Coding & AI Resources
📚Get daily updates for : ✅ Free resources ✅ All Free notes ✅ Internship,Jobs and a lot more....😍 📍Join & Share this channel with your friends and college mates ❤️ Managed by: @love_data Buy ads: https://telega.io/c/leadcoding
Больше📈 Аналитический обзор Telegram-канала Coding & AI Resources
Канал Coding & AI Resources (@leadcoding) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 35 412 подписчиков, занимая 5 348 место в категории Образование и 11 514 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 35 412 подписчиков.
Согласно последним данным от 22 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -18, а за последние 24 часа — -11, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.30%. В первые 24 часа после публикации контент обычно набирает 0.40% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 815 просмотров. В течение первых суток публикация набирает 142 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 2.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как learning, link:-, element, programming, analytic.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“📚Get daily updates for :
✅ Free resources
✅ All Free notes
✅ Internship,Jobs
and a lot more....😍
📍Join & Share this channel with your friends and college mates ❤️
Managed by: @love_data
Buy ads: https://telega.io/c/leadcoding”
Благодаря высокой частоте обновлений (последние данные получены 23 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.
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Subject: Application For The [Role] at [Company Name] Dear [Hiring Manager’s Name], I hope you’re doing great. I came across the [Position Title] role at [Company Name] and was really excited about the opportunity to apply. With my experience in [mention key relevant experience], I believe I could bring value to your team. I’ve attached my Resume for your review. I trust my background aligns with what you’re looking for, I’d love the chance to discuss how I can contribute to your team. Looking forward to hearing your thoughts! Best regards, [Your Name] [Link To Linkedin] [Link To Resume]📩 Message to a Recruiter After Seeing Their Job Posting
Subject: Excited to Apply for [Position Title] at [Company Name] Hi [Recruiter’s Name], I trust you have a awesome day today 🙂 I just saw your post about the [Position Title] opening at [Company Name], and I couldn’t wait to reach out! I’ve been following [Company Name] for a while now, and I truly admire [mention something specific—company’s projects, culture, values, recent achievements]. With my expertise in [mention relevant skills/experience], I believe I’d be a great fit for this role. I’ve attached my Resume for your review, and I’d love the chance to discuss how my experience can contribute to your team. Would you be open to a quick chat? Looking forward to your thoughts! [Your Resume]✉️ Warm Networking DM
Subject: Exploring Opportunities at [Company Name] Hi [First Name], I believe you have a wonderful day today 😊 I’m a [Your Role] specializing in [mention key skills]. I’ve been following [Company Name] for a while and love [mention something specific about their work, culture, or achievements]. With experience in [mention a key project or skill], I believe I could bring value to your team. If you’re open to it, I’d love to chat about any opportunities, where my skills could be a great fit. I know you must get a ton of messages, so I really appreciate your time. Looking forward to hearing from you! Warm, [Your Name] [Your Resume]
def is_palindrome(s):
return s == s[::-1]
print(is_palindrome("madam")) # True
print(is_palindrome("hello")) # False
2. How to find the factorial of a number using recursion?
def factorial(n):
if n == 0 or n == 1:
return 1
return n * factorial(n - 1)
print(factorial(5)) # 120
3. How to merge two dictionaries in Python?
dict1 = {'a': 1, 'b': 2}
dict2 = {'c': 3, 'd': 4}
# Method 1 (Python 3.5+)
merged_dict = {**dict1, **dict2}
# Method 2 (Python 3.9+)
merged_dict = dict1 | dict2
print(merged_dict)
4. How to find the intersection of two lists?
list1 = [1, 2, 3, 4]
list2 = [3, 4, 5, 6]
intersection = list(set(list1) & set(list2))
print(intersection) # [3, 4]
5. How to generate a list of even numbers from 1 to 100?
even_numbers = [i for i in range(1, 101) if i % 2 == 0]
print(even_numbers)
6. How to find the longest word in a sentence?
def longest_word(sentence):
words = sentence.split()
return max(words, key=len)
print(longest_word("Python is a powerful language")) # "powerful"
7. How to count the frequency of elements in a list?
from collections import Counter
my_list = [1, 2, 2, 3, 3, 3, 4]
frequency = Counter(my_list)
print(frequency) # Counter({3: 3, 2: 2, 1: 1, 4: 1})
8. How to remove duplicates from a list while maintaining the order?
def remove_duplicates(lst):
return list(dict.fromkeys(lst))
my_list = [1, 2, 2, 3, 4, 4, 5]
print(remove_duplicates(my_list)) # [1, 2, 3, 4, 5]
9. How to reverse a linked list in Python?
class Node:
def __init__(self, data):
self.data = data
self.next = None
def reverse_linked_list(head):
prev = None
current = head
while current:
next_node = current.next
current.next = prev
prev = current
current = next_node
return prev
# Create linked list: 1 -> 2 -> 3
head = Node(1)
head.next = Node(2)
head.next.next = Node(3)
# Reverse and print the list
reversed_head = reverse_linked_list(head)
while reversed_head:
print(reversed_head.data, end=" -> ")
reversed_head = reversed_head.next
10. How to implement a simple binary search algorithm?
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
print(binary_search([1, 2, 3, 4, 5, 6, 7], 4)) # 3
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