Data Analysis and Visualization in R

Simpliv

Course

Online

£ 10 + VAT

The best Analysis and Development courses

See all

See all

Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

What is it?Data Science for Professionals is simply the best way to gain a in-depth and practical skill set in data science. Through a combination of theory and hands-on practice, course participants will gain a solid grasp of how to manage, manipulate, and visualize data in R - the world's most popular data science language.Who should take this course?This course is for professionals who are tired of using spreadsheets for analysis and have a serious interest in learning how to use code to improve the quality and efficiency of their work. At the end of this course, participants will have a developed a solid foundation of the fundamentals of the R language. Participants will have also gained a perspective on the modern data science landscape and how they can use R not only to better analyze data, but also to better manage projects, create interactive presentations, and collaborate with other teams. Whether it's spreadsheets, text documents, or slides, anyone who analyzes, reports, or presents data will benefit from a knowledge of data science programming.Who should NOT take this course?While this course covers examples of machine learning in later lectures, this is not a machine learning or a statistics-focused course. The course does go through examples of how to use code to deploy and assess different types of models, including machine learning algorithms, but it does so from a coding perspective and not a statistics perspective. The reason is that the math behind most machine learning algorithms merits a course entirely on its own. There are many courses out there that make dubious claims of easy mastery of machine learning and deep learning algorithms - this is not one of those courses.A Different kind of data science courseThis course is different from most other courses in several ways:
.
We use very large, real-world examples to guide our learning process

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

Students will be able to analyze, manipulate, explore, illustrate, and report data in ways that will set them far apart from those who use spreadsheets and other traditional Office products

Anyone who collects, analyses, reports, or presents data. So pretty much everyone
Anyone who is tired of spreadsheets. Again, pretty much everyone
Anyone who wants to add a lot of value to their skill set and is willing to invest a few hours per week

Questions & Answers

Add your question

Our advisors and other users will be able to reply to you

Who would you like to address this question to?

Fill in your details to get a reply

We will only publish your name and question

Reviews

This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • Programming
  • Project
  • Perspective
  • Statistics
  • Algorithms
  • Data analysis

Course programme

Introduction 3 lectures 20:10 Course Goals and the Data Science Process Welcome to Data Science for Professionals! This course revolves around a single, very large problem: A company is worried about employee attrition (losing employees). The company has collected data on its employees and would like to know which factors are most important in determining whether someone stays or leaves the company. They would also like a predictive model that will allow them to predict which high-value employees are likely to leave in the future. We will learn R programming to solve this problem. By the end of this course, you should be comfortable using R in a way that's practical to your work or study. Why Use R? A Quick Overview of the R Language Introduction 3 lectures 20:10 Course Goals and the Data Science Process Welcome to Data Science for Professionals! This course revolves around a single, very large problem: A company is worried about employee attrition (losing employees). The company has collected data on its employees and would like to know which factors are most important in determining whether someone stays or leaves the company. They would also like a predictive model that will allow them to predict which high-value employees are likely to leave in the future. We will learn R programming to solve this problem. By the end of this course, you should be comfortable using R in a way that's practical to your work or study. Why Use R? A Quick Overview of the R Language Course Goals and the Data Science Process Welcome to Data Science for Professionals! This course revolves around a single, very large problem: A company is worried about employee attrition (losing employees). The company has collected data on its employees and would like to know which factors are most important in determining whether someone stays or leaves the company. They would also like a predictive model that will allow them to predict which high-value employees are likely to leave in the future. We will learn R programming to solve this problem. By the end of this course, you should be comfortable using R in a way that's practical to your work or study. Course Goals and the Data Science Process Welcome to Data Science for Professionals! This course revolves around a single, very large problem: A company is worried about employee attrition (losing employees). The company has collected data on its employees and would like to know which factors are most important in determining whether someone stays or leaves the company. They would also like a predictive model that will allow them to predict which high-value employees are likely to leave in the future. We will learn R programming to solve this problem. By the end of this course, you should be comfortable using R in a way that's practical to your work or study. Course Goals and the Data Science Process Welcome to Data Science for Professionals! This course revolves around a single, very large problem: A company is worried about employee attrition (losing employees). The company has collected data on its employees and would like to know which factors are most important in determining whether someone stays or leaves the company. They would also like a predictive model that will allow them to predict which high-value employees are likely to leave in the future. We will learn R programming to solve this problem. By the end of this course, you should be comfortable using R in a way that's practical to your work or study. Course Goals and the Data Science Process Welcome to Data Science for Professionals! This course revolves around a single, very large problem: A company is worried about employee attrition (losing employees). The company has collected data on its employees and would like to know which factors are most important in determining whether someone stays or leaves the company. They would also like a predictive model that will allow them to predict which high-value employees are likely to leave in the future. We will learn R programming to solve this problem. By the end of this course, you should be comfortable using R in a way that's practical to your work or study. Welcome to Data Science for Professionals! This course revolves around a single, very large problem: A company is worried about employee attrition (losing employees). The company has collected data on its employees and would like to know which factors are most important in determining whether someone stays or leaves the company. They would also like a predictive model that will allow them to predict which high-value employees are likely to leave in the future. We will learn R programming to solve this problem. By the end of this course, you should be comfortable using R in a way that's practical to your work or study. Welcome to Data Science for Professionals! This course revolves around a single, very large problem: A company is worried about employee attrition (losing employees). The company has collected data on its employees and would like to know which factors are most important in determining whether someone stays or leaves the company. They would also like a predictive model that will allow them to predict which high-value employees are likely to leave in the future. We will learn R programming to solve this problem. By the end of this course, you should be comfortable using R in a way that's practical to your work or study. Why Use R? Why Use R? Why Use R? Why Use R? A Quick Overview of the R Language A Quick Overview of the R Language A Quick Overview of the R Language A Quick Overview of the R Language Setup 2 lectures 04:38 Downloading and Installing R RStudio and Project Setup Setup 2 lectures 04:38 Downloading and Installing R RStudio and Project Setup Downloading and Installing R Downloading and Installing R Downloading and Installing R Downloading and Installing R RStudio and Project Setup RStudio and Project Setup RStudio and Project Setup RStudio and Project Setup R Essentials - Data Objects 10 lectures 01:38:37 Section Overview Vectors - Part 1 Getting Help with R Vectors - Part 2 Vectors - Part 3 Vectors - Part 4 Matrices Data Frames Lists Data Object Recap R Essentials - Data Objects 10 lectures 01:38:37 Section Overview Vectors - Part 1 Getting Help with R Vectors - Part 2 Vectors - Part 3 Vectors - Part 4 Matrices Data Frames Lists Data Object Recap Section Overview Section Overview Section Overview Section Overview Vectors - Part 1 Vectors - Part 1 Vectors - Part 1 Vectors - Part 1 Getting Help with R Getting Help with R Getting Help with R Getting Help with R Vectors - Part 2 Vectors - Part 2 Vectors - Part 2 Vectors - Part 2 Vectors - Part 3 Vectors - Part 3 Vectors - Part 3 Vectors - Part 3 Vectors - Part 4 Vectors - Part 4 Vectors - Part 4 Vectors - Part 4 Matrices Matrices Matrices Matrices Data Frames Data Frames Data Frames Data Frames Lists Lists Lists Lists Data Object Recap Data Object Recap Data Object Recap Data Object Recap R Essentials - Functions and Loops 2 lectures 25:42 Loops and IF Statements Custom Functions R Essentials - Functions and Loops 2 lectures 25:42 Loops and IF Statements Custom Functions Loops and IF Statements Loops and IF Statements Loops and IF Statements Loops and IF Statements Custom Functions Custom Functions Custom Functions Custom Functions R Essentials - Putting it all Together! 2 lectures 51:30 The Challenge The Solution R Essentials - Putting it all Together!

Additional information

No prior coding knowledge required

See related categories

Data Analysis and Visualization in R

£ 10 + VAT

The best Analysis and Development courses

See all

See all