Machine Learning & Artificial Intelligence | Data Science Free Courses
Открыть в Telegram
Perfect channel to learn Data Analytics, Data Sciene, Machine Learning & Artificial Intelligence Admin: @coderfun
Больше
Сеть:📈 Аналитический обзор Telegram-канала Machine Learning & Artificial Intelligence | Data Science Free Courses
Канал Machine Learning & Artificial Intelligence | Data Science Free Courses (@datasciencefree) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 68 672 подписчиков, занимая 2 392 место в категории Образование и 410 место в регионе Малайзия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 68 672 подписчиков.
Согласно последним данным от 31 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 188, а за последние 24 часа — -24, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.42%. В первые 24 часа после публикации контент обычно набирает 0.81% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 1 660 просмотров. В течение первых суток публикация набирает 557 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 4.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как sellerflash, waybienad, pricing, buybox, buyer.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Perfect channel to learn Data Analytics, Data Sciene, Machine Learning & Artificial Intelligence
Admin: @coderfun”
Благодаря высокой частоте обновлений (последние данные получены 01 ноября, 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.
68 672
Подписчики
-2424 часа
+117 дней
+18830 дней
Архив постов
Repost from Data Science & Machine Learning
Hi guys, now you can try 365DataScience Platform for Free
This website has very amazing curated content for data science aspirants.
👇👇
https://365datascience.pxf.io/q4m66g (Personally tried)
I would also recommend you all to try it's monthly plan feature which comes with Certificate, Resume feedback, Portfolio advice & Personalized support. Also, currently 365DataScience is providing 72% discount for limited time. So, take maximum use of it.
Those who can't afford paid plan can go for free one which includes
46 hours of video
203+ Exercises
Downloadables
Self-paced lessons
Resume builder
Gamified features
ENJOY LEARNING 👍👍
Python for Data Science -1.pdf7.57 MB
Large English learning resources collection
👇👇
https://t.me/englishlearnerspro/111
Preparing for a data science interview can be challenging, but with the right approach, you can increase your chances of success. Here are some tips to help you prepare for your next data science interview:
👉 1. Review the Fundamentals: Make sure you have a thorough understanding of the fundamentals of statistics, probability, and linear algebra. You should also be familiar with data structures, algorithms, and programming languages like Python, R, and SQL.
👉 2. Brush up on Machine Learning: Machine learning is a key aspect of data science. Make sure you have a solid understanding of different types of machine learning algorithms like supervised, unsupervised, and reinforcement learning.
👉 3. Practice Coding: Practice coding questions related to data structures, algorithms, and data science problems. You can use online resources like HackerRank, LeetCode, and Kaggle to practice.
👉 4. Build a Portfolio: Create a portfolio of projects that demonstrate your data science skills. This can include data cleaning, data wrangling, exploratory data analysis, and machine learning projects.
👉 5. Practice Communication: Data scientists are expected to effectively communicate complex technical concepts to non-technical stakeholders. Practice explaining your projects and technical concepts in simple terms.
👉 6. Research the Company: Research the company you are interviewing with and their industry. Understand how they use data and what data science problems they are trying to solve.
By following these tips, you can be well-prepared for your next data science interview. Good luck!
🆘 Exciting News- New Batch Starting for Future Data Scientists 🆘
Join Certification in Full Stack Data Science & AI Program - A course certified by IIT Guwahati 🚀
Register and enroll now
👉🏻 https://bit.ly/3tHgwwW
Why Join AlmaBetter 🚀
🔳 Advanced Certification from E&ICT Academy, IIT Guwahati.
🔳 6 months part-time program with online classes
🔳 Revised curriculum for post Chat-GPT era
🔳 No prior coding experience required
🔳 Suitable for final years, graduates and early professionals.
🆘 Special Discount Coupon: MAANG15 for Flat 15% OFF on Premium and Iconic Plans🆘
Practical Implementation of a Data Lake
Nayanjyoti Paul, 2023
Machine Learning with Python -> Amin Zollanvari
If you want to learn about crypto currency & Bitcoin, here is the perfect resource for you
👇👇
https://t.me/Bitcoin_Crypto_Web
Follow Observers.com to get news and signals from the crypto world.
𝐃𝐚𝐭𝐚_𝐒𝐜𝐢𝐞𝐧𝐜𝐞_𝐅𝐨𝐫_𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫𝐬_!_.pdf2.23 MB
Modern Computer Vision with Pytorch
V. Kishore Ayyadevara, 2020
What if we all are just a part of AI experiment by god- human’s life created as a unique dataset, contributing to the overall learning process. The Creator, observes the intricate patterns emerging from the myriad interactions among the humans.
Read more.....
BCG Hiring ML Engineer
👇👇
https://t.me/getjobss/1851
Requirements:
Very high proficiency in Python programming language, knowledge of other languages.
such as R, Java would be a plus.
Knowledge of various AI/ML models including deep learning models.
Knowledge of Generative AI stack – Large Language Models / Foundation Models, vector databases, orchestration stack.
Hand on experience in building AI orchestration with frameworks like LangChain.
Knowledge of vector databases e.g., Pinecone, Chroma etc.
Deep understanding of data processing frameworks e.g., Data Bricks, Airflow etc.
Knowledge of API frameworks Django, Flask etc.
Understanding of cloud data & AI stack on AWS / Azure / GCP is preferred.
ENJOY LEARNING 👍👍
Statistics For Data Science !.pdf1.29 MB
Famous ML Project Ideas
👇👇
https://t.me/pythonspecialist/103
Machine Learning Interview Questions.pdf.pdf
