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If you are learning javascript follow these 10 projects to increase your knowledge and coding skills.

1 - To-do list appโšœ๏ธ

2 - Calculator๐Ÿ”ข

3 โ€” Drum Kit๐Ÿฅ

4 - Quiz appโ”

5 - Weather appโ™ป๏ธ

6 - Image Slider๐ŸŒ‡๐ŸŽ†

7 - Random quote generatorโšก๏ธโšก๏ธ

8- Hangman game ๐Ÿงœ๐Ÿปโ€โ™‚๏ธ

9 - Rock-paper-scissors gameโœ‚๏ธ๐Ÿ”–

10 โ€” Tic-tac-toe game ๐Ÿงฎ

Read more @ : Click me !


if you are looking for their source code : #๐Ÿ“ฉ๐Ÿ“ฉ๐Ÿ“ฉcomment below or @fightAgainNow

Much respect for reading the article to the end!๐Ÿ™โฃ๏ธ๐Ÿ’–
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Top 8 Algorithms Every Programmer Should Know ๐Ÿ’ฏ

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
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#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
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แŠฅแŠ•แŠณแŠ• แˆˆ1 แˆบแˆ… 444แŠ›แ‹ แ‹จแ‹’แ‹ต แŠ แˆแˆแŒฅแˆญ แ‰ แ‹“แˆ แ‰ แˆฐแˆ‹แˆ แŠ แ‹ฐแˆจแˆณแ‰ฝแˆแข
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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 section๐Ÿ™
๐Ÿ‘จโ€๐Ÿ’ป5โค1
Identify one considered as front-end framework for web development
Anonymous Quiz
7%
Vue
6%
Svelte
48%
React
10%
Angular
30%
All
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JavaProjectIdea101.pdf
1.2 MB
If you wanna learn javascript by project development, I do have source codes so inbox me https://t.me/fightAgainNow
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"A programmer programmed the program that
programmers use for programming the programs
๐Ÿ’ป"
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You Can Become a Google Certified Data Scientist for FREE๐Ÿ‘‡

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