Data Science with R Programming Certification Training Course

BY
Edureka

Join Edureka’s Data Science Certification Course using R to gain a professional Data Science training and the knowledge of Machine Learning algorithms.

Mode

Online

Fees

Free

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom
Mode of Delivery Video and Text Based

Course overview

The Data Science with R Programming Certification Training Course training lets you have a conceptual understanding of statistics, Text Mining, Time Series, and an introduction to Deep Learning. You will gain proficiency in Machine Learning Algorithms like Random Forest, K-Means Clustering, Decision Trees and naïve Bayes using R language.

In the ‘Data Science with R Programming Certification Training Course’ on Edureka, you will implement real-life use-cases on Aviation, Social Media, Healthcare, Media and Human Resources. The course curriculum also allows you to comprehend the entire life cycle of Data Science, visualize and analyze various data sets and different Machine Learning Algorithms.

Data Science is a concept of combining data analysis, statistics and their related methods to analyze and understand actual phenomena with data. Data Science Training has theories and techniques drawn from many sectors within the broad areas of information science, statistics, maths, and computer science from sub-domains of classification, data mining, visualization, databases, machine learning and cluster analysis. Undertaking the online Data Science with R Programming Certification Training Course will enable aspirants to master these, helping them become a fluent professional of Data Science.

The highlights

  • 30 hours of live content
  • Data Science category
  • Five weeks duration
  • Life-long LMS access
  • Pre-recorded videos
  • Employment assistance
  • Real-life case studies
  • 24x7 learner assistance
  • Regular assignments
  • A community forum for peer interaction
  • Data Science Expert certificate
  • No Prerequisites course
  • Certification and Training programme

Program offerings

  • Online batches
  • Live classes
  • Instructor-led sessions
  • Certification
  • Training
  • Real-time industry-based projects
  • Forum
  • Lifetime access
  • Assignments.

Course and certificate fees

Type of course

Free

certificate availability

Yes

certificate providing authority

Edureka

Who it is for

Data Analytics, as a career, is growing all over the world at a rapid rate. This means increasing opportunities for IT professionals. Accelerate your career by learning all the aspects of Data Science through Data Science with R Programming Certification Training Course. The online course is best suited for the following professionals:

  • Analysts wanting to understand Data Science methodologies
  • Information Architects who want to gain expertise in Predictive Analytics
  • Analytics Managers who are leading a team of analysts
  • Developers aspiring to be a 'Data Scientist'
  • Business Analysts who want to understand Machine Learning (ML) Techniques
  • 'R' professionals who wish to work Big Data

Eligibility criteria

Towards the end of the Data Science with R Programming Certification Training Course, candidates will be working on a project. Also, each class has practical assignments which shall be completed before the upcoming class. The candidate will be eligible for certification based on his/her project submission.

As for prerequisites to enrol in the course, there are none. However, some prior basic knowledge of R will prove advantageous.

What you will learn

R programming Data science knowledge Machine learning Knowledge of deep learning Statistical skills

With a Data Science with R Programming Certification Training Course, you will be on your way to becoming a Data Science Expert. It will develop your skills by providing you with hands-on experience. After the completion, you will:

  • Understand the concepts of Deep Learning
  • Discuss Data Mining techniques and their implementation
  • Gain insight into the 'Roles' played by a Data Scientist
  • Explain Time Series and its related concepts
  • Gain insight into Data Visualization and Optimization techniques
  • Work with different data formats like XML, CSV, etc.
  • Analyze data using Machine Learning algorithms in R
  • Learn tools and techniques for Data Transformation
  • Describe the Data Science Life Cycle
  • Perform Text Mining and Sentimental analysis on text data
  • Analyze several types of data using R

The syllabus

Introduction to Data Science with R

Topics
  • What is Data Science?
  • The era of Data Science
  • Introduction to Big Data and Hadoop
  • What does Data Science involve?
  • Business Intelligence vs Data Science
  • Tools of Data Science
  • Introduction to R
  • The life cycle of Data Science
  • Introduction to Spark
  • Introduction to Machine Learning

Statistical Inference

Topics
  • Measures of Spread
  • What is Statistical Inference?
  • Measures of Centres
  • Terminologies of Statistics
  • Binary Distribution
  • Probability
  • Normal Distribution

Data Extraction, Wrangling and Exploration

Topics
  • What is Data Extraction
  • Raw and Processed Data
  • Exploratory Data Analysis
  • Data Analysis Pipeline
  • Types of Data
  • Data Wrangling
  • Visualization of Data
Hands-On/Demo
  • Arranging the data
  • Loading different types of the dataset in R
  • Plotting the graphs

Introduction to Machine Learning

Topics
  • Machine Learning Process Flow
  • What is Machine Learning?
  • Supervised Learning algorithm: Linear Regression and Logistic Regression
  • Machine Learning Use-Cases
  • Machine Learning Categories
Hands-On/Demo
  • Implementing a Logistic Regression model in R
  • Implementing Linear Regression model in R

Classification Techniques

Topics
  • What are classification and its use cases?
  • Algorithm for Decision Tree Induction
  • Confusion Matrix
  • What is Naive Bayes?
  • What is a Decision Tree?
  • Creating a Perfect Decision Tree
  • What is a Random Forest?
  • Support Vector Machine: Classification
Hands-on/Demo
  • Implementing Linear Random Forest in R
  • Implementing the Decision Tree model in R
  • Implementing Support Vector Machine in R
  • Implementing a Naive Bayes model in R

Unsupervised Learning

Topics
  • What is C-means Clustering?
  • What is Hierarchical Clustering?
  • What is Clustering & its use cases?
  • What is Canopy Clustering?
  • What is K-means Clustering?
Hands-On/Demo
  • Implementing Hierarchical Clustering in R
  • Implementing C-means Clustering in R
  • Implementing K-means Clustering in R

Recommender Engines

Topics
  • User-Based Recommendation
  • Difference: User-Based and Item-Based Recommendation
  • What is the Recommendation Engine & it’s working?
  • Item-Based Recommendation
  • Types of Recommendations
  • What are Association Rules & its use cases?
  • Recommendation use cases
Hands-On/Demo
  • Building a Recommendation Engine in R
  • Implementing Association Rules in R

Text Mining

Topics
  • Text Mining Algorithms
  • The concepts of text-mining
  • Beyond TF-IDF
  • TF-IDF
  • Use cases
  • Quantifying text
Hands-On/Demo
  • Implementing Sentiment Analysis on Twitter Data using R
  • Implementing the Bag of Words approach in R

Time Series

Topics
  • What is Time Series Data?
  • Implement the ARIMA model for forecasting
  • Identifying different time series scenario based on which different Exponential Smoothing model can be applied
  • Time Series variables
  • Visualize the data to identify Time Series Components
  • Exponential smoothing models
  • Different components of Time Series data
  • Implement the respective ETS model for forecasting
Hands-On/Demo
  • Forecasting for the given Time period
  • Visualizing and formatting Time Series data
  • Applying ARIMA and ETS model for Time Series Forecasting
  • Plotting decomposed Time Series data plot

Deep Learning

Topics
  • Reinforcement learning Process Flow
  • Deep Learning
  • Understand Artificial Neural Networks
  • How ANN works
  • Reinforced Learning
  • Reinforced Learning Use cases
  • Biological Neural Networks
  • Building an Artificial Neural Network
  • Important Terminologies of ANN’s

Admission details

To book your admission in Data Science with R Programming Certification Training Course at Edureka, you must go through the following steps in a similar sequence:

Step 1 – Click or tap on the link given below. It will open up the official course page.

https://www.edureka.co/data-science-r-programming-certification-course

Step 2 – Have a look at various live batch dates. Click the ‘Enrol now button’. Fill your details in the popup form and press the ‘Enter’ key.

Step 3 – A payment gateway will open up. Pay the course fee securely and proceed.

Step 4 – When the payment is complete, you will get a receipt and all the course details on your registered email address and phone number.

You have successfully enrolled in the Data Science with R Programming Certification Training Course on Edureka’s website.

Evaluation process

There are no examinations that a candidate has to take to receive the certification. However,  they have to submit a project towards the end of the Data Science with R Programming Certification Training Course to obtain the desired credential.

How it helps

Data Science is a massive booster for one’s career. The number of Data Science and Analytics jobs is only going to grow by nearly 364,000 listings by 2020, according to Forbes. The Data Science with R Programming Certification Training Course will equip the learners to become certified Data Science professionals who can demand handsome salaries.

Data Science increases the productivity of businesses in a big way. Many other benefits that this course offers are as follows:

  • Performing Text Mining and Sentimental analysis of text data.
  • Access to a resume-building tool via the LMS, to create a professional CV and showcase the acquired experience.
  • In-depth knowledge of Data Science Life Cycle and Machine Learning Algorithms.
  • Projects which are diverse covering media, healthcare, social media, aviation and HR.
  • Comprehensive understanding of Data Transformation’s numerous tools and techniques.
  • The exposure to several real-life industry-based projects, executed in RStudio.
  • Gaining insight into Data Visualization and Optimization techniques.
  • Learning the industry standards and best practices by an SME’s rigorous involvement throughout the Data Science Training.

FAQs

How to execute the practicals in Data Science with R Programming Certification Training Course?

You will have to set-up R programming IDE on your computer system. Download RStudio Desktop Open Source License from Rstudio’s official website for free. Additionally, step-by-step installation guides will be provided in your LMS to help you with the process.

Who is the Data Science with R Programming Certification Training Course instructors?

All the Edureka instructors and teachers are practitioners from their respective industry with a minimum relevant IT experience of 10 or 12 years. They are specially trained by Edureka for providing you with a quality experience.

Do I get Placement Assistance as well?

For helping our learners in job search, we have included a Resume Builder Tool in their LMS. A three-step approach is designed to help you create a winning resume in no time. Plus, you get unlimited access to the templates across different designations and roles.

How to visit a missed class?

You can attend any class you miss in another live batch. Alternatively, you may view the recorded session that you missed, which will be available in your LMS.

Where to reach if I have further queries?

Drop a mail at sales@edureka.co OR place a call at +919870276457/1844 230 6362 ( US Toll-free ). Our expert team will assist you in all your questions and queries.

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