
- Syntax, variables, data types (integers, floats, strings, booleans)
- Control structures (if-else, for and while loops)
- Basic data structures (lists, dictionaries, sets, tuples)
- Functions, lambda functions, error handling (try-except)
- Modules and packages
2. Pandas & Numpy
- Creating and manipulating DataFrames and Series
- Indexing, selecting, and filtering data
- Handling missing data (fillna, dropna)
- Data aggregation with groupby, summarizing data
- Merging, joining, and concatenating datasets
3. Basic Visualization
- Basic plotting with Matplotlib (line plots, bar plots, histograms)
- Visualization with Seaborn (scatter plots, box plots, pair plots)
- Customizing plots (sizes, labels, legends, color palettes)
- Introduction to interactive visualizations (e.g., Plotly)
Excel:
1. Basic
- Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.)
- Introduction to charts and basic data visualization
- Data sorting and filtering
- Conditional formatting
2. Intermediate
- Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF)
- PivotTables and PivotCharts for summarizing data
- Data validation tools
- What-if analysis tools (Data Tables, Goal Seek)
3. Advanced
- Array formulas and advanced functions
- Data Model & Power Pivot
- Advanced Filter
- Slicers and Timelines in Pivot Tables
- Dynamic charts and interactive dashboards
Power BI:
1. Data Modeling
- Importing data from various sources
- Creating and managing relationships between different datasets
- Data modeling basics (star schema, snowflake schema)
2. Data Transformation
- Using Power Query for data cleaning and transformation
- Advanced data shaping techniques
- Calculated columns and measures using DAX
3. Data Visualization and Reporting - Creating interactive reports and dashboards
- Visualizations (bar, line, pie charts, maps)
- Publishing and sharing reports, scheduling data refreshes
Statistics Fundamentals: Mean, Median, Mode, Standard Deviation, Variance, Probability Distributions, Hypothesis Testing, P-values, Confidence Intervals, Correlation, Simple Linear Regression, Normal Distribution, Binomial Distribution, Poisson Distribution.
Like for more 😄❤️
👍1
Java for Everything: ☕
Java + Spring = Enterprise Applications
Java + Hibernate = Object-Relational Mapping
Java + Android = Mobile App Development
Java + Swing = Desktop GUI Applications
Java + JavaFX = Modern GUI Applications
Java + JUnit = Unit Testing
Java + Maven = Project Management
Java + Jenkins = Continuous Integration
Java + Apache Kafka = Stream Processing
Java + Apache Hadoop = Big Data Processing
Java + Microservices = Scalable Services
Best Programming Resources: https://topmate.io/coding/886839
All the best 👍👍
Java + Spring = Enterprise Applications
Java + Hibernate = Object-Relational Mapping
Java + Android = Mobile App Development
Java + Swing = Desktop GUI Applications
Java + JavaFX = Modern GUI Applications
Java + JUnit = Unit Testing
Java + Maven = Project Management
Java + Jenkins = Continuous Integration
Java + Apache Kafka = Stream Processing
Java + Apache Hadoop = Big Data Processing
Java + Microservices = Scalable Services
Best Programming Resources: https://topmate.io/coding/886839
All the best 👍👍
👍2
Here are 20 essential VS Code shortcuts for beginners:
1. Ctrl + P: Open any file quickly 📂
2. Ctrl + /: Toggle line comment 📝
3. Alt + Up/Down: Move a line up or down ↕️
4. Ctrl + Shift + K: Delete the current line ❌
5. Ctrl + B: Show/hide the sidebar 📚
6. Ctrl + Space: Trigger IntelliSense for code suggestions 💡
7. Ctrl + Shift + F: Search across files 🔍
8. Ctrl + D: Select the next occurrence of the selected text 📑
9. Ctrl + Shift + L: Select all occurrences of the current selection 🔗
10. Ctrl + Shift + P: Open the Command Palette 📜
11. Ctrl + F2: Rename all occurrences of a variable ✏️
12. Ctrl + J: Show/hide the integrated terminal 💻
13. Ctrl + `: Open a new terminal 🔧
14. Ctrl + Shift + N: Open a new window 🖼️
15. Ctrl + W: Close the current editor tab 🗂️
16. Ctrl + Shift + E: Focus on the file explorer 🗃️
17. Ctrl + Shift + G: Open the Git view 🔄
18. Ctrl + Shift + M: Open the Problems panel 🚨
19. Alt + Shift + Up/Down: Copy the line up or down 📋
20. Ctrl + Alt + Arrow keys: Split the editor window ✂️
Master these and level up your coding speed! 🚀
1. Ctrl + P: Open any file quickly 📂
2. Ctrl + /: Toggle line comment 📝
3. Alt + Up/Down: Move a line up or down ↕️
4. Ctrl + Shift + K: Delete the current line ❌
5. Ctrl + B: Show/hide the sidebar 📚
6. Ctrl + Space: Trigger IntelliSense for code suggestions 💡
7. Ctrl + Shift + F: Search across files 🔍
8. Ctrl + D: Select the next occurrence of the selected text 📑
9. Ctrl + Shift + L: Select all occurrences of the current selection 🔗
10. Ctrl + Shift + P: Open the Command Palette 📜
11. Ctrl + F2: Rename all occurrences of a variable ✏️
12. Ctrl + J: Show/hide the integrated terminal 💻
13. Ctrl + `: Open a new terminal 🔧
14. Ctrl + Shift + N: Open a new window 🖼️
15. Ctrl + W: Close the current editor tab 🗂️
16. Ctrl + Shift + E: Focus on the file explorer 🗃️
17. Ctrl + Shift + G: Open the Git view 🔄
18. Ctrl + Shift + M: Open the Problems panel 🚨
19. Alt + Shift + Up/Down: Copy the line up or down 📋
20. Ctrl + Alt + Arrow keys: Split the editor window ✂️
Master these and level up your coding speed! 🚀
👍4👏1
Frontend Development Interview Questions
Beginner Level
1. What are semantic HTML tags?
2. Difference between id and class in HTML?
3. What is the Box Model in CSS?
4. Difference between margin and padding?
5. What is a responsive web design?
6. What is the use of the <meta viewport> tag?
7. Difference between inline, block, and inline-block elements?
8. What is the difference between == and === in JavaScript?
9. What are arrow functions in JavaScript?
10. What is DOM and how is it used?
Intermediate Level
1. What are pseudo-classes and pseudo-elements in CSS?
2. How do media queries work in responsive design?
3. Difference between relative, absolute, fixed, and sticky positioning?
4. What is the event loop in JavaScript?
5. Explain closures in JavaScript with an example.
6. What are Promises and how do you handle errors with .catch()?
7. What is a higher-order function?
8. What is the difference between localStorage and sessionStorage?
9. How does this keyword work in different contexts?
10. What is JSX in React?
Advanced Level
1. How does the virtual DOM work in React?
2. What are controlled vs uncontrolled components in React?
3. What is useMemo and when should you use it?
4. How do you optimize a large React app for performance?
5. What are React lifecycle methods (class-based) and their hook equivalents?
6. How does Redux work and when should you use it?
7. What is code splitting and why is it useful?
8. How do you secure a frontend app from XSS attacks?
9. Explain the concept of Server-Side Rendering (SSR) vs Client-Side Rendering (CSR).
10. What are Web Components and how do they work?
React ❤️ for the detailed answers
Join for free resources: 👇 https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
Beginner Level
1. What are semantic HTML tags?
2. Difference between id and class in HTML?
3. What is the Box Model in CSS?
4. Difference between margin and padding?
5. What is a responsive web design?
6. What is the use of the <meta viewport> tag?
7. Difference between inline, block, and inline-block elements?
8. What is the difference between == and === in JavaScript?
9. What are arrow functions in JavaScript?
10. What is DOM and how is it used?
Intermediate Level
1. What are pseudo-classes and pseudo-elements in CSS?
2. How do media queries work in responsive design?
3. Difference between relative, absolute, fixed, and sticky positioning?
4. What is the event loop in JavaScript?
5. Explain closures in JavaScript with an example.
6. What are Promises and how do you handle errors with .catch()?
7. What is a higher-order function?
8. What is the difference between localStorage and sessionStorage?
9. How does this keyword work in different contexts?
10. What is JSX in React?
Advanced Level
1. How does the virtual DOM work in React?
2. What are controlled vs uncontrolled components in React?
3. What is useMemo and when should you use it?
4. How do you optimize a large React app for performance?
5. What are React lifecycle methods (class-based) and their hook equivalents?
6. How does Redux work and when should you use it?
7. What is code splitting and why is it useful?
8. How do you secure a frontend app from XSS attacks?
9. Explain the concept of Server-Side Rendering (SSR) vs Client-Side Rendering (CSR).
10. What are Web Components and how do they work?
React ❤️ for the detailed answers
Join for free resources: 👇 https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
👍2❤1
Practice projects to consider:
1. Implement a basic search engine: Read a set of documents and build an index of keywords. Then, implement a search function that returns a list of documents that match the query.
2. Build a recommendation system: Read a set of user-item interactions and build a recommendation system that suggests items to users based on their past behavior.
3. Create a data analysis tool: Read a large dataset and implement a tool that performs various analyses, such as calculating summary statistics, visualizing distributions, and identifying patterns and correlations.
4. Implement a graph algorithm: Study a graph algorithm such as Dijkstra's shortest path algorithm, and implement it in Python. Then, test it on real-world graphs to see how it performs.
1. Implement a basic search engine: Read a set of documents and build an index of keywords. Then, implement a search function that returns a list of documents that match the query.
2. Build a recommendation system: Read a set of user-item interactions and build a recommendation system that suggests items to users based on their past behavior.
3. Create a data analysis tool: Read a large dataset and implement a tool that performs various analyses, such as calculating summary statistics, visualizing distributions, and identifying patterns and correlations.
4. Implement a graph algorithm: Study a graph algorithm such as Dijkstra's shortest path algorithm, and implement it in Python. Then, test it on real-world graphs to see how it performs.
👍1
Ages of Operating Systems👨🏻💻😎
📂 Windows 11 (3 years old)
🪟 Windows 10 (8 years old)
🍎 macOS Yosemite (10 years old)
🐉 Kali Linux (11 years old)
💻 Windows 8 (12 years old)
🌐 Manjaro (11 years old)
💻 Windows 7 (14 years old)
🖥️ Windows Vista (17 years old)
🌿 Linux Mint (18 years old)
🐧 Ubuntu (20 years old)
⚙️ Fedora (20 years old)
🔧 OpenSUSE (20 years old)
⚙️ CentOS (20 years old)
🐧 Arch Linux (22 years old)
🍏 macOS (22 years old)
💻 Windows XP (23 years old)
🖥️ Windows 2000 (24 years old)
📱 Windows 98 (25 years old)
🌍 Windows 95 (28 years old)
💻 Windows 3.1 (29 years old)
🖥️ OS/2 (32 years old)
🐧 Debian (31 years old)
🔴 Red Hat Linux (30 years old)
🎮 AmigaOS (34 years old)
🖥️ Xenix (40 years old)
📀 VMS (44 years old)
💾 MS-DOS (42 years old)
💾 CP/M (49 years old)
🖥️ Unix (54 years old)
📂 Windows 11 (3 years old)
🪟 Windows 10 (8 years old)
🍎 macOS Yosemite (10 years old)
🐉 Kali Linux (11 years old)
💻 Windows 8 (12 years old)
🌐 Manjaro (11 years old)
💻 Windows 7 (14 years old)
🖥️ Windows Vista (17 years old)
🌿 Linux Mint (18 years old)
🐧 Ubuntu (20 years old)
⚙️ Fedora (20 years old)
🔧 OpenSUSE (20 years old)
⚙️ CentOS (20 years old)
🐧 Arch Linux (22 years old)
🍏 macOS (22 years old)
💻 Windows XP (23 years old)
🖥️ Windows 2000 (24 years old)
📱 Windows 98 (25 years old)
🌍 Windows 95 (28 years old)
💻 Windows 3.1 (29 years old)
🖥️ OS/2 (32 years old)
🐧 Debian (31 years old)
🔴 Red Hat Linux (30 years old)
🎮 AmigaOS (34 years old)
🖥️ Xenix (40 years old)
📀 VMS (44 years old)
💾 MS-DOS (42 years old)
💾 CP/M (49 years old)
🖥️ Unix (54 years old)
👍6