Certification Course: Data Science using R
Learner rating  9.5 

 Course platform: Edureka
 Lifetime Access
 Level: All Level
 Price: Paid course (with Certificate)
 Class length: Approx. 30 hrs
Edureka’s Certification Course: Data Science using R
What is data science?
Data science, in its most basic terms, can be defined as obtaining insights and information, really anything of value, out of data. Like any new field, it’s often tempting but counterproductive to try to put concrete bounds on its definition. This is data science. This is not. In reality, data science is evolving so fast and has already shown such an enormous range of possibilities that a wider definition is essential to understanding it.
“We’re entering a new world in which data may be more important than software.”
– Tim O’Reilly, founder, O’Reilly Media
And while it’s hard to pin down a specific definition, it’s relatively easy to see and feel its impact. Data science, when applied to different fields can lead to incredible new insights. And the folks that are using it are already reaping the benefits.
What is R Programming?
R is a programming language and an analytics tool and It is extensively used by Software Programmers, Statisticians, Data Scientists, and Data Miners. It is one of the most popular analytics tool used in Data Analytics and Business Analytics.
It has numerous applications in domains like healthcare, academics, consulting, finance, media, and many more. Its vast applicability in Statistics, Data Visualization, and Machine Learning have given rise to the demand for certified trained professionals in R.
About Data Science using R course
Edureka’s Data Science using R Training lets you gain expertise in Machine Learning Algorithms like KMeans Clustering, Decision Trees, Random Forest, and Naive Bayes using R. Data Science Training encompasses a conceptual understanding of Statistics, Time Series, Text Mining, and an introduction to Deep Learning. Throughout this Data Science Course, you will implement reallife usecases on Media, Healthcare, Social Media, Aviation, and HR.
About the Data Science Certification
Data science is a “concept to unify statistics, data analysis, and their related methods” to “understand and analyses actual phenomena” with data. Data Science Training employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science from the subdomains of machine learning, classification, cluster analysis, data mining, databases, and visualization. The Data Science Certification Course enables you to gain knowledge of the entire life cycle of Data Science, analyses and visualize different data sets, different Machine Learning Algorithms like KMeans Clustering, Decision Trees, Random Forest, and Naive Bayes.
What you will learn:
 Gain insight into the ‘Roles’ played by a Data Scientist.
 Analyze several types of data using R programming.
 Describe the Data Science Life Cycle.
 Work with different data formats like XML, CSV, etc.
 Learn tools and techniques for Data Transformation.
 Discuss Data Mining techniques and their implementation.
 Analyze data using Machine Learning algorithms in R programming.
 Explain Time Series and it’s related concepts.
 Perform Text Mining and Sentimental analyses on text data.
 Gain insight into Data Visualization and Optimization techniques
 Understand the concepts of Deep Learning.
Who this Course is for:
The market for Data Analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Our Data Science Training helps you to grab this opportunity and accelerate your career by applying the techniques on different types of Data.
What are the objectives of our Data Science Online Course?
 Indepth knowledge of Data Science Life Cycle and Machine Learning Algorithms
 Comprehensive knowledge of various tools and techniques for Data Transformation
 The capability to perform Text Mining and Sentimental analyses on text data and gain an insight into Data Visualization and Optimization techniques
 The exposure to many reallife industrybased projects which will be executed in R Studio
 Projects which are diverse in nature covering media, healthcare, social media, aviation, and HR
 Rigorous involvement of an SME throughout the Data Science Training to learn industry standards and best practices
Syllabus:
1. Introduction to Data Science
 What is Data Science and What does Data Science involve?
 The era of Data Science, the Life cycle of Data Science, and Tools of Data Science.
 Business Intelligence vs Data Science.
 Introduction to data science using R: Big Data, Hadoop, R, Spark, and Machine Learning.
2. Statistical Inference
 What is Statistical Inference?
 Terminologies of Statistics.
 Measures of Centers and Spread.
 Normal Distribution and Binary Distribution.
3. Data Extraction, Wrangling, and Exploration
 Data Analysis Pipeline and Types of Data
 What is Data Extraction
 Raw and Processed Data and Data Wrangling.
 Exploratory Data Analysis and Visualization of Data.
4. Introduction to Machine Learning
 What is Machine Learning?
 Machine Learning UseCases, Process Flow and
 Supervised Learning algorithm: Linear Regression and Logistic Regression.
5. Data Science using R: Classification Techniques
 What are classification and its use cases?
 What is a Decision Tree?
 Algorithm for Decision Tree Induction and Creating a Perfect Decision Tree.
 Confusion Matrix.
 What is a Random Forest?
 What is Navies Bayes?
 Support Vector Machine: Classification.
7. Unsupervised Learning
 What is Clustering & its use cases?
 What are Kmeans, Cmeans, Canopy, and Hierarchical Clustering?
8. Recommender Engines
 What is Association Rules & its use cases?
 What is the Recommendation Engine & it’s working?
 Types of Recommendations and Recommendation use cases.
 UserBased Recommendation and ItemBased Recommendation.
 Difference: UserBased and ItemBased Recommendation.
9. Text Mining
 The concepts of textmining and Use cases.
 Text Mining Algorithms.
 Quantifying text.
 TFIDF and Beyond TFIDF.
Project Description
Edureka’s Data Science using R Training includes realtime industrybased projects, which will hone your skills as per current industry standards and prepare you for the upcoming Data Scientist roles.
Prerequisites:
There is no specific prerequisite for Data Science Training. However, a basic understanding of R programming can be beneficial. Edureka offers you a complimentary selfpaced course, i.e. “R Essentials” when you enroll in Data Science Training.
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