Data Science with R for Beginners

Learn how to use R to turn raw data into insight, knowledge, and understanding. This course introduces you to R, RStudio, and a collection of R packages designed to work together to make data science fast, fluent, and fun. This course is suitable for learner’s with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.

162 students enrolled

Course Overview

Data science is an exciting discipline that allows you to turn raw data into understanding, insight, and knowledge. The goal of the “Data Science with R for Beginners” course is to help you learn the most important tools in R that will allow you to do data science. After taking up this course, you’ll have the tools to tackle a wide variety of data science challenges, using the best parts of R.

This course is divided into two parts: Part a) Data Science: Visualization and Analysis and Part b) Data Science: Software Development and Testing.

In the course, we cover basic data manipulation—filtering and selecting relevant data, transforming data into shapes readily analysable, summarising data, visualising data in informative ways both for exploring data and presenting results, and model building. These are the key aspects of doing analysis in data science. After this we will cover how to develop R code that is reusable and works well with existing packages, and that is easy to extend, and we will also see how to build new R packages.

By the end of this course, learners will be equipped with all the knowledge required to start their career as a Data Scientist in the IT industry.

Why take up this course?

  • The demand for Data Science is at an all-time high. With every industry looking to apply AI in their domain, studying Data Science opens a world of opportunities to develop cutting edge machine learning applications in various verticals – such as cyber security, image recognition, medicine, or face recognition.
  • The average starting salary of a Data Scientist is minimum INR 25L per year.
  • People who have Data Science with R Programming skills will have great demand in the IT industry. Our online instructor led training will help you learn these skills and hence upgrade your career.

Course Objectives

After attending this course, learner’s will be able to demonstrate the following skills:

  • Learn how to work with data and write data pipelines.
  • Learn how to integrate documentation and analysis in a single document and how to use such documents to produce reproducible research.
  • Learn how to import, tidy up, and transform data, and compute summaries from data.
  • Learn how to make plots for exploring data features and for presenting data features and analysis results.
  • Learn how to deal with data where the number of observations make the usual approaches too slow.
  • Learn how to train models when you have datasets with known classes or regression values.
  • Learn the basics of R Programming.
  • Learn how R models object orientation and how you can use it to write more generic code.
  • Learn the necessary components of an R package and how to program your own.
  • Learn techniques for testing your R code and checking the consistency of your R packages.
  • Learn how to manage code under version control and how to collaborate using GitHub.
  • Learn how to identify hotspots of code where inefficient solutions are slowing you down and techniques for alleviating this.
  • Learn how to search for patterns you are not aware of in data.

Who should attend this course?

  • Candidates aspiring to be a Data Scientist, Data Engineer, Data Analyst, Data Analytics Professional, Software Developer.
  • Fresh Graduates who are looking to build a career in Data Science and Machine Learning.
  • Enterprise Architects, Managers, CXOs planning to shift to Big data tools in their organisation.
  • Technical professionals and others with technical background that work with large amounts of data and want to take advantage of Machine Learning to improve decision-making processes.

Course Highlights

Advanced Curriculum

Designed by subject specialists and reviewed by industry experts

Interactive Learning

Engaging content, easy to learn with no prior experience required

Discussion Forums

Ask questions and engage in discussions with instructors and other learners

Hands-on Lab Sessions

Practice Labs are available 24/7 for hands-on skill development

Real Life Case Studies

Learn about use cases, solution, challenges, best practices and lot more

Career Mentoring

Get continuous guidance on your career advancement from experts

Guaranteed Job

Guaranteed Job Placement through our network of 450+ Hiring Partners across Pan India

24/7 Tech Support

Get 24/7 full technical support even after you have completed the course

Lifetime Access

Get lifetime access to course material, presentations, videos etc

Post Program Career Options

Data Scientist
ML Engineer
Data Architect
Data Analyst

Average Salary Trends

25 Lac to 30 Lac
25 Lac to 30 Lac
55 Lac to 60 Lac
20 Lac to 25 Lac

Hiring Companies

What are the Prerequisites for this course?

There is no specific prerequisite to learn machine learning. But you need to be from an Engineering/Science/Maths/Stats background to understand the concepts and the techniques used.

Please note that the sessions will be conducted via google meet and require an Internet Connection and headset with microphone connected to your computer or laptop.

Upcoming Batches

Batch Start Date

Course Duration

Class Timings

September 30th 2023

SAT & SUN (12 WEEKS)

WEEKEND BATCH

FEW SEATS LEFT. HURRY UP

10:00 AM to 13:00 PM (IST)

October 9th 2023

MON, WED, FRI (12 WEEKS)

EVENING BATCH

08:30 PM to 10:30 PM (IST)

October 14th 2023

SAT & SUN (12 WEEKS)

WEEKEND BATCH

10:00 AM to 13:00 PM (IST)

October 16th 2023

MON, WED, FRI (12 WEEKS)

MORNING BATCH

06:00 AM to 08:00 AM (IST)

October 23rd 2023

MON, WED, FRI (12 WEEKS)

EVENING BATCH

08:30 PM to 10:30 PM (IST)

Can’t find a batch you were looking for?

Course Certification

Sample Certificate

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Module 1.0 : Introduction to R Programming

1
1.1 : R Programming Overview
2
1.2 : Working with Expressions, Assignments
3
1.3 : Basic Data Types
4
1.4 : Data Structures
5
1.5 : Vectorized Expressions
6
1.6 : Functions
7
1.7 : Recursive Functions
8
1.8 : Control Structures
9
1.9 : Factors
10
1.10 : Data Frames
11
1.11 : Dealing with Missing Values
12
1.12 : Using R Packages
13
1.13 : Data Pipelines
14
1.14 : Coding and Naming Conventions
15
Practice Session : Hands-on Lab
16
Skill Test

Module 2.0 : Reproducible Analysis

1
2.1 : Literate Programming and Integration of Workflow
2
2.2 : Creating an R Markdown Document in RStudio
3
2.3 : The YAML Language
4
2.4 : The Markdown Language
5
2.5 : Running R Code in Markdown Documents
6
2.6 : Caching Results and Displaying Data
7
Practice Session : Hands-on Lab
8
Skill Test

Module 3.0 : Data Manipulation

1
3.1 : Data Already in R
2
3.2 : Reading and Formatting Datasets
3
3.3 : Manipulating Data with dplyr
4
3.4 : Tidying Data with tidyr
5
Practice Session : Hands-on Lab
6
Skill Test

Module 4.0 : Visualizing Data

1
4.1 : Basic Graphics
2
4.2 : Graphics and the ggplot2 package
3
4.3 : Figures with Multiple Plots
4
Practice Session : Hands-on Lab
5
Skill Test

Module 5.0 : Working with Large Datasets

1
5.1 : Subsampling
2
5.2 : Running Out of Memory During Analysis
3
5.3 : Too Large to Plot
4
5.4 : Too Slow to Analyse
5
5.5 : Too Large to Load
6
Practice Session : Hands-on Lab
7
Skill Test

Module 6.0 : Supervised Learning

1
6.1 : Machine Learning Overview
2
6.2 : Regression versus Classification
3
6.3 : Inference versus Prediction
4
6.4 : Specifying Models
5
6.5 : Linear Regression
6
6.6 : Logistic Regression
7
6.7 : Model Matrices and Formula
8
6.8 : Validating Models
9
6.9 : Evaluating Regression Models
10
6.10 : Evaluating Classification Models
11
6.11 : Random Permutations of Your Data
12
6.12 : Cross-Validation
13
6.13 : Selecting Random Training and Testing Data
14
6.14 : Decision Trees
15
6.15 : Random Forests
16
6.16 : Neural Networks
17
6.17 : Support Vector Machines
18
6.18 : Naive Bayes
19
6.19 : Compare Classification Algorithms
20
Practice Session : Hands-on Lab
21
Skill Test

Module 7.0 : Unsupervised Learning

1
7.1 : Dimensionality Reduction
2
7.2 : Principal Component Analysis
3
7.3 : Multidimensional Scaling
4
7.4 : k-Means Clustering
5
7.5 : Hierarchical Clustering
6
7.6 : Association Rules
7
Practice Session : Hands-on Lab
8
Skill Test

Module 8.0 : Advanced R Programming

1
8.1 : Working with Vectors and Vectorizing Functions
2
8.2 : Advanced Functions
3
8.3 : Anonymous Functions
4
8.4 : Functions Taking Functions as Arguments
5
8.5 : Functions Returning Functions
6
8.6 : Filter, Map, and Reduce
7
8.7 : Function Operations: Functions as Input and Output
8
Practice Session : Hands-on Lab
9
Skill Test

Module 9.0 : Object Oriented Programming

1
9.1 : Immutable Objects and Polymorphic Functions
2
9.2 : Data Structures
3
9.3 : Classes
4
9.4 : Defining Your Own Polymorphic Functions
5
9.5 : Class Hierarchies
6
Practice Session : Hands-on Lab
7
Skill Test

Module 10.0 : Building an R Package

1
10.1 : Creating an R Package
2
10.2 : Working with Roxygen
3
10.3 : Adding Data to Your Package
4
10.4 : Building an R Package
5
Practice Session : Hands-on Lab
6
Skill Test

Module 11.0 : Testing and Package Checking

1
11.1 : Unit Testing
2
11.2 : Automating Testing
3
11.3 : Using testthat
4
11.4 : Writing Good Tests
5
11.5 : Using Random Number in Tests
6
11.6 : Testing Random Results
7
11.7 : Checking a package for consistency
8
Practice Session : Hands-on Lab
9
Skill Test

Module 12.0 : Version Control

1
12.1 : Version Control and Repositories
2
12.2 : Using git in Studio
3
12.3 : Collaborating on Github
4
Practice Session : Hands-on Lab
5
Skill Test

Module 13.0 : Profiling and Optimizing

1
13.1 : Profiling
2
13.2 : Graph-Flow Algorithm
3
13.3 : Speeding Up Your Code
4
13.4 : Parallel Execution
5
13.5 : Bayesian Linear Regression
6
13.6 : Formulas and Their Model Matrix
7
13.7 : Interface to a blm Class
8
13.8 : Building an R Package for blm
9
Practice Session : Hands-on Lab
10
Skill Test
The advantages of doing a course from Oxzer Academy are multifold. Our Instructors are professional trainers who have extensive technology and domain experience, including years of experience training & mentoring professionals in the industry. You get lifetime access to course material including presentations, videos etc. You get the industry recognised certificate from Oxzer Academy on your successful course completion. We give you an option to attend a free trial class before enrolling in the course. We provide 24 * 7 online support to resolve all your technical queries even after you have completed the course. We provide flexible batch timings to suit your availability. Most classes are scheduled either on weekends or in the evening hours, so that the class timings do not overlap with your other work during the day time. In case you miss any class, in that case you can go through the recorded videos of that lecture. Also there is an option to attend the lecture in a different batch if there is a seat available. Every module in the course will be followed with a quiz to assess your learning. We give you extensive time to complete the hands-on labs and assignments. We have smaller batches with a limited number of people in a single batch to ensure quality learning.
This is a Virtual Instructor Led training (VILT) where an instructor will facilitate a training session for a group of learners over a virtual setting (online mode). Similar to traditional instructor-led classroom training, VILT is synchronous, collaborative, and happens in real-time.
This is a virtual online Instructor Led course. There will be a maximum of 20 learners in a single batch.
Yes, the course curriculum includes both hands-on lab and theory sessions as well. The hands-on labs will be continuously monitored by our instructor and you get sufficient time to complete your labs. It is mandatory for the learners to attend both the labs as well as theory sessions for successful course completion.
All our labs are provisioned in the cloud. So you can only access the labs during the duration of the course. Ideally, once you have completed your course, your lab access will be removed as well. But in exceptional cases where you need extension for an additional time, you can drop an email to helpdesk@oxzeracademy.com or open a support ticket with our helpdesk regarding this. Once your request has been considered and approved by management, you will receive an email notification within 48 hours from Oxzer Academy providing you with the status on the lab extension. You can request for extension only once.
The online classes will happen on google meet or similar communication platform. You will be notified with the login details before every class.
Yes, you are eligible for one free trial class. You can attend your first class as a trial class. Please note that there is only one trial class provided for each course.
There is only one trial class provided under this course.
Yes, classes are structured in batches and each batch has a specific time. You can enrol yourself in a batch which suits your availability. If you are not able to attend the lecture due to any specific reason then you can go through the recorded videos of that lecture. Also there is an option to attend the lecture in a different batch if there is a seat available.
No, certification exam fee is not included in the course fees. If you wish to appear for the certification exam after course completion, then you need to enrol separately for the certification exam. Please note that any payments which are done on the third party websites, then the terms and condition, refund policy etc of the third party website will be applied.
No, there will be no refund in such cases. Please read the Refund policy carefully before enrolling in the course. https://www.oxzeracademy.com/refund-policy/
We have a 24/7 help desk to support our learners, instructors, customers and partners. You can raise a support ticket to our help desk from this page https://www.oxzeracademy.com/submit-ticket/ Additionally, you can find our contact information on our website https://www.oxzeracademy.com
Oxzer Academy will review the complaint within one hour of submission and will also take necessary action within 24 hours on the posted complaint if required.
There are various channels through which the learners and instructor interact in an online class. Learners can post his question in the google meet or similar communication platform chat and the instructor will respond. Then the learner can raise his hand, unmute himself and can directly ask questions to the Instructor. Also, towards the end of every lecture, there will be a query session for 15 minutes in which the learner can ask any doubt from the Instructor.
No, all our classes will be delivered in an online mode only. In case you require a hard copy of your course completion certificate, it will be courier to your communication address.
We provide 24/7 online support to resolve all your technical queries even after you have completed the course. Your access to our Technical Support is for a lifetime. Our support team will help you in resolving queries, during and after the course. You can raise a support ticket to our technical support from this page https://www.oxzeracademy.com/submit-ticket/
Yes, except for courses listed under academic category, you will get a certificate after you complete the course successfully.
You can find the course duration on the course details page.
Online course assignments depend largely on the course you have enrolled into. But in general, learners should expect assignments similar to those in-person programs. An assignment may require you to work either individually or in groups with other learners on a project. Depending on your course, you may also be required to prepare and give remote presentations.
Exams will be conducted online after all the modules in the course are completed. It is mandatory to switch on the camera while giving a Test or Exam and will be strictly monitored by the instructor. You should score at least 60% marks in the qualifying exam to complete the course successfully and receive your course certificate.
Before enrolling in an online course a learner should go through all the details regarding the course, prerequisite etc. for which they are enrolling and must read all terms and conditions of Oxzer Academy before enrolling in the course.
Yes, our placement team will assist you in all possible ways to find a right job if you are in need of the same. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter. Moreover, Oxzer Academy courses are well recognised in the industry as it is a testament to the intensive and hands-on learning you have gone through and the real life use cases you have learned during the course.
Once you enrol to the course, the LMS access will be instantly provided to you and will be available for lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, assignments etc. Moreover the access to our 24x7 support team will be granted instantly as well.
Yes, the access to the course material will be available for lifetime once you have enrolled into the course.
You can read the complete set of Terms and Conditions for this program at https://www.oxzeracademy.com/terms-and-conditions/

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Course Brochure

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Upcoming Batch Start Date: 09th Oct 2023

Includes

24 hours course duration
Full lifetime access
Access on mobile and TV
Certificate of Completion
24/7 Customer Support
Data Science with R for Beginners
Price:
₹38,400 ₹19,200