R Programming Language free courses
R Programming Tutorial - Learn the Basics of Statistical Computing
🆓 Free Online Course
🎬 20 video lesson
Duration ⏰: 2-3 hours worth of material
🏃♂️ Self paced
Resource: freecodecamp
🔗 Course Link
NOC:Foundations of R Software, IIT Kanpur
🎬 53 video lesson
⏰ 12 Modules
Taught by: Prof. Shalabh
Source: NPTEL
🔗 Course Link
R Basics - R Programming Language Introduction
Rating ⭐️: 4.6 out of 5
Students 👨🎓: 207,088
Duration ⏰: 4hr 06min
Created by: R-Tutorials Training
🔗 Course Link
R Shiny for Data Science Tutorial – Build Interactive Data-Driven Web Apps
🆓 Free Online Course
🎬 8 video lesson
Duration ⏰: 1-2 hours worth of material
🏃♂️ Self paced
Resource: freecodecamp
🔗 Course Link
NOC:Essentials of Data Science With R Software _ 1: Probability and Statistical Inference, IIT Kanpur
🎬 71 video lesson
⏰ 13 Modules
Taught by: Prof. Shalabh
Source: NPTEL
🔗 Course Link
NOC:Essentials of Data Science With R Software _ 2: Sampling Theory and Linear Regression Analysis, IIT Kanpur
🎬 51 video lesson
⏰ 13 Modules
Taught by: Prof. Shalabh
Source: NPTEL
🔗 Course Link
Mastering R Programming (Apr 2023)
Rating ⭐️: 4.3 out of 5
Students 👨🎓: 6,161
Duration ⏰: 1hr 47min
Created by: Proton Expert Systems & Solutions
🔗 Course Link
Statistical Computing with R - a gentle introduction (Login Required)
🆓 Free Online Course
Duration ⏰: 6-8 Hours study
🏃♂️ Self paced
Teacher: Max Reuter, Chris Barnes
Resource: University College London
🔗 Course Link
R Programming For Beginners-Full Course | Learn R in 3 Hours| R Language Tutorial | Great Learning
🆓 Free Online Course
🎬 14 video lesson
Duration ⏰: 3-4 hours worth of material
🏃♂️ Self paced
Resource: Great Learning
🔗 Course Link
NOC:Business analytics and data mining Modeling using R, IIT Roorkee
🎬 60 video lesson
⏰ 12 Modules
Taught by: Dr. Gaurav Dixit
Source: NPTEL
🔗 Course Link
Learn Live - Explore and analyze data with R
🆓 Free Online Course
🎬 9 video lesson
Duration ⏰: 1-2 hours worth of material
🏃♂️ Self paced
Resource: Class Central
🔗 Course Link
R Programming Full Course for 2023 | R Programming For Beginners | R Tutorial | Simplilearn
🆓 Free Online Course
🎬 1 video lesson
Duration ⏰: 10-11 hours worth of material
🏃♂️ Self paced
Resource: Youtube
🔗 Course Link
Books
The Book of R
R Programming for Data Science - Roger D. Peng
R for Beginners
#R #R_Language #R_Programming_Language
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R Programming Tutorial - Learn the Basics of Statistical Computing
🆓 Free Online Course
🎬 20 video lesson
Duration ⏰: 2-3 hours worth of material
🏃♂️ Self paced
Resource: freecodecamp
🔗 Course Link
NOC:Foundations of R Software, IIT Kanpur
🎬 53 video lesson
⏰ 12 Modules
Taught by: Prof. Shalabh
Source: NPTEL
🔗 Course Link
R Basics - R Programming Language Introduction
Rating ⭐️: 4.6 out of 5
Students 👨🎓: 207,088
Duration ⏰: 4hr 06min
Created by: R-Tutorials Training
🔗 Course Link
R Shiny for Data Science Tutorial – Build Interactive Data-Driven Web Apps
🆓 Free Online Course
🎬 8 video lesson
Duration ⏰: 1-2 hours worth of material
🏃♂️ Self paced
Resource: freecodecamp
🔗 Course Link
NOC:Essentials of Data Science With R Software _ 1: Probability and Statistical Inference, IIT Kanpur
🎬 71 video lesson
⏰ 13 Modules
Taught by: Prof. Shalabh
Source: NPTEL
🔗 Course Link
NOC:Essentials of Data Science With R Software _ 2: Sampling Theory and Linear Regression Analysis, IIT Kanpur
🎬 51 video lesson
⏰ 13 Modules
Taught by: Prof. Shalabh
Source: NPTEL
🔗 Course Link
Mastering R Programming (Apr 2023)
Rating ⭐️: 4.3 out of 5
Students 👨🎓: 6,161
Duration ⏰: 1hr 47min
Created by: Proton Expert Systems & Solutions
🔗 Course Link
Statistical Computing with R - a gentle introduction (Login Required)
🆓 Free Online Course
Duration ⏰: 6-8 Hours study
🏃♂️ Self paced
Teacher: Max Reuter, Chris Barnes
Resource: University College London
🔗 Course Link
R Programming For Beginners-Full Course | Learn R in 3 Hours| R Language Tutorial | Great Learning
🆓 Free Online Course
🎬 14 video lesson
Duration ⏰: 3-4 hours worth of material
🏃♂️ Self paced
Resource: Great Learning
🔗 Course Link
NOC:Business analytics and data mining Modeling using R, IIT Roorkee
🎬 60 video lesson
⏰ 12 Modules
Taught by: Dr. Gaurav Dixit
Source: NPTEL
🔗 Course Link
Learn Live - Explore and analyze data with R
🆓 Free Online Course
🎬 9 video lesson
Duration ⏰: 1-2 hours worth of material
🏃♂️ Self paced
Resource: Class Central
🔗 Course Link
R Programming Full Course for 2023 | R Programming For Beginners | R Tutorial | Simplilearn
🆓 Free Online Course
🎬 1 video lesson
Duration ⏰: 10-11 hours worth of material
🏃♂️ Self paced
Resource: Youtube
🔗 Course Link
Books
The Book of R
R Programming for Data Science - Roger D. Peng
R for Beginners
#R #R_Language #R_Programming_Language
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Get started in Data Science with Microsoft's FREE course for beginners.
- 10 weeks
- 20 lessons
- Lecture notes
- 100% FREE
https://microsoft.github.io/Data-Science-For-Beginners/
- 10 weeks
- 20 lessons
- Lecture notes
- 100% FREE
https://microsoft.github.io/Data-Science-For-Beginners/
R for Data Science
A weekly data project aimed at the R ecosystem. As this project was borne out of the R4DS Online Learning Community and the R for Data Science textbook, an emphasis was placed on understanding how to summarize and arrange data to make meaningful charts with ggplot2, tidyr, dplyr, and other tools in the tidyverse ecosystem. However, any code-based methodology is welcome - just please remember to share the code used to generate the results.
Creator: rfordatascience
Stars ⭐️: 5.6k
Forked By: 2.3k
https://github.com/rfordatascience/tidytuesday
#R #data_science
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Join @datascience_bds for more cool repositories.
*This channel belongs to @bigdataspecialist group
A weekly data project aimed at the R ecosystem. As this project was borne out of the R4DS Online Learning Community and the R for Data Science textbook, an emphasis was placed on understanding how to summarize and arrange data to make meaningful charts with ggplot2, tidyr, dplyr, and other tools in the tidyverse ecosystem. However, any code-based methodology is welcome - just please remember to share the code used to generate the results.
Creator: rfordatascience
Stars ⭐️: 5.6k
Forked By: 2.3k
https://github.com/rfordatascience/tidytuesday
#R #data_science
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Join @datascience_bds for more cool repositories.
*This channel belongs to @bigdataspecialist group
GitHub
GitHub - rfordatascience/tidytuesday: Official repo for the #tidytuesday project
Official repo for the #tidytuesday project. Contribute to rfordatascience/tidytuesday development by creating an account on GitHub.
Data Science for Engineers, IIT Madras
🆓 Free Online Course
💻 50 Lecture Videos
⏰ 8 Module
🏃♂️ Self paced
Teacher 👨🏫 : Prof. Shankar Narasimhan, Prof. Ragunathan Rengasamy
🔗 https://nptel.ac.in/courses/106106179
#Data_Science #IIT
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🆓 Free Online Course
💻 50 Lecture Videos
⏰ 8 Module
🏃♂️ Self paced
Teacher 👨🏫 : Prof. Shankar Narasimhan, Prof. Ragunathan Rengasamy
🔗 https://nptel.ac.in/courses/106106179
#Data_Science #IIT
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book.pdf
2.4 MB
Foundations of Data Science
by Avrim Blum, John Hopcroft, and Ravindran Kannan
📄 479 pages
#data_science #foundations_of_data_Science
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by Avrim Blum, John Hopcroft, and Ravindran Kannan
📄 479 pages
#data_science #foundations_of_data_Science
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Your Guide to Latent Dirichlet Allocation
Latent Dirichlet Allocation (LDA) is a “generative probabilistic model” of a collection of composites made up of parts. Its uses include Natural Language Processing (NLP) and topic modelling, among others.
In terms of topic modelling, the composites are documents and the parts are words and/or phrases (phrases n words in length are referred to as n-grams).
But you could apply LDA to DNA and nucleotides, pizzas and toppings, molecules and atoms, employees and skills, or keyboards and crumbs.
The probabilistic topic model estimated by LDA consists of two tables (matrices). The first table describes the probability or chance of selecting a particular part when sampling a particular topic (category).
Link
#ml #data_science
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*This channel belongs to @bigdataspecialist group
Latent Dirichlet Allocation (LDA) is a “generative probabilistic model” of a collection of composites made up of parts. Its uses include Natural Language Processing (NLP) and topic modelling, among others.
In terms of topic modelling, the composites are documents and the parts are words and/or phrases (phrases n words in length are referred to as n-grams).
But you could apply LDA to DNA and nucleotides, pizzas and toppings, molecules and atoms, employees and skills, or keyboards and crumbs.
The probabilistic topic model estimated by LDA consists of two tables (matrices). The first table describes the probability or chance of selecting a particular part when sampling a particular topic (category).
Link
#ml #data_science
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
MIT 6.S191: Introduction to Deep Learning 2021
Created by MIT
⏰ 29 hours worth of material
🎬 43 Video lessons
👨🏫 Teacher: Alexander Amini
🔗 Course link
#deeplearning #ai #MIT
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Created by MIT
⏰ 29 hours worth of material
🎬 43 Video lessons
👨🏫 Teacher: Alexander Amini
🔗 Course link
#deeplearning #ai #MIT
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Data Science Ethics (Login Required)
Utilize the framework provided in the course to analyze concerns related to data science ethics.
Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency.
Examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems.
Learn best practices for responsible data management.
Gain an understanding of the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten."
🎬 video lessons
Rating⭐️: 4.1 out 5
🏃♂️ Self paced
Source: University of Michigan
🔗 Course Link
#data_science
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Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group
Utilize the framework provided in the course to analyze concerns related to data science ethics.
Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency.
Examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems.
Learn best practices for responsible data management.
Gain an understanding of the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten."
🎬 video lessons
Rating⭐️: 4.1 out 5
🏃♂️ Self paced
Source: University of Michigan
🔗 Course Link
#data_science
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
Join @datascience_bds for more cool data science materials.
*This channel belongs to @bigdataspecialist group