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Data Science with R
Learn Data Science With R to become a Data Scientists or Data Analyst with R programming Language. Enroll yourself now and get a competitive advantage that leads to new career opportunities.
Industrial Trainers Support
Work on Real Time Projects
One-on-one Sessions
Fully Interactive Online Sessions
About Data science with R Course
No of classes X Hours
59 x 3 = 177 Hours
Self Study Hours
100 Hours
Assignments & Case Studies
22
Embark on a transformative journey in data science with our comprehensive Data Science with R Programming course. Whether you’re a novice or an experienced data scientist, this course is specifically designed to equip you with the essential skills and knowledge needed for success in the field.
Explore a wide range of topics, including data manipulation, data visualization, statistical analysis, and machine learning, all while harnessing the power of R programming. With R, you’ll learn how to effectively clean and manipulate data, create captivating visualizations, and develop predictive models that reveal valuable insights.
Our hands-on and interactive approach ensures active learning, providing real-world examples and exercises to put your knowledge into practice. Engage with authentic data sets and apply data science techniques to solve genuine challenges, gaining the practical experience necessary to excel in the field.
Throughout your journey, our expert instructors are dedicated to providing personalized support and guidance. Additionally, our vibrant community forum offers a collaborative environment, where you can seek advice, exchange ideas, and receive feedback from fellow students and instructors.
Whether you’re looking to advance your data science career or enhance your skills and knowledge, our Data Science with R Programming course serves as the ideal launchpad. Don’t hesitate—enroll today and embark on the path to becoming a proficient data science expert with Brainalyst!
Data Science Course using R Curricullum
The course curriculum starts with data analytics using R for data handling, manipulation and descriptive analytics. You also learn to use R with databases and data visualization. This data science with R course statistical analysis, regression modelling and gradually move to learn important machine learning concepts and techniques
- Chapter 1.1 : Basic Excel
- Chapter 1.2 : Basic Programming Elements
- Chapter 1.3 : Introduction of Basic Statistics
- Chapter 1.4 : Overview of Dashboard
- Chapter 1.5 : Business dashboard creations
- Chapter 1.6 : Data manipulation using functions
- Chapter 1.7 : Data Visualization in Excel
- Chapter 1.8 : Introduction to Analytics & Data Science
- Chapter 1.9 : Create dashboard in Excel – Using pivot controls
- Chapter 2.1 : Data Analytics with VBA
- Chapter 2.2: A look at some commonly used code snippets
- Chapter 2.3 : Programming Constructs in VBA
- Chapter 2.4 : Functions & Procedures in VBA-Modularizing your programs
- Chapter 2.5 : Objects & Memory Management in VBA
- Chapter 2.6 : Error Handling
- Chapter 2.7 : Controlling accessibility of your code – Access Specifiers
- Chapter 2.8 : Code reusability – Adding references and components of
your code - Chapter 2.9 : How VBA works with Excel
- Chapter 2.10 : Key Component of programming language
- Chapter 2.11 : Communicating with your users
- Chapter 3.1 : Intro to RDBMS & Basic SQL
- Chapter 3.2 : Data Based Object Creation (DDL commands)
- Chapter 3.3: Data Manipulation
- Chapter 3.4: Accessing data from multiple tables using Select
- Chapter 3.5: Advanced SQL
- Chapter 4.1 : Getting Started
- Chapter 4.2 : Data handlings & Summaries – I
- Chapter 4.3 : Data handlings & Summaries – II
- Chapter 4.4 : Building Advanced Reports/Maps
- Chapter 4.5 : Calculated Fields
- Chapter 4.6 : Table Calculations
- Chapter 4.7 : Parameters
- Chapter 4.8 : Buildings Interactive Dashboard
- Chapter 4.9 : Building Stories
- Chapter 4.10 : Work with data
- Chapter 4.11 : Sharing work with others
- Chapter 5.1 : Introduction to R
- Chapter 5.2 : Installation of R Software
- Chapter 5.3 : Basics of R Programming
- Chapter 5.4 : Modular Programming – Packages
- Chapter 5.5 : Data Types & Data structures
- Chapter 5.6 : Other Programming Elements
- Chapter 5.7 : Importing & Exporting data
- Chapter 5.8 : Understanding of data
- Chapter 5.9 : Data Preparation/manipulation of data
- Chapter 5.10 : Basic Statistics
- Chapter 5.11 : Data Visualization
- Chapter 5.12 : Shiny
- Chapter 5.13 : Introduction to Modelling
- Chapter 5.14 : Linear Regression
- Chapter 5.15 : Logistic Regression
- Chapter 5.16 : Segmentation
- Chapter 5.17 : Forecasting
- Chapter 5.18 : Machine Learning
- Chapter 5.19 : Deep Learning Basics
- Chapter 5.20 : Text Mining
Who Should Do?
Students from multiple quantitative backgrounds like Engineering, Finance, Maths, Statistics, and Business Management want data science with R training from the basics with a focus on R programming for data science and Machine Learning methods.
FAQ
Course Fee
₹
40,000
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Full Lifetime Access
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Live Interactive Classes
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Certificate of completion
Popular
Want to Know More?
The Data Science with R programming is an educational program offered by Brainalyst that teaches students how to use R programming for data science. It covers topics such as data manipulation, data visualization, statistical analysis, and machine learning.
Yes, After completing the course, you will receive a certificate of completion, which you can add to your resume and LinkedIn profile to demonstrate your expertise in Data science using R.
The projects that students work on in the course will vary depending on the program. However, they may include data analysis and visualization, statistical modeling, and machine learning projects. These projects may be based on real-world datasets and provide practical experience in applying data science concepts and techniques.
The availability of course materials after completion may vary depending on the program. However, some programs may offer ongoing access to course materials, including lectures, exercises, and projects.
By taking the Data Science with R course, students will gain a solid understanding of data science concepts and techniques, with a specific focus on the R programming language. They will learn how to manipulate and visualize data, perform statistical analysis, and build predictive models. Additionally, students will have access to personalized support and guidance from expert instructors.
