Forwarded from Front End Development
If you are learning javascript follow these 10 projects to increase your knowledge and coding skills.
1 - To-do list appโ๏ธ
2 - Calculator๐ข
3 โ Drum Kit๐ฅ
4 - Quiz appโ
5 - Weather appโป๏ธ
6 - Image Slider๐๐
7 - Random quote generatorโก๏ธโก๏ธ
8- Hangman game ๐ง๐ปโโ๏ธ
9 - Rock-paper-scissors gameโ๏ธ๐
10 โ Tic-tac-toe game ๐งฎ
Read more @ : Click me !
if you are looking for their source code : #๐ฉ๐ฉ๐ฉcomment below or @fightAgainNow
Much respect for reading the article to the end!๐โฃ๏ธ๐
1 - To-do list appโ๏ธ
2 - Calculator๐ข
3 โ Drum Kit๐ฅ
4 - Quiz appโ
5 - Weather appโป๏ธ
6 - Image Slider๐๐
7 - Random quote generatorโก๏ธโก๏ธ
8- Hangman game ๐ง๐ปโโ๏ธ
9 - Rock-paper-scissors gameโ๏ธ๐
10 โ Tic-tac-toe game ๐งฎ
Read more @ : Click me !
if you are looking for their source code : #๐ฉ๐ฉ๐ฉcomment below or @fightAgainNow
Much respect for reading the article to the end!๐โฃ๏ธ๐
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๐๐๐๐๐#Save these Websites, these have great resources to learn and they will make you a monster of Algorithms....โ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธโ๏ธ
1. www.codecademy.com
2. www.lynda.com
3. www.udemy.com
4. www.udacity.com
5. www.coursera.org
6. www.w3schools.com
7. www.thenewboston.org
8. www.programmr.com
9. www.codeavengers.com
10. www.codeschool.com
11. www.learnstreet.com
12. www.teamtreehouse.com
13. www.sqlzoo.net
14. www.codehs.com
15. www.teamtreehouse.com
16. www.html5rocks.com
17. www.codepen.io
18. www.sitepoint.com
19. www.tutorialspoint.com
20. www.javatpoint.com
21. www.cplusplus.com
22. www.learncpp.com
23. www.tutorialspoint.com
24. www.cprogramming.com
25. www.stackoverflow.com
26. www.learncodethehardway.org
27. www.bloc.io
28. www.howtocode.io
29. www.edx.org
30. www.instructables.com
31. www.developer.apple.com
32. www.developer.android.com
33. www.developers.google.com
34. www.developer.mozilla.org
35. www.msdn.microsoft.com
36. www.decompera.com
37. www.www.developphp.com
38. www.quackit.com
39. www.htmlite.com
40. www.siteduzero.com
41. www.dreamincode.net
42. www.phpbuddy.com
43. www.php.net
44. www.microsoftvirtualacademy.com
45. www.professormesser.com ๐๐ฟ๐๐ฟ
share them now ๐ฟ๐บ master your journey with us!
1. www.codecademy.com
2. www.lynda.com
3. www.udemy.com
4. www.udacity.com
5. www.coursera.org
6. www.w3schools.com
7. www.thenewboston.org
8. www.programmr.com
9. www.codeavengers.com
10. www.codeschool.com
11. www.learnstreet.com
12. www.teamtreehouse.com
13. www.sqlzoo.net
14. www.codehs.com
15. www.teamtreehouse.com
16. www.html5rocks.com
17. www.codepen.io
18. www.sitepoint.com
19. www.tutorialspoint.com
20. www.javatpoint.com
21. www.cplusplus.com
22. www.learncpp.com
23. www.tutorialspoint.com
24. www.cprogramming.com
25. www.stackoverflow.com
26. www.learncodethehardway.org
27. www.bloc.io
28. www.howtocode.io
29. www.edx.org
30. www.instructables.com
31. www.developer.apple.com
32. www.developer.android.com
33. www.developers.google.com
34. www.developer.mozilla.org
35. www.msdn.microsoft.com
36. www.decompera.com
37. www.www.developphp.com
38. www.quackit.com
39. www.htmlite.com
40. www.siteduzero.com
41. www.dreamincode.net
42. www.phpbuddy.com
43. www.php.net
44. www.microsoftvirtualacademy.com
45. www.professormesser.com ๐๐ฟ๐๐ฟ
share them now ๐ฟ๐บ master your journey with us!
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Top 8 Algorithms Every Programmer Should Know ๐ฏ
1.Sorting algorithms: Sorting is a fundamental operation in computer science and there are several efficient algorithms for it, such as quicksort, merge sort and heap sort.
2.Search algorithms: Searching for an element in a large dataset is a common task and there are several efficient algorithms for it, such as binary search and hash tables.
3.Graph algorithms: Graph algorithms are used to solve problems related to graphs, such as finding the shortest path between two nodes or determining if a graph is connected.
4.Dynamic programming: Dynamic programming is a technique for solving problems by breaking them down into smaller subproblems and storing the solutions to these subproblems to avoid redundant computation.
5.Greedy algorithms: Greedy algorithms are used to solve optimization problems by making the locally optimal choice at each step with the hope of finding a global optimum.
6.Divide and Conquer: Divide and Conquer is an algorithm design paradigm based on multi-branched recursion. A divide and conquer algorithm breaks down a problem into sub-problems of the same or related type, until these become simple enough to be solved directly.
7.Backtracking: Backtracking is a general algorithmic technique that considers searching every possible combination in a systematic manner, and abandons a particular path as soon as it determines that it cannot be part of the solution.
8.Randomized Algorithm: Randomized algorithms use randomness to solve a problem. It can be useful to solve problems that cannot be solved deterministically or to improve the average case complexity of a problem.
1.Sorting algorithms: Sorting is a fundamental operation in computer science and there are several efficient algorithms for it, such as quicksort, merge sort and heap sort.
2.Search algorithms: Searching for an element in a large dataset is a common task and there are several efficient algorithms for it, such as binary search and hash tables.
3.Graph algorithms: Graph algorithms are used to solve problems related to graphs, such as finding the shortest path between two nodes or determining if a graph is connected.
4.Dynamic programming: Dynamic programming is a technique for solving problems by breaking them down into smaller subproblems and storing the solutions to these subproblems to avoid redundant computation.
5.Greedy algorithms: Greedy algorithms are used to solve optimization problems by making the locally optimal choice at each step with the hope of finding a global optimum.
6.Divide and Conquer: Divide and Conquer is an algorithm design paradigm based on multi-branched recursion. A divide and conquer algorithm breaks down a problem into sub-problems of the same or related type, until these become simple enough to be solved directly.
7.Backtracking: Backtracking is a general algorithmic technique that considers searching every possible combination in a systematic manner, and abandons a particular path as soon as it determines that it cannot be part of the solution.
8.Randomized Algorithm: Randomized algorithms use randomness to solve a problem. It can be useful to solve problems that cannot be solved deterministically or to improve the average case complexity of a problem.
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#Problem_Solving_001
Find the Sum OF All Numbers in given a Range.
or
example, sumOfAll([10,5]) should return 45 because sum of all the numbers between 5 and 10 (both inclusive) is 45.
NB: 1. You can use Any Language you can
2. send you answer only at @fightAgainNow
Find the Sum OF All Numbers in given a Range.
or
example, sumOfAll([10,5]) should return 45 because sum of all the numbers between 5 and 10 (both inclusive) is 45.
NB: 1. You can use Any Language you can
2. send you answer only at @fightAgainNow
โค1๐ฅ1
#problem_solving_002
Find the Sum All Primes
it returns the sum of all prime numbers that are less than or equal to number provided.
for example;- sumPrimes(10) should return a number, 17.
or sumPrimes(977) should return 73156.
NB: 1. You can use Any Language you can
2. you can send you answer at @fightAgainNow or comment below
Find the Sum All Primes
it returns the sum of all prime numbers that are less than or equal to number provided.
for example;- sumPrimes(10) should return a number, 17.
or sumPrimes(977) should return 73156.
NB: 1. You can use Any Language you can
2. you can send you answer at @fightAgainNow or comment below
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12 Websites Youโll Love As A Developerโค๏ธ
1. Ray.so
2. Roadmap.sh
3. Codepen.io
4. Stack Overflow
5. Github
6. Iconstore.co
7. Readme.so
8. GitBook
9. Figma
10. LottieFiles
11. Dribbble
12. Lorem Picsum
1. Ray.so
2. Roadmap.sh
3. Codepen.io
4. Stack Overflow
5. Github
6. Iconstore.co
7. Readme.so
8. GitBook
9. Figma
10. LottieFiles
11. Dribbble
12. Lorem Picsum
๐2โค1๐พ1๐ค1
https://www.mygreatlearning.com/academy?referrer_code=GLC_NNG7K12NO
Learn Ethical hacking course and other bunch of courses for free certificate
Learn Ethical hacking course and other bunch of courses for free certificate
Great Learning
Free Online Courses with Certificates [2024] - Great Learning Academy
Great Learning Academy offers free online courses with certificates in various domains such as Gen AI, Prompt Engineering, Data Science, AI, ML, IT & Software, Cloud Computing, Marketing, Big Data & more.
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Which one is popular back-end frame Work?
Anonymous Quiz
19%
React
52%
Express.js
13%
Angular
6%
Vue
11%
All
MERN is full-stack Javascript frame work that stand for
M - _____
E- ______
R- _______
N- _______
// Answer in the comment section๐
M - _____
E- ______
R- _______
N- _______
// Answer in the comment section๐
๐จโ๐ป5โค1
Identify one considered as front-end framework for web development
Anonymous Quiz
7%
Vue
6%
Svelte
48%
React
10%
Angular
30%
All
๐2
JavaProjectIdea101.pdf
1.2 MB
If you wanna learn javascript by project development, I do have source codes so inbox me https://t.me/fightAgainNow๐1
"A programmer programmed the program that
programmers use for programming the programs๐ป"
programmers use for programming the programs๐ป"
๐คฃ7๐1
You Can Become a Google Certified Data Scientist for FREE๐
1. Learn Python basics for data analysis: Find out how rewarding programming in Python can be! Learn how to use and write functions, practice with data analysis, and work on your first algorithm!
https://lnkd.in/eG_79Tkp
2. Data Science Foundations: A comprehensive introduction to Data Science and Analytics Landscape!
https://lnkd.in/eByW-_N5
3. Data Science with Python: Getting Started with Data Science with Python!
https://lnkd.in/ewAcrUNS
4. Machine Learning Crash Course: Google's fast-paced, practical introduction to machine learning!
https://lnkd.in/eFKivP8j
5. Intro to TensorFlow for Deep Learning: Learn how to build deep learning applications with TensorFlow.
https://lnkd.in/eYgxu3TM
1. Learn Python basics for data analysis: Find out how rewarding programming in Python can be! Learn how to use and write functions, practice with data analysis, and work on your first algorithm!
https://lnkd.in/eG_79Tkp
2. Data Science Foundations: A comprehensive introduction to Data Science and Analytics Landscape!
https://lnkd.in/eByW-_N5
3. Data Science with Python: Getting Started with Data Science with Python!
https://lnkd.in/ewAcrUNS
4. Machine Learning Crash Course: Google's fast-paced, practical introduction to machine learning!
https://lnkd.in/eFKivP8j
5. Intro to TensorFlow for Deep Learning: Learn how to build deep learning applications with TensorFlow.
https://lnkd.in/eYgxu3TM