๐ง๐ผ๐ฝ ๐ญ๐ฑ ๐๐ฎ๐บ๐ฒ ๐๐ฒ๐ ๐๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ๐๐พ๐ฎ
1. C++: AAA games (Unreal)
2. C#: Unity, indie game
3. JavaScript: Web game
4. Java: Android game
5. Python: Prototypes (Pygame)
6. Lua: Scripting (Roblox)
7. Swift: iOS games
8. Objective-C: Legacy iOS/macOS
9. Rust: System-level (Amethyst)
10. Go: Multiplayer servers
11. HTML5 + JS: Simple 2D games
12. Kotlin: Android apps
13. Haxe: Cross-platform 2D
14. TypeScript: Scalable web games
15. Ruby: Lightweight 2D games
1. C++: AAA games (Unreal)
2. C#: Unity, indie game
3. JavaScript: Web game
4. Java: Android game
5. Python: Prototypes (Pygame)
6. Lua: Scripting (Roblox)
7. Swift: iOS games
8. Objective-C: Legacy iOS/macOS
9. Rust: System-level (Amethyst)
10. Go: Multiplayer servers
11. HTML5 + JS: Simple 2D games
12. Kotlin: Android apps
13. Haxe: Cross-platform 2D
14. TypeScript: Scalable web games
15. Ruby: Lightweight 2D games
๐9โค4
Java Developer Interview โค
It'll gonna be super helpful for YOU
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ญ: ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐ ๐ณ๐น๐ผ๐ ๐ฎ๐ป๐ฑ ๐ฎ๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ
- Please tell me about your project and its architecture, Challenges faced?
- What was your role in the project? Tech Stack of project? why this stack?
- Problem you solved during the project? How collaboration within the team?
- What lessons did you learn from working on this project?
- If you could go back, what would you do differently in this project?
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฎ: ๐๐ผ๐ฟ๐ฒ ๐๐ฎ๐๐ฎ
- String Concepts/Hashcode- Equal Methods
- Immutability
- OOPS concepts
- Serialization
- Collection Framework
- Exception Handling
- Multithreading
- Java Memory Model
- Garbage collection
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฏ: ๐๐ฎ๐๐ฎ-๐ด/๐๐ฎ๐๐ฎ-๐ญ๐ญ/๐๐ฎ๐๐ฎ๐ญ๐ณ
- Java 8 features
- Default/Static methods
- Lambda expression
- Functional interfaces
- Optional API
- Stream API
- Pattern matching
- Text block
- Modules
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฐ: ๐ฆ๐ฝ๐ฟ๐ถ๐ป๐ด ๐๐ฟ๐ฎ๐บ๐ฒ๐๐ผ๐ฟ๐ธ, ๐ฆ๐ฝ๐ฟ๐ถ๐ป๐ด-๐๐ผ๐ผ๐, ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ฒ๐ฟ๐๐ถ๐ฐ๐ฒ, ๐ฎ๐ป๐ฑ ๐ฅ๐ฒ๐๐ ๐๐ฃ๐
- Dependency Injection/IOC, Spring MVC
- Configuration, Annotations, CRUD
- Bean, Scopes, Profiles, Bean lifecycle
- App context/Bean context
- AOP, Exception Handler, Control Advice
- Security (JWT, Oauth)
- Actuators
- WebFlux and Mono Framework
- HTTP methods
- JPA
- Microservice concepts
- Spring Cloud
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฑ: ๐๐ถ๐ฏ๐ฒ๐ฟ๐ป๐ฎ๐๐ฒ/๐ฆ๐ฝ๐ฟ๐ถ๐ป๐ด-๐ฑ๐ฎ๐๐ฎ ๐๐ฝ๐ฎ/๐๐ฎ๐๐ฎ๐ฏ๐ฎ๐๐ฒ (๐ฆ๐ค๐ ๐ผ๐ฟ ๐ก๐ผ๐ฆ๐ค๐)
- JPA Repositories
- Relationship with Entities
- SQL queries on Employee department
- Queries, Highest Nth salary queries
- Relational and No-Relational DB concepts
- CRUD operations in DB
- Joins, indexing, procs, function
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฒ: ๐๐ผ๐ฑ๐ถ๐ป๐ด
- DSA Related Questions
- Sorting and searching using Java API.
- Stream API coding Questions
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ณ: ๐๐ฒ๐๐ผ๐ฝ๐ ๐พ๐๐ฒ๐๐๐ถ๐ผ๐ป๐ ๐ผ๐ป ๐ฑ๐ฒ๐ฝ๐น๐ผ๐๐บ๐ฒ๐ป๐ ๐ง๐ผ๐ผ๐น๐
- These types of topics are mostly asked by managers or leads who are heavily working on it, That's why they may grill you on DevOps/deployment-related tools, You should have an understanding of common tools like Jenkins, Kubernetes, Kafka, Cloud, and all.
๐ง๐ผ๐ฝ๐ถ๐ฐ๐ ๐ด: ๐๐ฒ๐๐ ๐ฝ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ
- The interviewer always wanted to ask about some design patterns, it may be Normal design patterns like singleton, factory, or observer patterns to know that you can use these in coding.
Make sure to scroll through the above messages ๐ definitely you will get the more interesting things ๐ค
All the best ๐๐
It'll gonna be super helpful for YOU
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ญ: ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐ ๐ณ๐น๐ผ๐ ๐ฎ๐ป๐ฑ ๐ฎ๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ
- Please tell me about your project and its architecture, Challenges faced?
- What was your role in the project? Tech Stack of project? why this stack?
- Problem you solved during the project? How collaboration within the team?
- What lessons did you learn from working on this project?
- If you could go back, what would you do differently in this project?
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฎ: ๐๐ผ๐ฟ๐ฒ ๐๐ฎ๐๐ฎ
- String Concepts/Hashcode- Equal Methods
- Immutability
- OOPS concepts
- Serialization
- Collection Framework
- Exception Handling
- Multithreading
- Java Memory Model
- Garbage collection
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฏ: ๐๐ฎ๐๐ฎ-๐ด/๐๐ฎ๐๐ฎ-๐ญ๐ญ/๐๐ฎ๐๐ฎ๐ญ๐ณ
- Java 8 features
- Default/Static methods
- Lambda expression
- Functional interfaces
- Optional API
- Stream API
- Pattern matching
- Text block
- Modules
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฐ: ๐ฆ๐ฝ๐ฟ๐ถ๐ป๐ด ๐๐ฟ๐ฎ๐บ๐ฒ๐๐ผ๐ฟ๐ธ, ๐ฆ๐ฝ๐ฟ๐ถ๐ป๐ด-๐๐ผ๐ผ๐, ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ฒ๐ฟ๐๐ถ๐ฐ๐ฒ, ๐ฎ๐ป๐ฑ ๐ฅ๐ฒ๐๐ ๐๐ฃ๐
- Dependency Injection/IOC, Spring MVC
- Configuration, Annotations, CRUD
- Bean, Scopes, Profiles, Bean lifecycle
- App context/Bean context
- AOP, Exception Handler, Control Advice
- Security (JWT, Oauth)
- Actuators
- WebFlux and Mono Framework
- HTTP methods
- JPA
- Microservice concepts
- Spring Cloud
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฑ: ๐๐ถ๐ฏ๐ฒ๐ฟ๐ป๐ฎ๐๐ฒ/๐ฆ๐ฝ๐ฟ๐ถ๐ป๐ด-๐ฑ๐ฎ๐๐ฎ ๐๐ฝ๐ฎ/๐๐ฎ๐๐ฎ๐ฏ๐ฎ๐๐ฒ (๐ฆ๐ค๐ ๐ผ๐ฟ ๐ก๐ผ๐ฆ๐ค๐)
- JPA Repositories
- Relationship with Entities
- SQL queries on Employee department
- Queries, Highest Nth salary queries
- Relational and No-Relational DB concepts
- CRUD operations in DB
- Joins, indexing, procs, function
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ฒ: ๐๐ผ๐ฑ๐ถ๐ป๐ด
- DSA Related Questions
- Sorting and searching using Java API.
- Stream API coding Questions
๐ง๐ผ๐ฝ๐ถ๐ฐ ๐ณ: ๐๐ฒ๐๐ผ๐ฝ๐ ๐พ๐๐ฒ๐๐๐ถ๐ผ๐ป๐ ๐ผ๐ป ๐ฑ๐ฒ๐ฝ๐น๐ผ๐๐บ๐ฒ๐ป๐ ๐ง๐ผ๐ผ๐น๐
- These types of topics are mostly asked by managers or leads who are heavily working on it, That's why they may grill you on DevOps/deployment-related tools, You should have an understanding of common tools like Jenkins, Kubernetes, Kafka, Cloud, and all.
๐ง๐ผ๐ฝ๐ถ๐ฐ๐ ๐ด: ๐๐ฒ๐๐ ๐ฝ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ
- The interviewer always wanted to ask about some design patterns, it may be Normal design patterns like singleton, factory, or observer patterns to know that you can use these in coding.
Make sure to scroll through the above messages ๐ definitely you will get the more interesting things ๐ค
All the best ๐๐
๐16๐2โค1๐ฅ1
๐ป Want to Clear Your Next Java Developer Interview?
Prepare these topics to ace your next Java interview! ๐
๐๐จ๐ฉ๐ข๐ ๐: ๐๐ซ๐จ๐ฃ๐๐๐ญ ๐ ๐ฅ๐จ๐ฐ ๐๐ง๐ ๐๐ซ๐๐ก๐ข๐ญ๐๐๐ญ๐ฎ๐ซ๐
๐น Describe your project and its architecture.
๐น Challenges faced and your role in the project.
๐น Tech stack used and the reasoning behind it.
๐น Problem-solving, collaboration, and lessons learned.
๐น Reflect on what you'd do differently.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐จ๐ซ๐ ๐๐๐ฏ๐
๐น String concepts (hashcode, equals).
๐น Immutability, OOPS concepts.
๐น Serialization, Collection Framework.
๐น Exception handling, multithreading.
๐น Java Memory Model, garbage collection.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐๐ฏ๐ ๐/๐๐/๐๐ Features
๐น Java 8 features: Lambda expressions, Stream API, Optional API.
๐น Functional interfaces, default/static methods.
๐น Pattern matching, text blocks, modules.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐ฉ๐ซ๐ข๐ง๐ & ๐๐ฉ๐ซ๐ข๐ง๐ ๐๐จ๐จ๐ญ
๐น Dependency Injection, IOC, Spring MVC.
๐น Bean lifecycle, scopes, profiles.
๐น REST API, CRUD, AOP, Exception handling.
๐น JWT, OAuth, actuators, WebFlux.
๐น Microservices, Spring Cloud, JPA.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐๐ญ๐๐๐๐ฌ๐ (๐๐๐/๐๐จ๐๐๐)
๐น JPA repositories, entity relationships.
๐น SQL queries (e.g., Nth highest salary).
๐น Relational and non-relational DB concepts.
๐น Joins, indexing, stored procedures.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐จ๐๐ข๐ง๐
๐น DSA-based questions.
๐น Sorting/searching with Java APIs.
๐น Stream API coding questions.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐๐ฏ๐๐ฉ๐ฌ & ๐๐๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐๐ง๐ญ
๐น Familiarize yourself with tools like Jenkins, Kubernetes, Kafka, and cloud technologies.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐๐ฌ๐ญ ๐๐ซ๐๐๐ญ๐ข๐๐๐ฌ
๐น Master design patterns like singleton, factory, observer, etc.
โจ Nail your interview with confidence! โจ
#JavaInterview #JavaDeveloper
Prepare these topics to ace your next Java interview! ๐
๐๐จ๐ฉ๐ข๐ ๐: ๐๐ซ๐จ๐ฃ๐๐๐ญ ๐ ๐ฅ๐จ๐ฐ ๐๐ง๐ ๐๐ซ๐๐ก๐ข๐ญ๐๐๐ญ๐ฎ๐ซ๐
๐น Describe your project and its architecture.
๐น Challenges faced and your role in the project.
๐น Tech stack used and the reasoning behind it.
๐น Problem-solving, collaboration, and lessons learned.
๐น Reflect on what you'd do differently.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐จ๐ซ๐ ๐๐๐ฏ๐
๐น String concepts (hashcode, equals).
๐น Immutability, OOPS concepts.
๐น Serialization, Collection Framework.
๐น Exception handling, multithreading.
๐น Java Memory Model, garbage collection.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐๐ฏ๐ ๐/๐๐/๐๐ Features
๐น Java 8 features: Lambda expressions, Stream API, Optional API.
๐น Functional interfaces, default/static methods.
๐น Pattern matching, text blocks, modules.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐ฉ๐ซ๐ข๐ง๐ & ๐๐ฉ๐ซ๐ข๐ง๐ ๐๐จ๐จ๐ญ
๐น Dependency Injection, IOC, Spring MVC.
๐น Bean lifecycle, scopes, profiles.
๐น REST API, CRUD, AOP, Exception handling.
๐น JWT, OAuth, actuators, WebFlux.
๐น Microservices, Spring Cloud, JPA.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐๐ญ๐๐๐๐ฌ๐ (๐๐๐/๐๐จ๐๐๐)
๐น JPA repositories, entity relationships.
๐น SQL queries (e.g., Nth highest salary).
๐น Relational and non-relational DB concepts.
๐น Joins, indexing, stored procedures.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐จ๐๐ข๐ง๐
๐น DSA-based questions.
๐น Sorting/searching with Java APIs.
๐น Stream API coding questions.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐๐ฏ๐๐ฉ๐ฌ & ๐๐๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐๐ง๐ญ
๐น Familiarize yourself with tools like Jenkins, Kubernetes, Kafka, and cloud technologies.
๐๐จ๐ฉ๐ข๐ ๐: ๐๐๐ฌ๐ญ ๐๐ซ๐๐๐ญ๐ข๐๐๐ฌ
๐น Master design patterns like singleton, factory, observer, etc.
โจ Nail your interview with confidence! โจ
#JavaInterview #JavaDeveloper
๐4โค2
๐ Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
๐5
Software development is complex, and the fancy names don't help.
Hashing vs. Encryption vs. Encoding
๐๐ฎ๐๐ต๐ถ๐ป๐ด
This is a one-way process used for data integrity verification.
When you hash data, you get a unique string representing the original data.
It's a one-way street; once you hash something, you can't get the original data back from the hash.
While multiple values can theoretically yield the same hash, well-crafted cryptographic hash functions make such collisions incredibly rare and nearly impossible to compute.
This property makes it perfect for verifying if someone altered the data.
If even one-bit changes in the original data, the hash changes dramatically.
๐๐ป๐ฐ๐ฟ๐๐ฝ๐๐ถ๐ผ๐ป
This is the real deal when it comes to data security.
It uses algorithms and keys to transform readable data (plaintext) into an unreadable format (ciphertext).
Only those with the correct key can unlock (decrypt) the data and read it.
This process is reversible, unlike hashing.
Encryption is critical for protecting sensitive data from unauthorized access.
๐๐ป๐ฐ๐ผ๐ฑ๐ถ๐ป๐ด
This is all about data representation.
It converts data from one format to another, making it easier to interpret and display.
Common formats:
โข Base64
โข UTF-8
โข ASCII
Encoding does NOT provide security! It's for data transmission and storage convenience.
One common use of hashing is for secure password storage.
When you create an account or set a password, the system hashes and stores the password in the database.
During login, the system hashes the provided password and compares it to the stored hash without revealing the password.
Hashing vs. Encryption vs. Encoding
๐๐ฎ๐๐ต๐ถ๐ป๐ด
This is a one-way process used for data integrity verification.
When you hash data, you get a unique string representing the original data.
It's a one-way street; once you hash something, you can't get the original data back from the hash.
While multiple values can theoretically yield the same hash, well-crafted cryptographic hash functions make such collisions incredibly rare and nearly impossible to compute.
This property makes it perfect for verifying if someone altered the data.
If even one-bit changes in the original data, the hash changes dramatically.
๐๐ป๐ฐ๐ฟ๐๐ฝ๐๐ถ๐ผ๐ป
This is the real deal when it comes to data security.
It uses algorithms and keys to transform readable data (plaintext) into an unreadable format (ciphertext).
Only those with the correct key can unlock (decrypt) the data and read it.
This process is reversible, unlike hashing.
Encryption is critical for protecting sensitive data from unauthorized access.
๐๐ป๐ฐ๐ผ๐ฑ๐ถ๐ป๐ด
This is all about data representation.
It converts data from one format to another, making it easier to interpret and display.
Common formats:
โข Base64
โข UTF-8
โข ASCII
Encoding does NOT provide security! It's for data transmission and storage convenience.
One common use of hashing is for secure password storage.
When you create an account or set a password, the system hashes and stores the password in the database.
During login, the system hashes the provided password and compares it to the stored hash without revealing the password.
๐7โค5
Top 5 Powerful Python Functions Every Developer Should Know
๐๐
https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a
๐๐
https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a
โ
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1. Web Development โ
โ๏ธ https://t.iss.one/webdevcoursefree
2. CSS โ
โ๏ธ https://css-tricks.com
3. JavaScript โ
โ๏ธ https://t.iss.one/javascript_courses
4. React โ
โ๏ธ https://react-tutorial.app
5. Tailwind CSS โ
โ๏ธ https://scrimba.com
6. Data Science โ
โ๏ธ https://t.iss.one/datasciencefun
7. Python โ
โ๏ธ https://pythontutorial.net
8. SQL โ
โ๏ธ https://t.iss.one/sqlanalyst
โ๏ธ https://stratascratch.com/?via=free
9. Git and GitHub โ
โ๏ธ https://GitFluence.com
10. Blockchain โ
โ๏ธ https://t.iss.one/Bitcoin_Crypto_Web
11. Mongo DB โ
โ๏ธ https://mongodb.com
12. Node JS โ
โ๏ธ https://nodejsera.com
13. English Speaking โ
โ๏ธ https://t.iss.one/englishlearnerspro
14. C#โ
โ๏ธhttps://learn.microsoft.com/en-us/training/paths/get-started-c-sharp-part-1/
15. Excelโ
โ๏ธ https://t.iss.one/excel_analyst
16. Generative AIโ
โ๏ธ https://t.iss.one/generativeai_gpt
17. App Development โ
โ๏ธ https://t.iss.one/appsuser
18. Power BI โ
โ๏ธ https://t.iss.one/powerbi_analyst
19. Tableau โ
โ๏ธ https://www.tableau.com/learn/training
20. Machine Learning โ
โ๏ธ https://developers.google.com/machine-learning/crash-course
21. Artificial intelligence โ
โ๏ธ https://t.iss.one/machinelearning_deeplearning/
22. Data Analytics โ
โ๏ธ https://medium.com/@data_analyst
โ๏ธ https://www.linkedin.com/company/sql-analysts
23. Java โ
โ๏ธ https://t.iss.one/Java_Programming_Notes
โ๏ธ https://learn.microsoft.com/shows/java-for-beginners/
24. C/C++ โ
โ๏ธ https://imp.i115008.net/kjoq9V
โ๏ธ https://docs.microsoft.com/en-us/cpp/c-language/?view=msvc-170&viewFallbackFrom=vs-2019
25. Data Structures โ
โ๏ธ https://leetcode.com/study-plan/data-structure/
26. Cybersecurity โ
โ๏ธ https://t.iss.one/EthicalHackingToday
27. Linux โ
โ๏ธ https://bit.ly/3KhPdf1
โ๏ธ https://training.linuxfoundation.org/resources/
28. Typescript โ
โ๏ธ https://learn.microsoft.com/training/paths/build-javascript-applications-typescript/
29. Deep Learning โ
โ๏ธ https://introtodeeplearning.com
30. Compiler Design โ
โ๏ธ https://online.stanford.edu/courses/soe-ycscs1-compilers
31. DSA โ
โ๏ธ https://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/
32. Prompt Engineering โ
โ๏ธ https://www.promptingguide.ai/
โ๏ธ https://t.iss.one/aiindi
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