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Certificate Course on Business Analytics using R

Build an Analytics Career with R Programming and Advanced Analytics & Visualisation Tools

Class Room Training on Business Analytics using R software

Business analytics (BA) is the skills, technologies, practices for continuous iterative exploration of an organization's data and investigation of past business performance, with an emphasis on statistical analysis. Business analytics is used by organizations which are making data-driven decisions.

This course addresses the demand for skilled Business Analytics resources using the widely used open source software R, for Data processing, Visualization and Business Analytics. This course also skills the learners through the tools Advanced Excel & VBA, SQL, Tableu and Qlikview

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Hands-On Classes
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Industry Data
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Domain Workspace
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Live Projects
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Study Material Shared
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Easy Learning Pedagogy
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Group Study
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Mock Interviews
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Resume Preparation

Course Highlights

The course duration of Business Analytics with R Programming Course at Study Analytics

160 Hrs of Classroom Training + 240 Hours Home Assignments and Projects

  • A man working with R, and Visualization tools to show that Assignments are given per topic with Business Analytics with R Programming course at Study AnalyticsAssignments: 200+ Micro Projects  
  • A computer screen with process and outcome to indicate that projects with real business scenarios are facilitaed along with Business Analytics with R Programming course at Study AnalyticsProjects: 5 projects
  • Multiple Domains Across the globe to indicate that workshops from multiple domains are conducted along with Business Analytics with R Programming course at study analytcisDomains: Multiple- Retail, Online, Sales
  • A man standing with process cycle on R and Visualization Tools to indicate that internships are provided with Business Analytics with R Programming Course at Study Analytics100% practice based
  • A man walking out of a door succesfully to indicate that placement support is provided with Business Analytics with R Programming course at Study AnalyticsInternships for freshers
  • A spanner and screw driver image to show that the teaching methodology at Study Analytics for Business Analytics with R Programming Course is practice basedPlacements : 100% of Alumni Are Well Placed Upon Successful Course Completion

What do you get?

  • A Thorough Understanding About Data Analysis Using R Software in Real Business
  • Live Projects to refine the subject taught (Be experienced)
  • The best practices to build an effective Business dashboard
  • Most Relevant and Latest Methods in Data Analytics and the Best Practiced R Programming Techniques.
  • In-Class Assignments (Learn while practicing)
Two fresh graduates new to Analytics standing hand in hand to indicate the prerequisites for taking up Business Analytics with R Programming course at Study Analytics

Prerequisites

Any candidate who wish to work with R Software for Data Analysis can take up this course. Candidates with a Graduation degree (or higher) with quantitative subjects, have good communication skills and a high flair to Mathematics, Statistics and IT may join this program

Two fresh graduates new to Analytics standing hand in hand to indicate the prerequisites for taking up Business Analytics with R Programming course at Study Analytics

Course Outcome

On successful completion of the training, the candidates will gain the skills to work with R software, Access the data, clean and validate, consolidate, transform the data, analyse scenarios and apply Business Statistics on them, create reports to make insightful decisions.

Course Modules

Data Visualization and MIS Reporting : 110 hours
  • Basic Excel Training
  • Advanced Excel Course
  • Advanced Business Dashboards Training
  • VBA and Automation Hands On Classes
  • Projects
  • Business Analysis
  • Use Case designs
  • RDBMS Concepts in Business
  • Data processing
  • Data Analysis
  • Reporting Using MySQL
  • Introduction to QlikView
  • Data Sources
  • Data Modelling
  • Designing Advanced Business Dash Boards
  • Building Dashboards
  • Security
  • Projects
Module 2 Sub Heading
  • Getting Started in Tableau
  • Data Sources
  • Data Visualizations
  • Dimensions & Measures
  • Graphs and Charts
  • Filtering and Sorting Your Data
  • Organizing Data
  • Using Groups
  • Working with Dates
  • Creating Dashboard
  • Calculations and Statistics
  • Formatting
  • Advance Chart Types
  • Creating Story Telling Business Dashboards
Data Analysis Using R Software : 50 hours
Module 2 Sub Heading
  • Basics of R Software
  • Operations
  • R Programming
  • Exploratory data Analysis
  • Functions
  • Basic Statistics
  • Graphical Plots
  • Inferential Statistics
  • Statistical Tests
  • Linear Regression
  • Logistic Regression
  • Predictive Modeling
  • Candidates do multiple projects across domains

Hear from Our Students

Soumya Siddharth Rout
JMR Infotech

Trainers at Study Analytics are very friendly and very knowledgeable which gave me immense confidence to go ahead and build a career in analytics.

Shivani More
WNS Global Services

The program at Study Analytics was very crisp and covered many significant parts of excel which is very useful. The teaching methodology was very clear and effective. All the doubts were clarified. And also the way everything was taught, it stays in memory.
Ravikanth M V
NetApp
Study analytics teaches professionally. I think the DNA of Study Analytics is thinking like an analyst while studying. This place gives a wide scope of the current situation of analytics relating to business examples. Study analytics gave me an opportunity to understand the broad range of analytics field.

Aashish NP
True Influence

Best training ever happened to me my career at Study Analytics. I thank the faculty for their valuable guidance and support.

Swastik Roy
Andaman Diaries

It was a splendid experience altogether, as I got to know in and out of analytics. The study material is most helpful and gives you the framework to crack the certification exam. The real-time industry experience from trainers was a boost as they provided us with a pragmatic approach towards analytics, specifically retail and marketing analytics; which is highly appreciable.

Fassil F.
Meredith India Services Private Limited

Very informative, got many insights into Analytics in Banking. As the title suggests recommend more follow up. Sessions to cover to entire scope of Analytics in Banking. Thank you Study Analytics.

Shashank. BM
University of Bath School of Management

Study Analytics is the stepping stone of my career. Study Analytics help me started on my dream career. The provided the right training, with right domain knowledge & support. Kudos to Soni and his team!

Shreyas Chandra
Hewlett Packard Enterprise

Study Analytics has provided me a path for a bright future. The teaching here is good. Study Analytics training provides more examples and scenarios to explain the topics.
Let our experts help you customize the course for your profile

FAQ

R has packages covering a wide range of topics such as econometrics, finance, and time series. R has best-in-class tools for visualization, reporting, and interactivity, which are important to businesses. Because of this, R is well-suited for scientists, engineers and Business Analytics professionals.
R was designed to be used as a statistical tool. R has hundreds of packages, deployment and visualization tools. One needs to get an overall idea about how these packages work. A good Business Analyst is one who has a balanced knowledge of communication, statistics, programming and business.
Learning R Programming doesn't need any prior background or requisites. But, knowing basics of probability and statistics would be very helpful; so that the learner can cruise through the introductory math operations a bit faster.
Tableau enable the user to develop dashboards instantly with an intuitive interface and provides great visual freedom that differentiates itself from other players in the market. QlikView, on the other hand, is capable of dealing with varied datasets and provides much better performance. It can efficiently deal with big data and traditional data and it is apt in making interconnections between varied datasets like these effectively.

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