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
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7. Python โ
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8. SQL โ
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โ๏ธ https://stratascratch.com/?via=free
9. Git and GitHub โ
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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
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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
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21. Artificial intelligence โ
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23. Java โ
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24. C/C++ โ
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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
Join @free4unow_backup for more free courses
Like for more โค๏ธ
ENJOY LEARNING๐๐
๐10โค7