In 1994, people told me programming was for nerds and that I should become a doctor or a lawyer instead.
10 years later, they told me that someone from India would take my job for $5/hour.
Then, no code was going to doom my career.
In 2021, Codex, then Copilot, then ChatGPT, then Devin, then OpenAI o1...
People keep yelling that "Programming is Dead," and yet the demand for good Software Engineers has never been higher.
Stop listening to midwit people. Learn to build good software, and you'll be okay. (Credits: unknown)
10 years later, they told me that someone from India would take my job for $5/hour.
Then, no code was going to doom my career.
In 2021, Codex, then Copilot, then ChatGPT, then Devin, then OpenAI o1...
People keep yelling that "Programming is Dead," and yet the demand for good Software Engineers has never been higher.
Stop listening to midwit people. Learn to build good software, and you'll be okay. (Credits: unknown)
❤7👍5
Here we have compiled a list of 40+ cheat sheets that cover a wide range of topics essential for you. 👇
1. HTML & CSS :- htmlcheatsheet.com
2. JavaScript :- https://lnkd.in/dfSvFuhM
3. Jquery :- https://lnkd.in/dcvy6kmQ
4. Bootstrap 5 :- https://lnkd.in/dNZ6qdBh
5. Tailwind CSS :- https://lnkd.in/d_T5q5Tx
6. React :- https://t.iss.one/Programming_experts/230
7. Python :- https://t.iss.one/pythondevelopersindia/99
8. MongoDB :- https://lnkd.in/dBXxCQ43
9. SQL :- https://t.iss.one/sqlspecialist/222
10. Nodejs :- https://lnkd.in/dwry8BKH
11. Expressjs :- https://lnkd.in/d3BMMwem
12. Django :- https://lnkd.in/dYWQKZnT
13. PHP :- https://quickref.me/php
14. Google Dork :- https://lnkd.in/dKej3-42
15. Linux :- https://lnkd.in/dCgH_qUq
16. Git :- https://lnkd.in/djf9Wc98
17. VSCode :- https://quickref.me/vscode
18. PC Keyboard :- https://bit.ly/3luF73K
19. Data Structures and Algorithms :- https://lnkd.in/d75ijyr3
20. DSA Practice :- https://lnkd.in/dDc6SaR8
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26. Windows Command :- https://lnkd.in/dAMeCywP
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28. MySQL :- https://lnkd.in/d7iJjSpQ
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30. MSExcel :- https://bit.ly/3Jz0dpG
31. MSWord :- https://lnkd.in/dAX4FGkR
32. Java :- https://lnkd.in/dRe98iSB
33. Data Analytics :- https://t.iss.one/sqlspecialist
34. C++ :- https://lnkd.in/d4GjE2kd
35. C :- https://lnkd.in/diuHU72d
36. Resume Creation :- https://bit.ly/3JA3KnJ
37. ChatGPT :- https://lnkd.in/dsK37bSj
38. Docker :- https://lnkd.in/dNVJxYNa
39. Gmail :- bit.ly/3JX68pR
40. AngularJS :- bit.ly/3yYY0ik
41. Atom Text Editor :- bit.ly/40oJFY9
42. R Programming :- bit.ly/3Jysq00
1. HTML & CSS :- htmlcheatsheet.com
2. JavaScript :- https://lnkd.in/dfSvFuhM
3. Jquery :- https://lnkd.in/dcvy6kmQ
4. Bootstrap 5 :- https://lnkd.in/dNZ6qdBh
5. Tailwind CSS :- https://lnkd.in/d_T5q5Tx
6. React :- https://t.iss.one/Programming_experts/230
7. Python :- https://t.iss.one/pythondevelopersindia/99
8. MongoDB :- https://lnkd.in/dBXxCQ43
9. SQL :- https://t.iss.one/sqlspecialist/222
10. Nodejs :- https://lnkd.in/dwry8BKH
11. Expressjs :- https://lnkd.in/d3BMMwem
12. Django :- https://lnkd.in/dYWQKZnT
13. PHP :- https://quickref.me/php
14. Google Dork :- https://lnkd.in/dKej3-42
15. Linux :- https://lnkd.in/dCgH_qUq
16. Git :- https://lnkd.in/djf9Wc98
17. VSCode :- https://quickref.me/vscode
18. PC Keyboard :- https://bit.ly/3luF73K
19. Data Structures and Algorithms :- https://lnkd.in/d75ijyr3
20. DSA Practice :- https://lnkd.in/dDc6SaR8
21. Data Science :- https://lnkd.in/dHaxPYYA
22. Flask :- https://lnkd.in/dkUyWHqR
23. CCNA :- https://lnkd.in/dE_yD6ny
24. Cloud Computing :- https://lnkd.in/d9vggegr
25. Machine Learning :- https://t.iss.one/learndataanalysis/29
26. Windows Command :- https://lnkd.in/dAMeCywP
27. Computer Basics :- https://lnkd.in/d9yaNaWN
28. MySQL :- https://lnkd.in/d7iJjSpQ
29. PostgreSQL :- https://lnkd.in/dDHQkk5f
30. MSExcel :- https://bit.ly/3Jz0dpG
31. MSWord :- https://lnkd.in/dAX4FGkR
32. Java :- https://lnkd.in/dRe98iSB
33. Data Analytics :- https://t.iss.one/sqlspecialist
34. C++ :- https://lnkd.in/d4GjE2kd
35. C :- https://lnkd.in/diuHU72d
36. Resume Creation :- https://bit.ly/3JA3KnJ
37. ChatGPT :- https://lnkd.in/dsK37bSj
38. Docker :- https://lnkd.in/dNVJxYNa
39. Gmail :- bit.ly/3JX68pR
40. AngularJS :- bit.ly/3yYY0ik
41. Atom Text Editor :- bit.ly/40oJFY9
42. R Programming :- bit.ly/3Jysq00
👍7❤2🥰1
Here are seven popular programming languages and their benefits:
1. Python:
- Benefits: Python is known for its simplicity and readability, making it a great choice for beginners. It has a vast ecosystem of libraries and frameworks for various applications such as web development, data science, machine learning, and automation. Python's versatility and ease of use make it a popular choice for a wide range of projects.
2. JavaScript:
- Benefits: JavaScript is the language of the web, used for building interactive and dynamic websites. It is supported by all major browsers and has a large community of developers. JavaScript can also be used for server-side development (Node.js) and mobile app development (React Native). Its flexibility and wide range of applications make it a valuable language to learn.
3. Java:
- Benefits: Java is a robust, platform-independent language commonly used for building enterprise-level applications, mobile apps (Android), and large-scale systems. It has strong support for object-oriented programming principles and a rich ecosystem of libraries and tools. Java's stability, performance, and scalability make it a popular choice for building mission-critical applications.
4. C++:
- Benefits: C++ is a powerful and efficient language often used for system programming, game development, and high-performance applications. It provides low-level control over hardware and memory management while offering high-level abstractions for complex tasks. C++'s performance, versatility, and ability to work closely with hardware make it a preferred choice for performance-critical applications.
5. C#:
- Benefits: C# is a versatile language developed by Microsoft and commonly used for building Windows applications, web applications (with ASP.NET), and games (with Unity). It offers a modern syntax, strong type safety, and seamless integration with the .NET framework. C#'s ease of use, robustness, and support for various platforms make it a popular choice for developing a wide range of applications.
6. R:
- Benefits: R is a language specifically designed for statistical computing and data analysis. It has a rich set of built-in functions and packages for data manipulation, visualization, and machine learning. R's focus on data science, statistical modeling, and visualization makes it an ideal choice for researchers, analysts, and data scientists working with large datasets.
7. Swift:
- Benefits: Swift is Apple's modern programming language for developing iOS, macOS, watchOS, and tvOS applications. It offers safety features to prevent common programming errors, high performance, and interoperability with Objective-C. Swift's clean syntax, powerful features, and seamless integration with Apple's platforms make it a preferred choice for building native applications in the Apple ecosystem.
These are just a few of the many programming languages available today, each with its unique strengths and use cases.
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Like if you need similar content 😄👍
1. Python:
- Benefits: Python is known for its simplicity and readability, making it a great choice for beginners. It has a vast ecosystem of libraries and frameworks for various applications such as web development, data science, machine learning, and automation. Python's versatility and ease of use make it a popular choice for a wide range of projects.
2. JavaScript:
- Benefits: JavaScript is the language of the web, used for building interactive and dynamic websites. It is supported by all major browsers and has a large community of developers. JavaScript can also be used for server-side development (Node.js) and mobile app development (React Native). Its flexibility and wide range of applications make it a valuable language to learn.
3. Java:
- Benefits: Java is a robust, platform-independent language commonly used for building enterprise-level applications, mobile apps (Android), and large-scale systems. It has strong support for object-oriented programming principles and a rich ecosystem of libraries and tools. Java's stability, performance, and scalability make it a popular choice for building mission-critical applications.
4. C++:
- Benefits: C++ is a powerful and efficient language often used for system programming, game development, and high-performance applications. It provides low-level control over hardware and memory management while offering high-level abstractions for complex tasks. C++'s performance, versatility, and ability to work closely with hardware make it a preferred choice for performance-critical applications.
5. C#:
- Benefits: C# is a versatile language developed by Microsoft and commonly used for building Windows applications, web applications (with ASP.NET), and games (with Unity). It offers a modern syntax, strong type safety, and seamless integration with the .NET framework. C#'s ease of use, robustness, and support for various platforms make it a popular choice for developing a wide range of applications.
6. R:
- Benefits: R is a language specifically designed for statistical computing and data analysis. It has a rich set of built-in functions and packages for data manipulation, visualization, and machine learning. R's focus on data science, statistical modeling, and visualization makes it an ideal choice for researchers, analysts, and data scientists working with large datasets.
7. Swift:
- Benefits: Swift is Apple's modern programming language for developing iOS, macOS, watchOS, and tvOS applications. It offers safety features to prevent common programming errors, high performance, and interoperability with Objective-C. Swift's clean syntax, powerful features, and seamless integration with Apple's platforms make it a preferred choice for building native applications in the Apple ecosystem.
These are just a few of the many programming languages available today, each with its unique strengths and use cases.
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Like if you need similar content 😄👍
👍8❤2
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 👍👍
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 👍👍
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Roadmap to Becoming a Python Developer 🚀
1. Basics 🌱
- Learn programming fundamentals and Python syntax.
2. Core Python 🧠
- Master data structures, functions, and OOP.
3. Advanced Python 📈
- Explore modules, file handling, and exceptions.
4. Web Development 🌐
- Use Django or Flask; build REST APIs.
5. Data Science 📊
- Learn NumPy, pandas, and Matplotlib.
6. Projects & Practice💡
- Build projects, contribute to open-source, join communities.
Like for more ❤️
ENJOY LEARNING 👍👍
1. Basics 🌱
- Learn programming fundamentals and Python syntax.
2. Core Python 🧠
- Master data structures, functions, and OOP.
3. Advanced Python 📈
- Explore modules, file handling, and exceptions.
4. Web Development 🌐
- Use Django or Flask; build REST APIs.
5. Data Science 📊
- Learn NumPy, pandas, and Matplotlib.
6. Projects & Practice💡
- Build projects, contribute to open-source, join communities.
Like for more ❤️
ENJOY LEARNING 👍👍
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If-else in Python 👆
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Roadmap to learn Network Engineering
Here's a comprehensive guide to mastering the essential skills and knowledge areas:
1. Networking Fundamentals: OSI model, TCP/IP model, and networking devices (routers, switches, hubs, bridges).
2. Network Protocols: Core protocols (TCP, UDP, IP), application layer protocols (HTTP, HTTPS, FTP, DNS, DHCP), and additional protocols (SNMP, ICMP, ARP).
3. Routing and Switching: Routing protocols (OSPF, EIGRP, BGP), switching concepts (VLANs, STP, trunking), and routing techniques.
4. Network Design and Architecture: Network topologies (star, mesh, bus, ring), design principles (redundancy, scalability, reliability), and network types (LAN,
WAN, MAN, WLAN, VLAN).
5. Network Security: Firewalls, VPNs, ACLs, security protocols (SSL/TLS, IPSec), and best practices.
6. Wireless Networking: Wireless standards (IEEE 802.11a/b/g/n/ac/ax), wireless security (WPA2, WPA3), and network design.
7. Cloud Networking: Cloud services (VPC, Direct Connect, VPN), hybrid cloud Networking, and cloud providers (AWS, Azure, Google Cloud).
8. Network Automation and Scripting: Network programmability, automation techniques, and scripting (Python, Bash, PowerShell).
9. Monitoring and Troubleshooting: Network monitoring, troubleshooting techniques (ping, traceroute, network diagrams), and performance monitoring (NetFlow, SNMP).
10. Virtualization and Container Networking: Virtual network functions (NFV), software-defined networking (SDN), and container networking (Docker, Kubernetes).
11. Certifications: Entry-level (CompTIA Network+, Cisco CCNA), professional-level (Cisco CCNP, Juniper JNCIP), advanced-level (Cisco CCIE, VMware VCP-NV).
Here's a comprehensive guide to mastering the essential skills and knowledge areas:
1. Networking Fundamentals: OSI model, TCP/IP model, and networking devices (routers, switches, hubs, bridges).
2. Network Protocols: Core protocols (TCP, UDP, IP), application layer protocols (HTTP, HTTPS, FTP, DNS, DHCP), and additional protocols (SNMP, ICMP, ARP).
3. Routing and Switching: Routing protocols (OSPF, EIGRP, BGP), switching concepts (VLANs, STP, trunking), and routing techniques.
4. Network Design and Architecture: Network topologies (star, mesh, bus, ring), design principles (redundancy, scalability, reliability), and network types (LAN,
WAN, MAN, WLAN, VLAN).
5. Network Security: Firewalls, VPNs, ACLs, security protocols (SSL/TLS, IPSec), and best practices.
6. Wireless Networking: Wireless standards (IEEE 802.11a/b/g/n/ac/ax), wireless security (WPA2, WPA3), and network design.
7. Cloud Networking: Cloud services (VPC, Direct Connect, VPN), hybrid cloud Networking, and cloud providers (AWS, Azure, Google Cloud).
8. Network Automation and Scripting: Network programmability, automation techniques, and scripting (Python, Bash, PowerShell).
9. Monitoring and Troubleshooting: Network monitoring, troubleshooting techniques (ping, traceroute, network diagrams), and performance monitoring (NetFlow, SNMP).
10. Virtualization and Container Networking: Virtual network functions (NFV), software-defined networking (SDN), and container networking (Docker, Kubernetes).
11. Certifications: Entry-level (CompTIA Network+, Cisco CCNA), professional-level (Cisco CCNP, Juniper JNCIP), advanced-level (Cisco CCIE, VMware VCP-NV).
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