Java Backend Development is a highly in-demand and well-paying job in the tech industry.
If you're looking to become an excellent Java Developer, here's a roadmap that includes various online resourcesππ
https://t.iss.one/Java_Programming_Notes/15
If you're looking to become an excellent Java Developer, here's a roadmap that includes various online resourcesππ
https://t.iss.one/Java_Programming_Notes/15
π8β€2
30-Day Roadmap to Learn Android App Development up to an Intermediate Level
Week 1: Setting the Foundation
*Day 1-2:*
- Familiarize yourself with the basics of Android development and set up Android Studio.
- Create a simple "Hello, Android!" app and run it on an emulator or a physical device.
*Day 3-4:*
- Understand the Android project structure and layout files (XML).
- Explore activities and their lifecycle in Android.
*Day 5-7:*
- Dive into user interface components like buttons, text views, and layouts.
- Build a basic interactive app with user input.
Week 2: Functionality and Navigation
*Day 8-9:*
- Study how to handle button clicks and user interactions.
- Learn about intents and navigation between activities.
*Day 10-12:*
- Explore fragments for modular UI components.
- Understand how to pass data between activities and fragments.
*Day 13-14:*
- Practice creating and using custom views.
- Build a small project involving multiple activities and fragments.
Week 3: Data Management
*Day 15-17:*
- Learn about data storage options: SharedPreferences and internal storage.
- Understand how to work with SQLite databases in Android.
*Day 18-19:*
- Study content providers and how to share data between apps.
- Practice implementing data persistence in a project.
*Day 20-21:*
- Explore background processing and AsyncTask for handling long-running tasks.
- Understand the basics of threading and handling concurrency.
Week 4: Advanced Topics
*Day 22-23:*
- Dive into handling permissions in Android apps.
- Work on projects involving file operations and reading/writing to external storage.
*Day 24-26:*
- Learn about services and background processing.
- Explore broadcast receivers and how to respond to system-wide events.
*Day 27-28:*
- Study advanced UI components like RecyclerView for efficient list displays.
- Explore Android's networking capabilities and make API requests.
*Day 29-30:*
- Delve into more advanced topics like dependency injection (e.g., Dagger).
- Explore additional libraries and frameworks relevant to your interests (e.g., Retrofit for networking, Room for database management).
- Work on a complex project that combines your knowledge from the past weeks.
Throughout the 30 days, practice coding daily, consult Android documentation, and leverage online resources for additional guidance. Adapt the roadmap based on your progress and interests. Good luck with your Android app development journey!
Week 1: Setting the Foundation
*Day 1-2:*
- Familiarize yourself with the basics of Android development and set up Android Studio.
- Create a simple "Hello, Android!" app and run it on an emulator or a physical device.
*Day 3-4:*
- Understand the Android project structure and layout files (XML).
- Explore activities and their lifecycle in Android.
*Day 5-7:*
- Dive into user interface components like buttons, text views, and layouts.
- Build a basic interactive app with user input.
Week 2: Functionality and Navigation
*Day 8-9:*
- Study how to handle button clicks and user interactions.
- Learn about intents and navigation between activities.
*Day 10-12:*
- Explore fragments for modular UI components.
- Understand how to pass data between activities and fragments.
*Day 13-14:*
- Practice creating and using custom views.
- Build a small project involving multiple activities and fragments.
Week 3: Data Management
*Day 15-17:*
- Learn about data storage options: SharedPreferences and internal storage.
- Understand how to work with SQLite databases in Android.
*Day 18-19:*
- Study content providers and how to share data between apps.
- Practice implementing data persistence in a project.
*Day 20-21:*
- Explore background processing and AsyncTask for handling long-running tasks.
- Understand the basics of threading and handling concurrency.
Week 4: Advanced Topics
*Day 22-23:*
- Dive into handling permissions in Android apps.
- Work on projects involving file operations and reading/writing to external storage.
*Day 24-26:*
- Learn about services and background processing.
- Explore broadcast receivers and how to respond to system-wide events.
*Day 27-28:*
- Study advanced UI components like RecyclerView for efficient list displays.
- Explore Android's networking capabilities and make API requests.
*Day 29-30:*
- Delve into more advanced topics like dependency injection (e.g., Dagger).
- Explore additional libraries and frameworks relevant to your interests (e.g., Retrofit for networking, Room for database management).
- Work on a complex project that combines your knowledge from the past weeks.
Throughout the 30 days, practice coding daily, consult Android documentation, and leverage online resources for additional guidance. Adapt the roadmap based on your progress and interests. Good luck with your Android app development journey!
π16
Complete DSA Roadmap
|-- Basic_Data_Structures
| |-- Arrays
| |-- Strings
| |-- Linked_Lists
| |-- Stacks
| ββ Queues
|
|-- Advanced_Data_Structures
| |-- Trees
| | |-- Binary_Trees
| | |-- Binary_Search_Trees
| | |-- AVL_Trees
| | ββ B-Trees
| |
| |-- Graphs
| | |-- Graph_Representation
| | | |- Adjacency_Matrix
| | | β Adjacency_List
| | |
| | |-- Depth-First_Search
| | |-- Breadth-First_Search
| | |-- Shortest_Path_Algorithms
| | | |- Dijkstra's_Algorithm
| | | β Bellman-Ford_Algorithm
| | |
| | ββ Minimum_Spanning_Tree
| | |- Prim's_Algorithm
| | β Kruskal's_Algorithm
| |
| |-- Heaps
| | |-- Min_Heap
| | |-- Max_Heap
| | ββ Heap_Sort
| |
| |-- Hash_Tables
| |-- Disjoint_Set_Union
| |-- Trie
| |-- Segment_Tree
| ββ Fenwick_Tree
|
|-- Algorithmic_Paradigms
| |-- Brute_Force
| |-- Divide_and_Conquer
| |-- Greedy_Algorithms
| |-- Dynamic_Programming
| |-- Backtracking
| |-- Sliding_Window_Technique
| |-- Two_Pointer_Technique
| ββ Divide_and_Conquer_Optimization
| |-- Merge_Sort_Tree
| ββ Persistent_Segment_Tree
|
|-- Searching_Algorithms
| |-- Linear_Search
| |-- Binary_Search
| |-- Depth-First_Search
| ββ Breadth-First_Search
|
|-- Sorting_Algorithms
| |-- Bubble_Sort
| |-- Selection_Sort
| |-- Insertion_Sort
| |-- Merge_Sort
| |-- Quick_Sort
| ββ Heap_Sort
|
|-- Graph_Algorithms
| |-- Depth-First_Search
| |-- Breadth-First_Search
| |-- Topological_Sort
| |-- Strongly_Connected_Components
| ββ Articulation_Points_and_Bridges
|
|-- Dynamic_Programming
| |-- Introduction_to_DP
| |-- Fibonacci_Series_using_DP
| |-- Longest_Common_Subsequence
| |-- Longest_Increasing_Subsequence
| |-- Knapsack_Problem
| |-- Matrix_Chain_Multiplication
| ββ Dynamic_Programming_on_Trees
|
|-- Mathematical_and_Bit_Manipulation_Algorithms
| |-- Prime_Numbers_and_Sieve_of_Eratosthenes
| |-- Greatest_Common_Divisor
| |-- Least_Common_Multiple
| |-- Modular_Arithmetic
| ββ Bit_Manipulation_Tricks
|
|-- Advanced_Topics
| |-- Trie-based_Algorithms
| | |-- Auto-completion
| | ββ Spell_Checker
| |
| |-- Suffix_Trees_and_Arrays
| |-- Computational_Geometry
| |-- Number_Theory
| | |-- Euler's_Totient_Function
| | ββ Mobius_Function
| |
| ββ String_Algorithms
| |-- KMP_Algorithm
| ββ Rabin-Karp_Algorithm
|
|-- OnlinePlatforms
| |-- LeetCode
| |-- HackerRank
Best DSA RESOURCES: https://topmate.io/coding/886874
Credits: https://t.iss.one/free4unow_backup
All the best ππ
|-- Basic_Data_Structures
| |-- Arrays
| |-- Strings
| |-- Linked_Lists
| |-- Stacks
| ββ Queues
|
|-- Advanced_Data_Structures
| |-- Trees
| | |-- Binary_Trees
| | |-- Binary_Search_Trees
| | |-- AVL_Trees
| | ββ B-Trees
| |
| |-- Graphs
| | |-- Graph_Representation
| | | |- Adjacency_Matrix
| | | β Adjacency_List
| | |
| | |-- Depth-First_Search
| | |-- Breadth-First_Search
| | |-- Shortest_Path_Algorithms
| | | |- Dijkstra's_Algorithm
| | | β Bellman-Ford_Algorithm
| | |
| | ββ Minimum_Spanning_Tree
| | |- Prim's_Algorithm
| | β Kruskal's_Algorithm
| |
| |-- Heaps
| | |-- Min_Heap
| | |-- Max_Heap
| | ββ Heap_Sort
| |
| |-- Hash_Tables
| |-- Disjoint_Set_Union
| |-- Trie
| |-- Segment_Tree
| ββ Fenwick_Tree
|
|-- Algorithmic_Paradigms
| |-- Brute_Force
| |-- Divide_and_Conquer
| |-- Greedy_Algorithms
| |-- Dynamic_Programming
| |-- Backtracking
| |-- Sliding_Window_Technique
| |-- Two_Pointer_Technique
| ββ Divide_and_Conquer_Optimization
| |-- Merge_Sort_Tree
| ββ Persistent_Segment_Tree
|
|-- Searching_Algorithms
| |-- Linear_Search
| |-- Binary_Search
| |-- Depth-First_Search
| ββ Breadth-First_Search
|
|-- Sorting_Algorithms
| |-- Bubble_Sort
| |-- Selection_Sort
| |-- Insertion_Sort
| |-- Merge_Sort
| |-- Quick_Sort
| ββ Heap_Sort
|
|-- Graph_Algorithms
| |-- Depth-First_Search
| |-- Breadth-First_Search
| |-- Topological_Sort
| |-- Strongly_Connected_Components
| ββ Articulation_Points_and_Bridges
|
|-- Dynamic_Programming
| |-- Introduction_to_DP
| |-- Fibonacci_Series_using_DP
| |-- Longest_Common_Subsequence
| |-- Longest_Increasing_Subsequence
| |-- Knapsack_Problem
| |-- Matrix_Chain_Multiplication
| ββ Dynamic_Programming_on_Trees
|
|-- Mathematical_and_Bit_Manipulation_Algorithms
| |-- Prime_Numbers_and_Sieve_of_Eratosthenes
| |-- Greatest_Common_Divisor
| |-- Least_Common_Multiple
| |-- Modular_Arithmetic
| ββ Bit_Manipulation_Tricks
|
|-- Advanced_Topics
| |-- Trie-based_Algorithms
| | |-- Auto-completion
| | ββ Spell_Checker
| |
| |-- Suffix_Trees_and_Arrays
| |-- Computational_Geometry
| |-- Number_Theory
| | |-- Euler's_Totient_Function
| | ββ Mobius_Function
| |
| ββ String_Algorithms
| |-- KMP_Algorithm
| ββ Rabin-Karp_Algorithm
|
|-- OnlinePlatforms
| |-- LeetCode
| |-- HackerRank
Best DSA RESOURCES: https://topmate.io/coding/886874
Credits: https://t.iss.one/free4unow_backup
All the best ππ
π31β€3
List of most asked Programming Interview Questions.
Are you preparing for a coding interview? This tweet is for you. It contains a list of the most asked interview questions from each topic.
Arrays
- How is an array sorted using quicksort?
- How do you reverse an array?
- How do you remove duplicates from an array?
- How do you find the 2nd largest number in an unsorted integer array?
Linked Lists
- How do you find the length of a linked list?
- How do you reverse a linked list?
- How do you find the third node from the end?
- How are duplicate nodes removed in an unsorted linked list?
Strings
- How do you check if a string contains only digits?
- How can a given string be reversed?
- How do you find the first non-repeated character?
- How do you find duplicate characters in strings?
Binary Trees
- How are all leaves of a binary tree printed?
- How do you check if a tree is a binary search tree?
- How is a binary search tree implemented?
- Find the lowest common ancestor in a binary tree?
Graph
- How to detect a cycle in a directed graph?
- How to detect a cycle in an undirected graph?
- Find the total number of strongly connected components?
- Find whether a path exists between two nodes of a graph?
- Find the minimum number of swaps required to sort an array.
Dynamic Programming
1. Find the longest common subsequence?
2. Find the longest common substring?
3. Coin change problem?
4. Box stacking problem?
5. Count the number of ways to cover a distance?
Are you preparing for a coding interview? This tweet is for you. It contains a list of the most asked interview questions from each topic.
Arrays
- How is an array sorted using quicksort?
- How do you reverse an array?
- How do you remove duplicates from an array?
- How do you find the 2nd largest number in an unsorted integer array?
Linked Lists
- How do you find the length of a linked list?
- How do you reverse a linked list?
- How do you find the third node from the end?
- How are duplicate nodes removed in an unsorted linked list?
Strings
- How do you check if a string contains only digits?
- How can a given string be reversed?
- How do you find the first non-repeated character?
- How do you find duplicate characters in strings?
Binary Trees
- How are all leaves of a binary tree printed?
- How do you check if a tree is a binary search tree?
- How is a binary search tree implemented?
- Find the lowest common ancestor in a binary tree?
Graph
- How to detect a cycle in a directed graph?
- How to detect a cycle in an undirected graph?
- Find the total number of strongly connected components?
- Find whether a path exists between two nodes of a graph?
- Find the minimum number of swaps required to sort an array.
Dynamic Programming
1. Find the longest common subsequence?
2. Find the longest common substring?
3. Coin change problem?
4. Box stacking problem?
5. Count the number of ways to cover a distance?
π20β€2
_Operating System RoadMap
|
|-- Kernel
| |-- Memory Management
| | |-- Paging
| | |-- Segmentation
| | |-- Virtual Memory
| |
| |-- Process Management
| | |-- Process Scheduling
| | |-- Inter-Process Communication (IPC)
| | |-- Threads
| |
| |-- File System
| | |-- File I/O
| | |-- Directory Structure
| | |-- File Permissions
| |
| |-- Device Drivers
| | |-- Communication with Hardware
| | |-- Input/Output (I/O)
| |
| |-- System Calls
| |-- Interface to Kernel Functionality
| |-- Examples: open(), read(), write(), etc.
|
|-- Memory Management
| |-- RAM
| | |-- Stack
| | |-- Heap
| | |-- Data Segment
| | |-- Code Segment
| |
| |-- Cache
| | |-- L1, L2, L3 Caches
| |
| |-- Virtual Memory
| |-- Page Table
| |-- Page Replacement Algorithms
| |-- Swapping
|
|-- File System
| |-- File Organization
| |-- File Allocation Table (FAT)
| |-- Inodes
| |-- File Access Methods
|
|-- Networking
| |-- TCP/IP
| |-- Protocols
| |-- Network Stack
| |-- Routing
| |-- Firewalls
|
|-- Security
| |-- Authentication
| |-- Authorization
| |-- Encryption
| |-- Access Control Lists (ACL)
|
|-- Process Management
| |-- PCB (Process Control Block)
| |-- Context Switching
| |-- Deadlocks
| |-- Synchronization
| |-- Mutual Exclusion
|
|-- Device Management
| |-- I/O Buffering
| |-- Device Controllers
| |-- Interrupt Handling
| |-- DMA (Direct Memory Access)
|
|-- User Interface
| |-- Graphical User Interface (GUI)
| |-- Command Line Interface (CLI)
| |-- Windowing Systems
|
|-- Shell
| |-- Command Interpreter
| |-- Scripting
| |-- Job Control
|
|-- System Utilities
| |-- Task Manager
| |-- Disk Cleanup
| |-- System Monitor
| |-- Backup and Restore
|
|-- Boot Process
| |-- BIOS/UEFI
| |-- Boot Loader
| |-- Kernel Initialization
| |-- Init Process
|
|-- System Libraries
| |-- Standard C Library
| |-- POSIX Library
| |-- WinAPI (for Windows)
|
|-- System Calls
| |-- File System Calls
| |-- Process Control Calls
| |-- Memory Management Calls
| |-- Communication Calls
|
|-- Error Handling
| |-- Error Codes
| |-- Logging
| |-- Recovery Strategies
|
|-- Distributed Systems
| |-- Clustering
| |-- Load Balancing
| |-- Distributed File Systems
|
|-- Cloud Computing
| |-- Virtualization
| |-- Infrastructure as a Service (IaaS)
| |-- Platform as a Service (PaaS)
| |-- Software as a Service (SaaS)
|
β-- Comments
|-- // Single-line comment
β-- /* Multi-line comment */
Join for more: https://t.iss.one/programming_guide
|
|-- Kernel
| |-- Memory Management
| | |-- Paging
| | |-- Segmentation
| | |-- Virtual Memory
| |
| |-- Process Management
| | |-- Process Scheduling
| | |-- Inter-Process Communication (IPC)
| | |-- Threads
| |
| |-- File System
| | |-- File I/O
| | |-- Directory Structure
| | |-- File Permissions
| |
| |-- Device Drivers
| | |-- Communication with Hardware
| | |-- Input/Output (I/O)
| |
| |-- System Calls
| |-- Interface to Kernel Functionality
| |-- Examples: open(), read(), write(), etc.
|
|-- Memory Management
| |-- RAM
| | |-- Stack
| | |-- Heap
| | |-- Data Segment
| | |-- Code Segment
| |
| |-- Cache
| | |-- L1, L2, L3 Caches
| |
| |-- Virtual Memory
| |-- Page Table
| |-- Page Replacement Algorithms
| |-- Swapping
|
|-- File System
| |-- File Organization
| |-- File Allocation Table (FAT)
| |-- Inodes
| |-- File Access Methods
|
|-- Networking
| |-- TCP/IP
| |-- Protocols
| |-- Network Stack
| |-- Routing
| |-- Firewalls
|
|-- Security
| |-- Authentication
| |-- Authorization
| |-- Encryption
| |-- Access Control Lists (ACL)
|
|-- Process Management
| |-- PCB (Process Control Block)
| |-- Context Switching
| |-- Deadlocks
| |-- Synchronization
| |-- Mutual Exclusion
|
|-- Device Management
| |-- I/O Buffering
| |-- Device Controllers
| |-- Interrupt Handling
| |-- DMA (Direct Memory Access)
|
|-- User Interface
| |-- Graphical User Interface (GUI)
| |-- Command Line Interface (CLI)
| |-- Windowing Systems
|
|-- Shell
| |-- Command Interpreter
| |-- Scripting
| |-- Job Control
|
|-- System Utilities
| |-- Task Manager
| |-- Disk Cleanup
| |-- System Monitor
| |-- Backup and Restore
|
|-- Boot Process
| |-- BIOS/UEFI
| |-- Boot Loader
| |-- Kernel Initialization
| |-- Init Process
|
|-- System Libraries
| |-- Standard C Library
| |-- POSIX Library
| |-- WinAPI (for Windows)
|
|-- System Calls
| |-- File System Calls
| |-- Process Control Calls
| |-- Memory Management Calls
| |-- Communication Calls
|
|-- Error Handling
| |-- Error Codes
| |-- Logging
| |-- Recovery Strategies
|
|-- Distributed Systems
| |-- Clustering
| |-- Load Balancing
| |-- Distributed File Systems
|
|-- Cloud Computing
| |-- Virtualization
| |-- Infrastructure as a Service (IaaS)
| |-- Platform as a Service (PaaS)
| |-- Software as a Service (SaaS)
|
β-- Comments
|-- // Single-line comment
β-- /* Multi-line comment */
Join for more: https://t.iss.one/programming_guide
π16β€2
Forwarded from Coding Memes
Advantages of being SINGLE
1. You can sleep well.
2. You can save time and money.
3. No worries about how you look.
4. No missed calls in the midnight.
5. No need to recharge more than twice a day.
6. You can talk to all boys/girls.
7. You can eat well.
8. No sc0ldings from parents/guardians.
9. You can eat in any restaurant.
10. You can visit anybody.
11. Can pick any call, any time without being questioned.
12. Don't worry about missed calls.
13. You can do whatever you want.
1. You can sleep well.
2. You can save time and money.
3. No worries about how you look.
4. No missed calls in the midnight.
5. No need to recharge more than twice a day.
6. You can talk to all boys/girls.
7. You can eat well.
8. No sc0ldings from parents/guardians.
9. You can eat in any restaurant.
10. You can visit anybody.
11. Can pick any call, any time without being questioned.
12. Don't worry about missed calls.
13. You can do whatever you want.
π46β€26π7π4
How to Learn Java in 2024
1. Set Clear Goals:
- Define your learning objectives. Do you want to build web applications, mobile apps, or work on enterprise-level software?
2. Choose a Structured Learning Path:
- Follow a structured learning path that covers the fundamentals of Java, object-oriented programming principles, and essential libraries.
3. Start with the Basics:
- Begin with the core concepts of Java, such as variables, data types, operators, and control flow statements.
4. Master Object-Oriented Programming:
- Learn about classes, objects, inheritance, polymorphism, and encapsulation.
5. Explore Java Libraries:
- Familiarize yourself with commonly used Java libraries, such as those for input/output, networking, and data structures.
6. Practice Regularly:
- Write code regularly to reinforce your understanding and identify areas where you need more practice.
7. Leverage Online Resources:
- Utilize online courses, tutorials, and documentation to supplement your learning.
8. Join a Coding Community:
- Engage with online coding communities and forums to ask questions, share knowledge, and collaborate on projects.
9. Build Projects:
- Create simple projects to apply your skills and gain practical experience.
10. Stay Updated with Java Releases:
- Keep up with the latest Java releases and updates to ensure your knowledge remains current.
11. Explore Frameworks and Tools:
- Learn about popular Java frameworks and tools, such as Spring Boot, Maven, and IntelliJ IDEA.
12. Contribute to Open Source Projects:
- Contribute to open source Java projects to gain real-world experience and showcase your skills.
13. Seek Feedback and Mentoring:
- Seek feedback from experienced Java developers and consider mentorship opportunities to accelerate your learning.
14. Prepare for Certifications:
- Consider pursuing Java certifications, such as the Oracle Certified Java Programmer (OCJP), to validate your skills.
15. Network with Java Developers:
- Attend Java meetups, conferences, and online events to connect with other Java developers and learn from their experiences.
Best Programming Resources: https://topmate.io/coding/898340
Java Programming Resources: https://t.iss.one/Java_Programming_Notes
ENJOY LEARNING ππ
1. Set Clear Goals:
- Define your learning objectives. Do you want to build web applications, mobile apps, or work on enterprise-level software?
2. Choose a Structured Learning Path:
- Follow a structured learning path that covers the fundamentals of Java, object-oriented programming principles, and essential libraries.
3. Start with the Basics:
- Begin with the core concepts of Java, such as variables, data types, operators, and control flow statements.
4. Master Object-Oriented Programming:
- Learn about classes, objects, inheritance, polymorphism, and encapsulation.
5. Explore Java Libraries:
- Familiarize yourself with commonly used Java libraries, such as those for input/output, networking, and data structures.
6. Practice Regularly:
- Write code regularly to reinforce your understanding and identify areas where you need more practice.
7. Leverage Online Resources:
- Utilize online courses, tutorials, and documentation to supplement your learning.
8. Join a Coding Community:
- Engage with online coding communities and forums to ask questions, share knowledge, and collaborate on projects.
9. Build Projects:
- Create simple projects to apply your skills and gain practical experience.
10. Stay Updated with Java Releases:
- Keep up with the latest Java releases and updates to ensure your knowledge remains current.
11. Explore Frameworks and Tools:
- Learn about popular Java frameworks and tools, such as Spring Boot, Maven, and IntelliJ IDEA.
12. Contribute to Open Source Projects:
- Contribute to open source Java projects to gain real-world experience and showcase your skills.
13. Seek Feedback and Mentoring:
- Seek feedback from experienced Java developers and consider mentorship opportunities to accelerate your learning.
14. Prepare for Certifications:
- Consider pursuing Java certifications, such as the Oracle Certified Java Programmer (OCJP), to validate your skills.
15. Network with Java Developers:
- Attend Java meetups, conferences, and online events to connect with other Java developers and learn from their experiences.
Best Programming Resources: https://topmate.io/coding/898340
Java Programming Resources: https://t.iss.one/Java_Programming_Notes
ENJOY LEARNING ππ
π14π4
Famous programming languages and their frameworks
1. Python:
Frameworks:
Django
Flask
Pyramid
Tornado
2. JavaScript:
Frameworks (Front-End):
React
Angular
Vue.js
Ember.js
Frameworks (Back-End):
Node.js (Runtime)
Express.js
Nest.js
Meteor
3. Java:
Frameworks:
Spring Framework
Hibernate
Apache Struts
Play Framework
4. Ruby:
Frameworks:
Ruby on Rails (Rails)
Sinatra
Hanami
5. PHP:
Frameworks:
Laravel
Symfony
CodeIgniter
Yii
Zend Framework
6. C#:
Frameworks:
.NET Framework
ASP.NET
ASP.NET Core
7. Go (Golang):
Frameworks:
Gin
Echo
Revel
8. Rust:
Frameworks:
Rocket
Actix
Warp
9. Swift:
Frameworks (iOS/macOS):
SwiftUI
UIKit
Cocoa Touch
10. Kotlin:
- Frameworks (Android):
- Android Jetpack
- Ktor
11. TypeScript:
- Frameworks (Front-End):
- Angular
- Vue.js (with TypeScript)
- React (with TypeScript)
12. Scala:
- Frameworks:
- Play Framework
- Akka
13. Perl:
- Frameworks:
- Dancer
- Catalyst
14. Lua:
- Frameworks:
- OpenResty (for web development)
15. Dart:
- Frameworks:
- Flutter (for mobile app development)
16. R:
- Frameworks (for data science and statistics):
- Shiny
- ggplot2
17. Julia:
- Frameworks (for scientific computing):
- Pluto.jl
- Genie.jl
18. MATLAB:
- Frameworks (for scientific and engineering applications):
- Simulink
19. COBOL:
- Frameworks:
- COBOL-IT
20. Erlang:
- Frameworks:
- Phoenix (for web applications)
21. Groovy:
- Frameworks:
- Grails (for web applications)
Best Programming Resources: https://topmate.io/coding/898340
ENJOY LEARNING ππ
1. Python:
Frameworks:
Django
Flask
Pyramid
Tornado
2. JavaScript:
Frameworks (Front-End):
React
Angular
Vue.js
Ember.js
Frameworks (Back-End):
Node.js (Runtime)
Express.js
Nest.js
Meteor
3. Java:
Frameworks:
Spring Framework
Hibernate
Apache Struts
Play Framework
4. Ruby:
Frameworks:
Ruby on Rails (Rails)
Sinatra
Hanami
5. PHP:
Frameworks:
Laravel
Symfony
CodeIgniter
Yii
Zend Framework
6. C#:
Frameworks:
.NET Framework
ASP.NET
ASP.NET Core
7. Go (Golang):
Frameworks:
Gin
Echo
Revel
8. Rust:
Frameworks:
Rocket
Actix
Warp
9. Swift:
Frameworks (iOS/macOS):
SwiftUI
UIKit
Cocoa Touch
10. Kotlin:
- Frameworks (Android):
- Android Jetpack
- Ktor
11. TypeScript:
- Frameworks (Front-End):
- Angular
- Vue.js (with TypeScript)
- React (with TypeScript)
12. Scala:
- Frameworks:
- Play Framework
- Akka
13. Perl:
- Frameworks:
- Dancer
- Catalyst
14. Lua:
- Frameworks:
- OpenResty (for web development)
15. Dart:
- Frameworks:
- Flutter (for mobile app development)
16. R:
- Frameworks (for data science and statistics):
- Shiny
- ggplot2
17. Julia:
- Frameworks (for scientific computing):
- Pluto.jl
- Genie.jl
18. MATLAB:
- Frameworks (for scientific and engineering applications):
- Simulink
19. COBOL:
- Frameworks:
- COBOL-IT
20. Erlang:
- Frameworks:
- Phoenix (for web applications)
21. Groovy:
- Frameworks:
- Grails (for web applications)
Best Programming Resources: https://topmate.io/coding/898340
ENJOY LEARNING ππ
π27β€6π1
Before diving into the 30-day learning plan for DSA, it is essential to have a few prerequisites covered to ensure you can follow the plan effectively:
### Prerequisites:
1. Basic Programming Knowledge:
- You should be familiar with at least one programming language (such as Python, Java, C++, or JavaScript).
- Understand basic syntax, data types, and control structures (loops, conditionals, functions).
2. Problem-Solving Mindset:
- Be comfortable with solving basic problems on platforms like LeetCode, HackerRank, or CodeSignal.
- Understand how to break down a problem into smaller, manageable parts.
3. Familiarity with Basic Concepts:
- Basic understanding of time and space complexity.
- Familiarity with simple algorithms and how they work (e.g., sorting algorithms like bubble sort or insertion sort).
### Suggested Preparatory Steps:
1. Language Proficiency:
- Python: Understand lists, dictionaries, sets, and basic input/output operations.
- Java: Understand arrays, ArrayList, HashMap, basic file I/O, and exception handling.
- C++: Understand vectors, maps, strings, basic I/O operations, and pointers.
2. Basic Algorithmic Concepts:
- Time Complexity: Learn Big O notation and how to analyze the time complexity of basic operations.
- Sorting Algorithms: Learn at least one simple sorting algorithm (e.g., bubble sort or selection sort).
3. Mathematical Foundations:
- Basic understanding of mathematical concepts like logarithms, exponentiation, and basic probability/statistics.
4. Basic Data Structures:
- Arrays and Strings: Be comfortable manipulating arrays and strings.
- Linked Lists: Understand the concept of linked lists and basic operations on them.
- Stacks and Queues: Understand what stacks and queues are and their basic operations.
5. Online Courses and Resources:
- Consider taking a basic course on data structures and algorithms if youβre entirely new to the topic. Courses on platforms like Udacity, or freeCodeCamp can be beneficial.
- Familiarize yourself with online coding platforms (LeetCode, HackerRank) and solve a few easy problems to get comfortable with the interface and problem -solving environment.
Best Programming Resources: https://topmate.io/coding/886839
ENJOY LEARNING ππ
### Prerequisites:
1. Basic Programming Knowledge:
- You should be familiar with at least one programming language (such as Python, Java, C++, or JavaScript).
- Understand basic syntax, data types, and control structures (loops, conditionals, functions).
2. Problem-Solving Mindset:
- Be comfortable with solving basic problems on platforms like LeetCode, HackerRank, or CodeSignal.
- Understand how to break down a problem into smaller, manageable parts.
3. Familiarity with Basic Concepts:
- Basic understanding of time and space complexity.
- Familiarity with simple algorithms and how they work (e.g., sorting algorithms like bubble sort or insertion sort).
### Suggested Preparatory Steps:
1. Language Proficiency:
- Python: Understand lists, dictionaries, sets, and basic input/output operations.
- Java: Understand arrays, ArrayList, HashMap, basic file I/O, and exception handling.
- C++: Understand vectors, maps, strings, basic I/O operations, and pointers.
2. Basic Algorithmic Concepts:
- Time Complexity: Learn Big O notation and how to analyze the time complexity of basic operations.
- Sorting Algorithms: Learn at least one simple sorting algorithm (e.g., bubble sort or selection sort).
3. Mathematical Foundations:
- Basic understanding of mathematical concepts like logarithms, exponentiation, and basic probability/statistics.
4. Basic Data Structures:
- Arrays and Strings: Be comfortable manipulating arrays and strings.
- Linked Lists: Understand the concept of linked lists and basic operations on them.
- Stacks and Queues: Understand what stacks and queues are and their basic operations.
5. Online Courses and Resources:
- Consider taking a basic course on data structures and algorithms if youβre entirely new to the topic. Courses on platforms like Udacity, or freeCodeCamp can be beneficial.
- Familiarize yourself with online coding platforms (LeetCode, HackerRank) and solve a few easy problems to get comfortable with the interface and problem -solving environment.
Best Programming Resources: https://topmate.io/coding/886839
ENJOY LEARNING ππ
π18β€3
π΄ How to MASTER a programming language using ChatGPT: π
1. Can you provide some tips and best practices for writing clean and efficient code in [lang]?
2. What are some commonly asked interview questions about [lang]?
3. What are the advanced topics to learn in [lang]? Explain them to me with code examples.
4. Give me some practice questions along with solutions for [concept] in [lang].
5. What are some common mistakes that people make in [lang]?
6. Can you provide some tips and best practices for writing clean and efficient code in [lang]?
7. How can I optimize the performance of my code in [lang]?
8. What are some coding exercises or mini-projects I can do regularly to reinforce my understanding and application of [lang] concepts?
9. Are there any specific tools or frameworks that are commonly used in [lang]? How can I learn and utilize them effectively?
10. What are the debugging techniques and tools available in [lang] to help troubleshoot and fix code issues?
11. Are there any coding conventions or style guidelines that I should follow when writing code in [lang]?
12. How can I effectively collaborate with other developers in [lang] on a project?
13. What are some common data structures and algorithms that I should be familiar with in [lang]?
How to Create Resume using ChatGPT ππ
https://t.iss.one/free4unow_backup/687
Master DSA ππ
https://t.iss.one/dsabooks/156
1. Can you provide some tips and best practices for writing clean and efficient code in [lang]?
2. What are some commonly asked interview questions about [lang]?
3. What are the advanced topics to learn in [lang]? Explain them to me with code examples.
4. Give me some practice questions along with solutions for [concept] in [lang].
5. What are some common mistakes that people make in [lang]?
6. Can you provide some tips and best practices for writing clean and efficient code in [lang]?
7. How can I optimize the performance of my code in [lang]?
8. What are some coding exercises or mini-projects I can do regularly to reinforce my understanding and application of [lang] concepts?
9. Are there any specific tools or frameworks that are commonly used in [lang]? How can I learn and utilize them effectively?
10. What are the debugging techniques and tools available in [lang] to help troubleshoot and fix code issues?
11. Are there any coding conventions or style guidelines that I should follow when writing code in [lang]?
12. How can I effectively collaborate with other developers in [lang] on a project?
13. What are some common data structures and algorithms that I should be familiar with in [lang]?
How to Create Resume using ChatGPT ππ
https://t.iss.one/free4unow_backup/687
Master DSA ππ
https://t.iss.one/dsabooks/156
π16π1
π Roadmap to Master C++ in 50 Days! π₯οΈ
Here's a concise 50-day plan to get you started:
Week 1-2:
β’ Days 1-5: Programming Language & its application
β’ Days 6-10: Basic Concepts - Operations
Week 3-4:
β’ Days 11-15: Strings & Variables
β’ Days 16-20: Control Structures
Week 5-6:
β’ Days 21-25: Functions & Header Files
β’ Days 26-30: Exception Handling & File Operations
Week 7-8:
β’ Days 31-35: Advanced Class Concepts
β’ Days 36-40: Algorithms
Final Stretch:
β’ Days 41-45: Object-Oriented Programming Concepts
β’ Days 46-50: Revision of all topics covered
Best Programming Resources: https://topmate.io/coding/886839
All the best ππ
Here's a concise 50-day plan to get you started:
Week 1-2:
β’ Days 1-5: Programming Language & its application
β’ Days 6-10: Basic Concepts - Operations
Week 3-4:
β’ Days 11-15: Strings & Variables
β’ Days 16-20: Control Structures
Week 5-6:
β’ Days 21-25: Functions & Header Files
β’ Days 26-30: Exception Handling & File Operations
Week 7-8:
β’ Days 31-35: Advanced Class Concepts
β’ Days 36-40: Algorithms
Final Stretch:
β’ Days 41-45: Object-Oriented Programming Concepts
β’ Days 46-50: Revision of all topics covered
Best Programming Resources: https://topmate.io/coding/886839
All the best ππ
π16β€4π1
π©βπ«π§βπ« PROGRAMMING LANGUAGES YOU SHOULD LEARN TO BECOME.
βοΈ[ Web Developer]
βοΈ[ Game Developer]
βοΈ[ Data Analysis]
βοΈ[ Desktop Developer]
βοΈ[ Embedded System Program]
βοΈ[Mobile Apps Development]
βοΈ[ Web Developer]
PHP, C#, JS, JAVA, Python, Ruby
βοΈ[ Game Developer]
Java, C++, Python, JS, Ruby, C, C#
βοΈ[ Data Analysis]
R, Matlab, Java, Python
βοΈ[ Desktop Developer]
Java, C#, C++, Python
βοΈ[ Embedded System Program]
C, Python, C++
βοΈ[Mobile Apps Development]
Kotlin, Dart, Objective-C, Java, Python, JS, Swift, C#
π27β€5π1
Forwarded from TrueMinds | Personality Development - Words of Wisdom
11 ways to be more mysterious:
1. Keep calm
2. Talk less
3. Stay away from drama
4. Donβt overreact
5. Make eye contact
6. Use clear gestures
7. Hear more, talk less
8. Think creatively
9. Think before you talk
10. donβt always be available
11. Share less about yourself
1. Keep calm
2. Talk less
3. Stay away from drama
4. Donβt overreact
5. Make eye contact
6. Use clear gestures
7. Hear more, talk less
8. Think creatively
9. Think before you talk
10. donβt always be available
11. Share less about yourself
π35β€9
π₯ Website To Learn Programming & Data Analytics
1. Learn HTML :- html.com
2. Learn CSS :- css-tricks.com
3. Learn Tailwind CSS :- tailwindcss.com
4. Learn JavaScript :- imp.i115008.net/mgGagX
5. Learn Bootstrap :- getbootstrap.com
6. Learn DSA :- t.iss.one/dsabooks
7. Learn Git :- git-scm.com
8. Learn React :- react-tutorial.app
9. Learn API :- rapidapi.com/learn
10. Learn Python :- t.iss.one/pythondevelopersindia
11. Learn SQL :- t.iss.one/sqlspecialist
12. Learn Web3 :- learnweb3.io
13. Learn JQuery :- learn.jquery.com
14. Learn ExpressJS :- expressjs.com
15. Learn NodeJS :- nodejs.dev/learn
16. Learn MongoDB :- learn.mongodb.com
17. Learn PHP :- phptherightway.com/
18. Learn Golang :- learn-golang.org/
19. Learn Power BI :- t.iss.one/powerbi_analyst
20. Learn Data Analytics:- datasimplifier.com
21. Learn Excel:- t.iss.one/excel_analyst
Join for more free resources: https://t.iss.one/free4unow_backup
ENJOY LEARNING ππ
1. Learn HTML :- html.com
2. Learn CSS :- css-tricks.com
3. Learn Tailwind CSS :- tailwindcss.com
4. Learn JavaScript :- imp.i115008.net/mgGagX
5. Learn Bootstrap :- getbootstrap.com
6. Learn DSA :- t.iss.one/dsabooks
7. Learn Git :- git-scm.com
8. Learn React :- react-tutorial.app
9. Learn API :- rapidapi.com/learn
10. Learn Python :- t.iss.one/pythondevelopersindia
11. Learn SQL :- t.iss.one/sqlspecialist
12. Learn Web3 :- learnweb3.io
13. Learn JQuery :- learn.jquery.com
14. Learn ExpressJS :- expressjs.com
15. Learn NodeJS :- nodejs.dev/learn
16. Learn MongoDB :- learn.mongodb.com
17. Learn PHP :- phptherightway.com/
18. Learn Golang :- learn-golang.org/
19. Learn Power BI :- t.iss.one/powerbi_analyst
20. Learn Data Analytics:- datasimplifier.com
21. Learn Excel:- t.iss.one/excel_analyst
Join for more free resources: https://t.iss.one/free4unow_backup
ENJOY LEARNING ππ
π26β€10
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
You can check these resources for Coding interview Preparation
Credits: https://t.iss.one/free4unow_backup
All the best ππ
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
You can check these resources for Coding interview Preparation
Credits: https://t.iss.one/free4unow_backup
All the best ππ
π16β€6π4π3
Best suited IDE's for programming languages:
1. JavaScript => VSCode
2. Python => PyCharm
3. C# => Visual Studio
4. Java => IntelliJ IDEA
5. Ruby => Ruby Mine
6. C & C++ => CLion
1. JavaScript => VSCode
2. Python => PyCharm
3. C# => Visual Studio
4. Java => IntelliJ IDEA
5. Ruby => Ruby Mine
6. C & C++ => CLion
β€23π7π6