R For Data Science Full Course | Data Science With R Full Course |Data Science Tutorial |Simplilearn

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In this video on R for Data Science Full Course, we’ll start by learning data science from an animated video. You will then learn the essential concepts in data science and understand the important packages in R for data science. You will look at some of the widely used data science algorithms such as Linear regression, logistic regression, decision trees, and random forest, including time-series analysis. Finally, you will get an idea about the Salary structure, Skills, Jobs, and resume of a data scientist.

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00:00:00 Data science in 5 min
00:05:23 Data science concept
00:17:40 Data science package in R
01:18:51 Linear Regression in R
01:47:07 Use Case :Linear Regression
02:04:31 Logistic Regression in R
02:22:37 Decision tree in R
03:22:03 Random forest in R
04:02:10 What is clustering
04:43:54 Time series analysis
05:54:16 Salary, Skills, and resume

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➡️ About Data Science Course in collaboration with IBM
This Data Science course in collaboration with IBM propels your career to become a data scientist. Gain expertise in in-demand skills like Python, SQL, Excel, Machine Learning, Tableau, generative AI, and more. Dive deep into data interpretation nuances, master Machine Learning, and enhance programming skills to elevate your Data Science career.

✅ Key Features
Simplilearn's JobAssist helps you get noticed by top hiring companies
Masterclasses from IBM experts
Dedicated live sessions by faculty of industry experts
Industry-recognized Data Scientist Master’s certificate from Simplilearn
Industry-recognized IBM certifications for IBM courses
Ask-Me-Anything (AMA) sessions with IBM leadership
Capstone from 3 domains and 25+ projects
Exclusive hackathons conducted by IBM
Lifetime access to self-paced learning content
Program crafted to initiate your journey as a Data Scientist
Integrated labs for hands-on learning experience

✅ Skills Covered
Generative AI
Prompt Engineering
ChatGPT
Exploratory Data Analysis
Descriptive Statistics
Inferential Statistics
Explainable AI
Conversational AI
Large Language Models
Model Building and Finetuning
Ensemble Learning
Data Visualization
Database Management

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