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GROUP FOR PROGRAMMERS🖥 | Telegram Webview: realgroupforprogrammer/969 -
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Free Big Data Courses

Complete Big Data
🎬 13 video lesson
Duration : 2-3 hours worth of material
🏃‍♂️ Self paced
Source: Class Central
🔗 COURSE LINK

Big Data 101 (Login Required)
Modules: 6
Duration : 3 hours worth of material
🏃‍♂️ Self paced
Source: IBM via Cognitive Class
🔗 COURSE LINK

Introduction to Big Data - an overview of the 10 V's
Rating⭐️: 4.4 out 5
Students 👨‍🎓 :15,630
Duration : 40min of on-demand video
Teacher 👨‍🏫: Taimur Zahid
🔗 COURSE LINK

MIT RES.LL-005 Mathematics of Big Data and Machine Learning, IAP 2020
🎬 20 video lesson
Duration : 14 hours worth of material
🏃‍♂️ Self paced
Source: MIT open courseware
🔗 Course Link

NOC:Big Data Computing, IIT Patna
🎬 35 video lesson
8 Modules
Taught by: Dr. Rajiv Misra
Source: NPTEL
🔗 COURSE LINK

Algorithms for Big Data (COMPSCI 229r)
🎬 25 video lesson
Duration : 34 hours worth of material
🏃‍♂️ Self paced
Source: Harvard University
🔗 Course Link

NOC:Algorithms for Big Data, IIT Madras
🎬 48 video lesson
8 Modules
Taught by: Prof. John Augustine
Source: NPTEL
🔗 COURSE LINK

Big Data Hadoop Tutorial for Beginners
🎬 17 video lesson
Duration : 4-5 hours worth of material
🏃‍♂️ Self paced
Source: Great Learning
🔗 Course Link

Big Data Analytics Full Course In 10 Hours | Big Data Hadoop Tutorial
🎬 5 video lesson
Duration : 10 hours worth of material
🏃‍♂️ Self paced
Source: Great Learning
🔗 Course Link

Big Data Analytics
Free Online Course
🎬 70 video lesson
Duration : 19 hours worth of material
🏃‍♂️ Self paced
Source: caltech via youtube
🔗 Course Link

Stanford Seminar - Big Data is (at least) Four Different Problems
Free Online Course
🎬 27 video lesson
Duration : 1-2 hours worth of material
🏃‍♂️ Self paced
Source: Stanford Online via YouTube
🔗 Course Link

#Big_Data

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Free Big Data Courses

Complete Big Data
🎬 13 video lesson
Duration : 2-3 hours worth of material
🏃‍♂️ Self paced
Source: Class Central
🔗 COURSE LINK

Big Data 101 (Login Required)
Modules: 6
Duration : 3 hours worth of material
🏃‍♂️ Self paced
Source: IBM via Cognitive Class
🔗 COURSE LINK

Introduction to Big Data - an overview of the 10 V's
Rating⭐️: 4.4 out 5
Students 👨‍🎓 :15,630
Duration : 40min of on-demand video
Teacher 👨‍🏫: Taimur Zahid
🔗 COURSE LINK

MIT RES.LL-005 Mathematics of Big Data and Machine Learning, IAP 2020
🎬 20 video lesson
Duration : 14 hours worth of material
🏃‍♂️ Self paced
Source: MIT open courseware
🔗 Course Link

NOC:Big Data Computing, IIT Patna
🎬 35 video lesson
8 Modules
Taught by: Dr. Rajiv Misra
Source: NPTEL
🔗 COURSE LINK

Algorithms for Big Data (COMPSCI 229r)
🎬 25 video lesson
Duration : 34 hours worth of material
🏃‍♂️ Self paced
Source: Harvard University
🔗 Course Link

NOC:Algorithms for Big Data, IIT Madras
🎬 48 video lesson
8 Modules
Taught by: Prof. John Augustine
Source: NPTEL
🔗 COURSE LINK

Big Data Hadoop Tutorial for Beginners
🎬 17 video lesson
Duration : 4-5 hours worth of material
🏃‍♂️ Self paced
Source: Great Learning
🔗 Course Link

Big Data Analytics Full Course In 10 Hours | Big Data Hadoop Tutorial
🎬 5 video lesson
Duration : 10 hours worth of material
🏃‍♂️ Self paced
Source: Great Learning
🔗 Course Link

Big Data Analytics
Free Online Course
🎬 70 video lesson
Duration : 19 hours worth of material
🏃‍♂️ Self paced
Source: caltech via youtube
🔗 Course Link

Stanford Seminar - Big Data is (at least) Four Different Problems
Free Online Course
🎬 27 video lesson
Duration : 1-2 hours worth of material
🏃‍♂️ Self paced
Source: Stanford Online via YouTube
🔗 Course Link

#Big_Data

Join our Community 👇

https://linktr.ee/groupforprogrammers

Share with your College Whatsapp Groups & Friends too

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GROUP FOR PROGRAMMERS Telegram | DID YOU KNOW?

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Cryptoassets enthusiasts use this application for their trade activities, and they may make donations for this cause.If somehow Telegram do run out of money to sustain themselves they will probably introduce some features that will not hinder the rudimentary principle of Telegram but provide users with enhanced and enriched experience. This could be similar to features where characters can be customized in a game which directly do not affect the in-game strategies but add to the experience.

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