Coding Projects
Channel specialized for advanced concepts and projects to master: * Python programming * Web development * Java programming * Artificial Intelligence * Machine Learning Managed by: @love_data
Show more๐ Analytical overview of Telegram channel Coding Projects
Channel Coding Projects (@programming_experts) in the English language segment is an active participant. Currently, the community unites 66 072 subscribers, ranking 1 981 in the Technologies & Applications category and 5 203 in the India region.
๐ Audience metrics and dynamics
Since its creation on ะฝะตะฒัะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 66 072 subscribers.
According to the latest data from 13 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 783 over the last 30 days and by 43 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 3.54%. Within the first 24 hours after publication, content typically collects 1.30% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 336 views. Within the first day, a publication typically gains 857 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 8.
- Thematic interests: Content is focused on key topics such as |--, algorithm, array, framework, javascript.
๐ Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
โChannel specialized for advanced concepts and projects to master:
* Python programming
* Web development
* Java programming
* Artificial Intelligence
* Machine Learning
Managed by: @love_dataโ
Thanks to the high frequency of updates (latest data received on 14 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
cin and cout.
- Day 4: Study operators and perform arithmetic and logical operations.
*Day 5-7:*
- Day 5: Explore control flow with if-else statements and loops (for, while, do-while).
- Day 6: Understand switch statements and how to use them for menu-driven programs.
- Day 7: Practice writing small programs involving conditions and loops.
Week 2: Functions and Object-Oriented Programming
*Day 8-9:*
- Day 8: Learn about functions (methods) in C++ and how to define your own functions.
- Day 9: Study function parameters, return types, and function overloading.
*Day 10-12:*
- Day 10: Understand the basics of object-oriented programming (OOP) in C++, including classes and objects.
- Day 11: Dive into constructors, destructors, and operator overloading.
- Day 12: Explore encapsulation, inheritance, and polymorphism.
*Day 13-14:*
- Day 13: Study C++ namespaces and access specifiers (public, private, protected).
- Day 14: Practice creating classes and objects for real-world applications.
Week 3: Data Structures and Standard Template Library (STL)
*Day 15-17:*
- Day 15: Dive into C++ arrays and understand their usage.
- Day 16: Explore the Standard Template Library (STL) and containers like vectors and lists.
- Day 17: Learn about iterating through containers using iterators.
*Day 18-19:*
- Day 18: Study other STL components like maps, sets, and queues.
- Day 19: Understand when and how to use different STL containers in C++.
*Day 20-21:*
- Day 20: Explore exception handling in C++ and how to handle runtime errors.
- Day 21: Practice working with try-catch blocks and handling exceptions effectively.
Week 4: Intermediate Topics and Projects
*Day 22-23:*
- Day 22: Learn about file handling in C++, including reading and writing files.
- Day 23: Create a small project that involves file operations, like a text-based note-taking application.
*Day 24-26:*
- Day 24: Study C++ pointers, references, and dynamic memory allocation.
- Day 25: Explore more advanced C++ topics like multithreading or creating a simple game using libraries like SDL or SFML.
- Day 26: Work on a project that involves pointers, references, or multithreading.
*Day 27-28:*
- Day 27: Explore more advanced C++ libraries and frameworks that interest you (e.g., Boost or Qt).
- Day 28: Work on a more complex project that combines your knowledge from the past weeks. For example, create a small database application using SQLite and C++.
*Day 29-30:*
- Day 29: Review and revisit any topics you found challenging.
- Day 30: Continue building projects and exploring areas of C++ that interest you.
Remember to practice coding daily, and don't hesitate to explore additional resources, online tutorials, and forums to enhance your C++ skills. Good luck with your C++ learning journey!
ENJOY LEARNING ๐๐Why type emails when Python can do it for you? Work smarter, not harder... unless youโre debugging. ๐ ๐ป
DISTINCT keyword in a SELECT statement to retrieve unique records. For example: SELECT DISTINCT column1, column2 FROM table;
5. Question: What is a subquery in SQL?
Answer: A subquery is a query nested inside another query. It can be used to retrieve data that will be used in the main query as a condition to further restrict the data to be retrieved.
6. Question: Explain the purpose of the GROUP BY clause.
Answer: The GROUP BY clause is used to group rows that have the same values in specified columns into summary rows, like when using aggregate functions such as COUNT, SUM, AVG, etc.
7. Question: How can you add a new record to a table?
Answer: Use the INSERT INTO statement. For example: INSERT INTO table_name (column1, column2) VALUES (value1, value2);
8. Question: What is the purpose of the HAVING clause?
Answer: The HAVING clause is used in combination with the GROUP BY clause to filter the results of aggregate functions based on a specified condition.
9. Question: Explain the concept of normalization in databases.
Answer: Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves breaking down tables into smaller, related tables.
10. Question: How do you update data in a table in SQL?
Answer: Use the UPDATE statement to modify existing records in a table. For example: UPDATE table_name SET column1 = value1 WHERE condition;
Here is an amazing resources to learn & practice SQL: https://bit.ly/3FxxKPz
Share with credits: https://t.me/sqlspecialist
Hope it helps :)scipy.stats, statsmodels, pandas
Visualization: seaborn, matplotlib
๐ก Quick tip: Use these formulas to crush interviews and build solid ML foundations!
๐ฌ Tap โค๏ธ for moredef bubble_sort(arr):
for i in range(len(arr)):
for j in range(len(arr)-i-1):
if arr[j] > arr[j+1]:
arr[j], arr[j+1] = arr[j+1], arr[j]
*C++*void bubbleSort(int arr[], int n) {
for(int i=0; i<n-1; i++)
for(int j=0; j<n-i-1; j++)
if(arr[j] > arr[j+1])
swap(arr[j], arr[j+1]);
}
*Java*void bubbleSort(int[] arr) {
for(int i = 0; i < arr.length - 1; i++)
for(int j = 0; j < arr.length - i - 1; j++)
if(arr[j] > arr[j+1]) {
int temp = arr[j]; arr[j] = arr[j+1]; arr[j+1] = temp;
}
}
๐ก 2. Binary Search โ Searching Algorithm
๐ Efficiently searches a sorted array in O(log n) time.
*Python*def binary_search(arr, target):
low, high = 0, len(arr)-1
while low <= high:
mid = (low + high) // 2
if arr[mid] == target: return mid
elif arr[mid] < target: low = mid + 1
else: high = mid - 1
return -1
๐ 3. Recursion โ Factorial Example
๐ Function calls itself to solve smaller subproblems.
*C++*int factorial(int n) {
if(n == 0) return 1;
return n * factorial(n - 1);
}
๐ต 4. Dynamic Programming โ Fibonacci (Bottom-Up)
๐ Stores previous results to avoid repeated work.
*Python*def fib(n):
dp = [0, 1]
for i in range(2, n+1):
dp.append(dp[i-1] + dp[i-2])
return dp[n]
๐ฃ 5. Sliding Window โ Max Sum Subarray of Size K
๐ Finds max sum in a subarray of fixed length in O(n) time.
*Java*int maxSum(int[] arr, int k) {
int sum = 0, max = 0;
for(int i = 0; i < k; i++) sum += arr[i];
max = sum;
for(int i = k; i < arr.length; i++) {
sum += arr[i] - arr[i - k];
if(sum > max) max = sum;
}
return max;
}
๐ง 6. BFS (Breadth-First Search) โ Graph Traversal
๐ Explores all neighbors before going deeper.
*Python*from collections import deque
def bfs(graph, start):
visited = set([start])
queue = deque([start])
while queue:
node = queue.popleft()
print(node)
for neighbor in graph[node]:
if neighbor not in visited:
visited.add(neighbor)
queue.append(neighbor)
๐ Tap โค๏ธ for more! #coding #algorithms #interviews #programming #datastructures
Note: I've addedaround code snippets to format them correctly in Telegram.
Available now! Telegram Research 2025 โ the year's key insights 
