Data Science and Machine Learning with R Language

Academy of Skills

Reed courses certificate of completion

Digital certificate - Included

• DS and ML from A-Z Course Intro 35:41

  • 1: Data Science ML Course Intro1 02:30
  • 2: 1.2 What is data science 09:47
  • 3: 1.3 Machine Learning Overview1 05:26
  • 4: 1.4 Whos this course is for1 02:57
  • 5: 1.5 DL and ML Marketplace1 04:38
  • 6: 1.6 Data Science and ML Job opps 02:36
  • 7: 1.7 Data Science Job Roles1 04:04
  • 8: DS+ML course Sales VIdeo 03:43

• Getting Started with R 44:49

  • 9: Getting Started 10:58
  • 10: Basics 06:24
  • 11: Files 11:08
  • 12: R Studio 06:58
  • 13: Tidyverse 05:19
  • 14: Resources 04:02

• Data Types and Structures in R 5:01:48

  • 15: Section Introduction 30:03
  • 16: Basic Types 08:46
  • 17: Vectors Part One 19:40
  • 18: Vectors Part Two 24:51
  • 19: Vectors Missing Values 15:35
  • 20: Vectors Coercion 14:06
  • 21: Vectors Naming 10:15
  • 22: Vectors Misc 05:59
  • 23: Creating Matrices 31:27
  • 24: Lists 31:41
  • 25: Introduction to Data Frames 19:20
  • 26: Creating Data Frames 19:50
  • 27: Data Frames Helper Functions 31:12
  • 28: Data Frames Tibbles 39:03

• Intermediate R 4:14:03

  • 29: Section Introduction Intermediate R 46:31
  • 30: Relational Operations 11:06
  • 31: Logical Operators 07:04
  • 32: Conditoinal Statements 11:19
  • 33: Loops 07:56
  • 34: Functions 14:19
  • 35: Packages 11:29
  • 36: Factors 28:14
  • 37: Dates and Times 30:10
  • 38: Functional Programming 36:41
  • 39: Data Import or Export 22:06
  • 40: Database 27:08

• Data Manipulation in R 5:39:51

  • 41: Data Manipulation in R Section Introduction 36:29
  • 42: Tidy Data 10:53
  • 43: The Pipe Operator 14:50
  • 44: The Filter Verb 21:34
  • 45: The Select Verb 46:03
  • 46: The Mutate Verb 31:56
  • 47: The Arrange Verb 10:03
  • 48: The Summarize Verb 23:05
  • 49: Data Pivoting 42:41
  • 50: JSON Parsing 10:46
  • 51: String Manipulation 32:38
  • 52: Web Scraping 58:53

• Data Visualization in R 2:24:25

  • 53: Data Visualization in R Section Introduction 17:12
  • 54: Getting Started 15:37
  • 55: Aesthetics Mappings 24:44
  • 56: Single Variables Plot 36:50
  • 57: Two Varible Plots 20:33
  • 58: Facets Layering and Coordinate System 17:56
  • 59: Styling and Saving 11:33

• Creating Reports with R Markdown 28:54

  • 60: Creating Reports with R Markdown 28:54

• Building Webapps with R Shiny 1:31:28

  • 61: Section Introduction With R Shiny 26:05
  • 62: A Basic App 31:18
  • 63: Other Examples 34:05

• Introduction to Machine Learning 1:08:33

  • 64: Intro to Machine Learning Part 1 21:48
  • 65: Intro to Machine Learning Part 2 46:45

• Data Preprocessing 1:04:50

  • 66: Data Preprocessing 37:47
  • 67: Introduction to Data Preprocessing 27:03

• Linear Regression_ A Simple Model 1:18:13

  • 68: Linear Regression A Simple Model 53:04
  • 69: LR Section Introduction 25:09

• Exploratory Data Analysis 1:28:00

  • 70: Hands-on Exploratory Data Analysis 1:02:57
  • 71: Section Introduction EDA 25:03

• Linear Regression A Real Model 1:24:52

  • 72: Linear Regression - Real Model Section Intro 32:04
  • 73: Linear Regression in R real model 52:48

• Logistic Regression 1:17:25

  • 74: Introduction to Logistic Regression 37:48
  • 75: Logistic Regression in R 39:37

• Starting A Career in Data Science 29:37

  • 76: Starting a Career in Data Science 02:54
  • 77: Data Science Resume 03:42
  • 78: Getting Started with Freelancing 04:44
  • 79: Top Freelancing Websites 05:18
  • 80: Personal Branding 05:27
  • 81: Importance of Website and Blog 03:42
  • 82: Networking dos and donts 03:50

With the help and knowledge of industry specialists, this novel Data Science and Machine Learning with R Language course has been put together. Data Science and Machine Learning with R Language has been meticulously created to fulfill the learning needs that will enable you to make a significant contribution to the area and carve out a successful career path.

Data Science and Machine Learning with R Language course was created to help motivated students become the best in their personal and professional lives. Many students have already completed and enjoyed this Data Science and Machine Learning with R Language course. This Data Science and Machine Learning with R Language education gave them the tools they needed to advance to more gratifying and rewarding jobs. This one-of-a-kind Data Science and Machine Learning with R Language course is suitable for devoted and ambitious learners who want to be the best at their career or profession.

With the help and knowledge of industry leaders, the original Data Science and Machine Learning with R Language was created. This Data Science and Machine Learning with R Language has been meticulously created to suit all of the learning criteria for making a significant contribution to the associated subject and subsequent career path. By participating in this Data Science and Machine Learning with R Language course, the student will receive valuable knowledge and skills that will help them land their ideal career and establish a strong personal and professional reputation.

After enrolling in this Data Science and Machine Learning with R Language course, you may use our tutor's assistance to help you with any questions you may have, which you can send to our learner support staff through email. This Data Science and Machine Learning with R Language is one of our most popular online courses, created by professionals for the future-focused professional and designed to provide learners with the tools and frameworks they need to lead successfully in a fast changing environment.

Enroll in the Data Science and Machine Learning with R Language right now to advance your abilities.

Curriculum

Course Curriculum: Data Science and Machine Learning with R Language

Here is a curriculum breakdown of the Data Science and Machine Learning with R Language course:

1 - DS and ML from A-Z Course Intro

1 - Data Science ML Course Intro

2 - 1.2 What is data science

3 - 1.3 Machine Learning Overview

4 - 1.4 Whos this course is for

5 - 1.5 DL and ML Marketplace

6 - 1.6 Data Science and ML Job opps

7 - 1.7 Data Science Job Roles

8 - DS+ML course Sales VIdeo

2 - 2. Getting Started with R

9 - Getting Started

10 - Basics

11 - Files

12 - R Studio

13 - Tidyverse

14 - Resources

3 - Data Types and Structures in R

15 - Section Introduction

16 - Basic Types

17 - Vectors Part One

18 - Vectors Part Two

19 - Vectors Missing Values

20 - Vectors Coercion

21 - Vectors Naming

22 - Vectors Misc

23 - Creating Matrices

24 - Lists

25 - Introduction to Data Frames

26 - Creating Data Frames

27 - Data Frames Helper Functions

28 - Data Frames Tibbles

4 - Intermediate R

29 - Section Introduction Intermediate R4

30 - Relational Operations

31 - Logical Operators

32 - Conditoinal Statements

33 - Loops

34 - Functions

35 - Packages

36 - Factors

37 - Dates and Times

38 - Functional Programming

39 - Data Import or Export

40 - Database

5 - Data Manipulation in R

41 - Data Manipulation in R Section Introduction

42 - Tidy Data

43 - The Pipe Operator

44 - The Filter Verb

45 - The Select Verb

46 - The Mutate Verb

47 - The Arrange Verb

48 - The Summarize Verb

49 - Data Pivoting

50 - JSON Parsing

51 - String Manipulation

52 - Web Scraping

6 - 6. Data Visualization in R

53 - Data Visualization in R Section Introduction

54 - Getting Started

55 - Aesthetics Mappings

56 - Single Variables Plot

57 - Two Varible Plots

58 - Facets Layering and Coordinate System

59 - Styling and Saving

7 - Creating Reports with R Markdown

60 - Creating Reports with R Markdown

8 - Building Webapps with R Shiny

61 - Section Introduction With R Shiny

62 - A Basic ApP

63 - Other Examples

9 - 9. Introduction to Machine Learning

64 - Intro to Machine Learning Part 1

65 - Intro to Machine Learning Part 2

10 - Data Preprocessing

66 - Data Preprocessing

67 - Introduction to Data Preprocessing

11 - Linear Regression_ A Simple Model

68 - Linear Regression A Simple Model

69 - LR Section Introduction

12 - Exploratory Data Analysis

70 - Hands-on Exploratory Data Analysis

71 - Section Introduction EDA

13 - Linear Regression A Real Model

72 - Linear Regression - Real Model Section Intro

73 - Linear Regression in R real model

14 - Logistic Regression

74 - Introduction to Logistic Regression

75 - Logistic Regression in R

15 - Starting A Career in Data Science

76 - Starting a Career in Data Science

77 - Data Science Resume

78 - Getting Started with Freelancing

79 - Top Freelancing Websites

80 - Personal Branding

81 - Importance of Website and Blog

82 - Networking dos and donts

The Data Science and Machine Learning with R Language training course is ideal for highly driven students who wish to improve your personal and professional abilities while also preparing for the career of their dreams! This Data Science and Machine Learning with R Language is also great for persons who want to learn more about this topic in depth and appreciate being up to speed on the newest facts and expertise.

• There are no official requirements for Data Science and Machine Learning with R Language
• Data Science and Machine Learning with R Language requires a basic Internet connection
• Data Science and Machine Learning with R Language requires you to have access to a computer, tablet, or a mobile device
• Knowledge of basic English

The Data Science and Machine Learning with R Language course is meant to prepare you for the job of your dreams, a promotion at work, or being self-employed and starting your own business.

Courses from the Academy of Skills will help you enhance your profession and keep your skills current.

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