Applied Data Science with R

Learn how to execute an end-to-end data science project and deliver business results
4.2 (180 ratings) Instead of using a simple lifetime average, Udemy calculates a
course's star rating by considering a number of different factors
such as the number of ratings, the age of ratings, and the
likelihood of fraudulent ratings.
3,514 students enrolled
$30
Take This Course
  • Lectures 55
  • Contents Video: 11 hours
    Other: 0 mins
  • Skill Level Intermediate Level
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
Wishlisted Wishlist

How taking a course works

Discover

Find online courses made by experts from around the world.

Learn

Take your courses with you and learn anywhere, anytime.

Master

Learn and practice real-world skills and achieve your goals.

About This Course

Published 2/2015 English

Course Description

"Data Science is the sexiest job of the 21st century - It has exciting work and incredible pay".

Learning Data Science though is not an easy task. The field traverses through Computer Science, Programming, Information Theory, Statistics and Artificial Intelligence. College/University courses in this field are expensive. Becoming a Data Scientist through self-study is challenging since it requires going through multiple books, websites, searches and exercises and you will still end up feeling "not complete" at the end of it. So how do you acquire full-stack Data Science skills that will get you a and give you the confidence to execute it?

Applied Data Science with R addresses the problem. This course provides extensive, end-to-end coverage of all activities performed in a Data Science project. If teaches application of the latest techniques in data acquisition, transformation and predictive analytics to solve real world business problems. The goal of this course is to teach practice rather than theory. Rather than deep dive into formulae and derivations, it focuses on using existing libraries and tools to produce solutions. It also keeps things simple and easy to understand.

Through this course, we strive to make you fully equipped to become a developer who can execute full fledged Data Science projects. By taking this course, you will

  • Appreciate what Data Science really is
  • Understand the Data Science Life Cycle
  • Learn to use R for executing Data Science Projects
  • Master the application of Analytics and Machine Learning techniques
  • Gain insight into how Data Science works through end-to-end use cases.

By becoming a student of V2 Maestros, you will also get maximum discounts on all of our other current and future courses (coupon codes inside the course material). You will also get prompt support of all your queries and questions. We continuously strive to improve our course material to reflect the latest trends and technologies

What are the requirements?

  • Programming Experience in at least one language like Java, C/C++/C#, Python, Perl
  • Experience in analyzing Data preferred

What am I going to get from this course?

  • Appreciate what Data Science really is
  • Understand the Data Science Life Cycle
  • Learn to use R for executing Data Science Projects
  • Master the application of Analytics and Machine Learning techniques
  • Gain insight into how Data Science works through end-to-end use cases.

What is the target audience?

  • IT Professionals aspiring to be Data Scientists
  • Students who want to learn about Data Science domain
  • Statisticians and Project Managers who want to expand their horizon into Data Science

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.

Curriculum

Section 1: Introduction
About this Course
Preview
08:12
About V2 Maestros
Preview
01:39
Resource Bundle
Article
Section 2: What is Data Science?
Basic Elements of Data Science
11:51
The Dataset
10:44
Learning from relationships
12:55
Modeling and Prediction
09:31
Use Cases for Data Science
07:47
Section 3: Data Science Life Cycle
Stage 1 - Setup
11:46
Stage 2 - Data Engineering
Preview
11:57
Stage 3 & 4 - Analysis and Production
19:16
Section 4: Statistics for Data Science
Types of Data
07:29
Summary Statistics
16:10
Statistical Distributions
19:05
Correlations
10:09
Section 5: R Programming
Downloading and Installing R and R Studio
Article
R Studio - Walkaround
06:40
R Language Basics
12:04
Vectors and Lists
08:51
Data Frames and Matrices
14:41
Data Manipulation and I/O Operations
Preview
10:30
Programming and Packages
12:41
Statistics in R
03:01
Graphics in R
06:51
R Code Examples - Variables and Vectors
16:18
R Code Examples - Data Frames and Matrices
15:05
R Code Examples - Programming Elements
17:18
R Code Examples - Statistics and Base Plotting System
17:29
R Code Examples - ggplot
17:22
Section 6: Data Engineering
Data Acquisition
16:01
Data Cleansing
10:50
Data Transformations
11:09
Text Pre-Processing TF-IDF
14:53
R Examples for Data Engineering
11:14
Section 7: Machine Learning and Predictive Analysis
Types of Analytics
12:08
Types of Learning
17:16
Analyzing Results and Errors
13:46
Linear Regression
19:00
R Use Case : Linear Regression
18:01
Decision Trees
10:42
R Use Case : Decision Trees
19:36
Naive Bayes Classification
Preview
19:21
R Use Case : Naive Bayes
19:12
Random Forests
10:31
R Use Case : Random Forests
18:47
K-means Clustering
11:53
R Use Case : K-Means clustering
16:24
Association Rules Mining
11:31
R Use Case : Association Rules Mining
13:11
Section 8: Advanced Topics
Artificial Neural Networks and Support Vector Machines
04:35
Bagging and Boosting
11:27
Dimensionality Reduction
07:28
R Use Case : Advanced Methods
17:18
Section 9: Conclusion
Closing Remarks
03:35
BONUS Lecture : Other courses you should check out
Article

Students Who Viewed This Course Also Viewed

  • Loading
  • Loading
  • Loading

Instructor Biography

V2 Maestros, Big Data Science / Analytics Experts | 10K+ students

V2 Maestros is dedicated to teaching big data / data science at affordable costs to the world. Our instructors have real world experience practicing big data and data science and delivering business results. Big Data Science is a hot and happening field in the IT industry. Unfortunately, the resources available for learning this skill are hard to find and expensive. We hope to ease this problem by providing quality education at affordable rates, there by building data science talent across the world.

Ready to start learning?
Take This Course