Data Science for Beginners - Be a Data Scientist in 30 Days

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INTRODUCTION TO DATA SCIENCE: 3:51- 01:25:00 3:51 Trainer Introduction : The Instructor Mr. Rajib Layek who is a Business Consultant and Senior data scientist having experience of 8+ years. 6:24 Course Curriculum Overview 29:05 Introduction to Data Science 42:37 Introduction to Business Analytics:practice using optimal business management decisions with the help of graphics and analytical tools 54:54 Introduction to Machine Learning: It helps computers to learn,act,response like humans and improve their learning from experience without being explicitly programmed. 01:07:00 How to switch your career into ML 01:22:00 Introduction To Data Scientist

INTRODUCTION TO R 1:25:00 - 1:51:00 1:25:00 Introduction to R 1:40:00 How to set up R

R Programming 1:51:00 - 2:46:00 1:51:00 R Operator 2:05:00 R Conditional Statement & Loop 2:17:00 Function in R

R Data Structure 2:46:00 - 3:35:00 2:46:00 An Introduction of R Data Structure + Vector 2:57:00 Matrix, Array and Data Frame 3:11:00 A Deep Drive to R Data Frame 3:24:00 Factor 3:29:00 List

Import and Export in R 3:35:00 - 4:07:00 3:35:00 Import CSV Data in R 3:44:00 Import Text Data in R 3:47:00 Import Excel, Web Data in R 4:00:00 Export Data in R - Text 4:02:00 Export Data in R - CSV & Excel

Data Manipulation 4:07:00 - 5:40:00 4:07:00 Apply Function 4:31:00 Dplyr package 5:29:00 Date with R

Data Visualization 5:40:00 - 7:48:00 5:40:00 Introduction to Data Visualization & Scatter Plot 5:51:00 Data Visualization - mfrow 5:59:00 Data Visualization - pch 6:11:00 Data Visualization - Color 6:13:00 Data Visualization - Line Chart 6:16:00 Data Visualization - Bar Plot 6:23:00 Data Visualization - Pie Chart 6:29:00 Data Visualization - Histogram 6:36:00 Data Visualization - Density Plot 6:39:00 Data Visualization - Box Plot 6:44:00 Data Visualization - Mosaic Plot and Heat Map 6:52:00 Data Visualization - 3D Plot 7:02:00 Correlation Plot and Word Cloud 7:11:00 Data Visualization - ggplot2

Machine Learning Toolbox 7:48:00 - 8:14:00

Business Case Understanding 8:14:00 - 8:27:00

Data Pre-Processing 8:27:00 - 9:51:00

SUPERVISED LEARNING : REGRESSION 9:51:00 - 12:56:00 9:51:00 Linear Regression 11:50:00 Correlation Part 12:04:00 Stepwise Regression 12:32:00 Dummy Variable 12:45:00 Non Linear

Capstone Project 12:56:00 - 13:37:00 12:56:00 Introduction 13:04:00 Data Understanding 13:12:00 Lazy Predictor 13:19:00 Data Preparation 13:25:00 Data Exploration 13:29:00 Feature Engineering

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