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Business Analytics With R Training

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  • Classes for Beginners and Advanced Students.
  • With R, you can learn how to do business analytics by doing it yourself.
  • Interview Preparation Techniques in Business Analytics With R: Best Practices
  • Student Portal, Study Materials, Videos, and Top MNC Interview Questions are all Available for a lifetime.
  • Fees are reasonable, and the program is created by an R expert.
  • Presented by a Business Analytics With R Certified Expert with more than 12 years of Experience.
  • 13492+ Students Trained & 370+ Clients Recruited
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Obtain Our Business Analytics With R Training Certification

  • Our Business Analytics with R Training course strives to provide high-quality training that combines sound underlying knowledge with a practical approach to core concepts.
  • The instructor will provide business analytics using the R certification guide, sample questions, and practice questions.
  • The program will provide you with hands-on experience with RStudio, an integrated development environment (IDE) that comes with a number of built-in tools that make coding with R easier.
  • R for Business Intelligence The goal of this training course is to assist students to comprehend real-world knowledge and become Business Analytics experts.
  • R is providing the excellent capability to the analytics professionals' open source programming environment.
  • Our Business Analytics with R course covers everything you'll need to know to pass the Business Analytics with R exam.
  • Concepts: Introduction to Schema, Changing Datatypes Of Elements In Schema, Validating Maps (Schema), Debugging & Exceptions, Flat Files, Power shell Scripting.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
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Course Objectives

R Programming Language, often known as Business Analytics With R, is an open-source programming language and software environment created by and for statisticians. It's primarily utilized for statistical calculations and high-resolution visuals. As a result, it is a popular language for data analysis among mathematicians, statisticians, data miners, and scientists.
Business Analytics R programming is a powerful enterprise-oriented programming language with the following distinguishing characteristics:
  • Business Analytics R programming is a free and open-source programming language.
  • Business Analytics R programming was created with data analysis in mind.
  • Business Analytics R programming is an object-oriented programming language.
  • Business Analytics R programming is a computer language that is interpreted.
  • The Business Analytics R programming language generates high-end images.
  • Advanced Analytics with Business Analytics with R programming.
  • >Business Analytics R programming has a close-knit community for the business analytics community.
Business Analytics with R Training is a completely programmable computer language that: Efficiently stores and processes data utilizing a set of arithmetic and textual operators for array and matrix calculations. It consists of data analysis tools. It was provided with graphical services to give data analysis that is both understandable and instructive. It Contains no-nonsense programming approaches such as well-defined functions, loops, conditionals, and input-output capabilities. It Contains a LaTeX-like documentation format that delivers a wide range of documentation in both hardcopy and softcopy formats. As a result, R is easily expandable via functions and extensions, allowing developers to extend its capabilities.
The Business Analytics with R Training programming language is riddled with myths. To be clear, R is not a database, even though the R programming language may readily link to a database management system (DBMS). Though it can call its C/C++ code, R's Language interpreter can be slow at times. Business Analytics R programming does not have a graphical user interface, however, it is compatible with Java and Tcl/TK. Although it is easy to connect to Excel/MS Office, the Business Analytics with R Training language does not provide a spreadsheet view of data.
It depends on your skill level, but it's still a difficult task. You can begin by running simple programs like a file open/close, directory change, and so on. However, writing real software may take longer. However, if you devote 6 month to learning the fundamentals of R and put forth a genuine effort, you will be quite proficient in the language.
    Statistical Analysis in Business Analytics with R Online Training is a book that teaches you how to do statistical analysis in Business Analytics R programming. Certification in Data Science. Professional Certificate in IBM Data Analytics with Excel and R. Business Analytics R programming Nanodegree Programming for Data Science.
    It's entirely plausible. Business Analytics with R online Training is a very simple way to learn a high-level interpreted language. There are high-quality Business Analytics with R online courses available in our ACTE, the most well-known of which being freshers, where you may enroll for free, learn at your own pace, practice and comprehend R, and receive a certificate of completion!

What is the best way for a fresher to learn Business Analytics with R Training?

  • Install the RStudio and Business Analytics with R Training packages.
  • A Gentle Introduction to Tidy Statistics in Business Analytics with R Training will take you an hour.
  • Use RStudio to begin coding.
  • Use R Markdown to publish your work.
  • Learn about some useful development tools.

Is Business Analytics with R appropriate for business analysts?

As a result, Business Analytics with R refocuses analysis on the analysts rather than the tools. Analysts with R language abilities can also become heroes within their analytical departments by assisting in the reduction of their department's annual budget costs.

What are the different types of tools used to analyse the data in Business Analytics with R training?

The language was created to aid in the analysis of data. It includes a number of methods for retrieving, analysing, and interpreting data, as well as high-quality visuals. It includes statistical approaches such as
  • Median Distributions
  • Covariance Regression
  • Non-linear Mixed-Effects
  • GLM
  • GAM, and many others.

What is the importance of using Business Analytics with R training?

    Another excellent feature of this language is that it is object-oriented. As a result, the language excels in creating comprehensive object-oriented programs. It's also a language that lets you perform some amazing branching and looping, as well as modular programming.

How Business Analytics with R programming differs from other programming languages?

    The benefit of utilizing R for business analytics is that it is a language that allows you to produce some stunning visuals. It also has advanced analytics, which is a huge plus. Its packages, such as CRAN and Task Views, are also useful.
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Overview of Business Analytics with R Training

Our Business Analytics with R Course prepares you for difficult multi-faceted projects and boosts your job possibility by certifying data analysis. Our academy also offers online Data Analytics tutoring for people who cannot attend the classroom instruction at a reasonable rate. We have branch experts with a lot of trainer experience. R-Business Analytics: Experience the real-time realization of R-programming business analytics, knowledge of different sub-setting methods in R, Analytics R, the functionality of R-Business for data inspection, Spatial Analysis introduction into R, R-Business Tree classification rules, advanced analytics, and data analysis, etc.

In several vertical areas, you will also be exposed to industrially based ETP projects. Our Business Analytics with R Course course strives to give quality training, which provides a practical approach to strong foundational knowledge of key ideas. This exposure to existing applications and scenarios in the sector will assist students to expand their skills and do projects in real-time with best practices.

Additional Info

Course Overview :

The Business Analytics with R Institute provides courses on R programming, R for the analysis, R classification rules for decision trees, as well as a practical implementation of business analytics with R. Learn the various sub-setting methods of R, R for the analysis, and functions used in R for data inspection. As part of this program, you will also work on Real-time projects across various industries.

Intro Of R Analytics :

This Business Analytics with R Online Course open-source programming language and software environment known as Business Analytics With R is a programming language and environment developed by statisticians and for statisticians. Statistical computations and advanced graphics are primarily carried out using it. Hence, it is a popular language for applied mathematicians, statisticians, data analysts, and also for scientists to analyze data. Statistical computing or graphics is performed using R programming language, an open-source programming language. Data mining and statistical analysis often use this programming language. By identifying patterns and building practical models, it can serve as an analytics tool. Additionally, R can be used to develop software applications that analyze data and perform statistical analysis, such as the creation of data analysis software. R offers a graphical user interface that can be used to develop programs, including classical statistical tests, cluster analysis and other time-series analysis techniques, as well as linear and nonlinear modeling methods. There are four windows on the interface: a script window, console window, workspace and history window, and tabs for different areas (help, packages, plots, and files). Plots and graphics can be written in R for publication and analytics can be stored for future use.

Throughout the years, R has grown in popularity, and it is one of the most popular analytics languages for colleges and universities. Academics and corporations throughout the world have accounted for its reliability, accuracy, and robustness. In recent years, the user interface of R has become more user-friendly, which was initially seen as a barrier to non-statisticians learning this programming language. The application now supports extensions and other plugins like R Studio and R Excel, which assists new users in learning it more quickly and effectively. As more graduates enter the workforce as R-trained analysts, it is expected to become the industry standard for statistical analysis and data mining projects.

R Analytics: Why Should You Get Started?

A strong community of R users makes it possible to find sample codes for a variety of data analysis projects using this open source coding language. You can also experiment with these tools for free if your company wants to start using analytics. R is used for demonstrating the benefits of further investment by management by testing new analytics projects or Proof of Concepts. The countless R forums and tutorials available for learning the language help analysts use R in their own work. The languages are used by over two million people.

What can I use R analytics for?

1. Today, R is being used in multiple industries and fields, across a range of different sectors. Data collection, clustering, and analytics models are some of the ways R is used in business analytics.

2. Rather than using a ready-made approach, R data analysis allows companies to create their own statistics engines that provide better, more accurate insights, because data is collected and stored more precisely.

3. Furthermore, using R instead of boxed software makes it possible for companies to create ways to test for errors in analytical models while reusing existing queries and conducting ad-hoc analyses. Using R and its sister language, Python, as part of your analytics stack is essential if you want to maximize data value. The integration of these technologies can make them as easy to use as SQL.

4. Academics and more research-oriented areas often require highly specific and unique modeling methods, so R has proven invaluable in these fields.

5. With this flexibility, organizations can now rapidly design custom analytical programs that can integrate with existing statistical analyses while providing insight into much deeper and richer data sets.

6. The Business Analytics with R online Course can provide models that can typically deliver better or more specific insights when it comes to social media data or web data, even when standard measures like page views or bounce rates are used.

R Analytics: What are the benefits?

Business data can be analyzed more efficiently using R's business analytics. Companies that use R in their analytics programs achieve some of the following benefits:

Organizational Democratization of Analytics :

Using interactive data visualization and reporting tools, R enables business users to gain insight into their data. In order for business users and citizen data scientists to make better business decisions, R can be used for data science by nondata scientists. Additionally, R analytics allows data scientists to concentrate their efforts on more complex data science initiatives, reducing the amount of time they devote to data preparation and data wrangling.

Insights that are more Deep and Precise :

Nowadays, the majority of successful companies rely on data and data analytics affects virtually every aspect of their operation. Despite the fact that R is a powerful language for creating models to analyze large amounts of data, there are a lot of powerful data analysis tools that are available. Using R analytics, companies are able to collect and store data more accurately, which provides them with more valuable insight to users. Business insights are gained more accurately and more deeply with the use of analytics and statistical engines using R. R is capable of producing detailed analyses of very specific data.

Utilizing big data :

Big data can be queried with R, and many industry leaders are leveraging big data across their businesses with this tool. R analytics enables organizations to discover new insights for their data sets and give their information a coherent context. As easy as, or perhaps easier than, most other analysis tools available today, R uses big datasets to handle these big data sets.

Visualizing Interactive Data :

As another benefit, Business Analytics with R online Course allows you to create graphs and diagrams to aid in creating data visualizations and data exploration. Visualizations, 3D charts, and graphs are among the features that help users communicate with each other.

The best way to implement R analytics?

Originally designed for statisticians, R programming is now used to perform a variety of tasks, including modeling data, predictive analytics, and data mining. R provides a platform where businesses can create custom models for data collection, clustering, and analysis. The use of R analytics for business intelligence can provide a valuable way to rapidly build models that target specific areas of the business and provide tailored insights tailored to meeting every day needs.

The following purposes can be achieved using R analytics :

  • Statistical analysis
  • Predictive analytics
  • Analytical prediction
  • Analyzing time series
  • Analyzing what-if scenarios
  • Models of regression
  • Exploration of data
  • The forecasting process
  • Searching for text
  • Mining data
  • Analyzing visual data
  • Analytics on the web
  • Analyzing social media
  • Analyzing sentiment
  • By Turbocharging an organization's analytics program, R can be used to solve real-world business problems. An analytics platform can integrate this tool into a business's system to help users maximize data usage. You can apply statistical models to your analysis using R by applying its extensive library of functions and advanced statistical techniques. Among its advantages are that it enables businesses to identify opportunities and risks, predict business outcomes, and build interactive dashboards for an overview of the data. A better understanding of this can allow businesses to make better decisions and increase revenue.

Skills of Business Analytics with R :

Ability :

Professionals are struggling to keep up with the huge changes to the big data landscape, which makes it tough to know where to concentrate their efforts. Despite the rapidly evolving nature of the business analytics discipline, there are certain core competencies that are essential for a solid career in this field.

Business analysts should have the following characteristics :

  • Communication Skills are Important :

    Making sure that all stakeholders understand insights and can implement recommendations requires the ability to present findings in a clear and concise manner. Writing and presenting data can be powerful tools for people who work in analysis.

  • Inquisitive :

    This field requires individuals with a natural curiosity and a desire to keep learning and understanding how things function. It is important to keep up-to-date on changes in the industry, even as analysts become managers.

  • The ability to solve problems :

    Using logical thinking, predictive analytics, and statistics, analysts make recommendations for solving problems and propelling companies forward. An ability to solve problems naturally is crucial for a profession that strives to turn data into answers.

  • Critical thinking :

    It is crucial that business analytics professionals consider not only what data they collect, but about what data they should collect in the first place. In order to make good decisions, they are expected to analyze and highlight only the most relevant data.

  • Using a Visualizer :

    Data that is disorganized won't help anyone. An analytics professional must be able to translate and visualize data in a concise and accurate way that's easy to digest in order to create value from it.

  • A detail-oriented thinker as well as a big picture thinker
  • As much as business analytics professionals need to understand complex data, they must also ensure that their recommendations will have a positive impact on the bottom line of a company. If you don't know how to leverage large quantities of information for analyzing and improving strategies, tactics and processes, having access to data is pointless.

The Technical Skills Necessary for Business Analytics :

Analytics professionals are responsible for fulfilling the demand for technical expertise in a business environment that rapidly becomes dominated by big data by wearing both analyst and developer hats. To translate data into tangible solutions, it is important to both understand tools and programming languages conceptually and practically.

Business analytics professionals should be aware of these top tools :

1. SQL :

An analytics professional's toolkit should contain the language SQL, which codes databases. SQL queries are written by professionals to retrieve and analyze data from transaction databases and to create visualizations for stakeholders to see.

2. Languages of Statistical Analysis :

R, which is used for statistical analysis, and Python, which is used in general programming, are the two most commonly used languages in analytics. Although big data sets are analyzed using either of these languages, expert knowledge in either is not necessary.

3. Software for Statistical Analysis :

A career in analytics is sometimes suited to those who are able to program. However, expertise in writing code is not necessary. For managing and analyzing data, you can utilize statistical software such as SPSS, SAS, Sage, Mathematica, and even Excel.

Benefits of Learning :

  • Use analytics tools, such as R and advanced Excel, to explore, analyze, and solve business problems

  • Learn how to collect data and the 'what' and 'how'

  • Discover how to measure and analyze data using Industry Best Practices

  • Business Objectives will be communicated to data analysts in a focused manner & they will be able to formulate better conclusions from data analysis.

  • Develop business strategies that are goal-oriented

  • Integrate+integrate+analyse customer data from multiple sources and engage with customers in real time to gain an overall view of customers across multiple channels

  • Analyzing transactional data helps to determine the affinity of products.

  • Understanding analytically-based financial decision making will assist in bolstering your company's profit margins

  • Market share can be increased by taking actionable data-driven decisions

  • Predictive models can be adjusted to macro changes with this tool

Career Benefits :

  • Prepare yourself for jobs requiring a background in analytics
  • Opening doors to international job opportunities requiring specialized skills
  • Talent Shortage gives you access to thousands of untapped analytics jobs that pay well
  • You will be promoted within your current profile with the most highly sought-after skills
  • When interviewing for a job, separate your profile from those of your peers
  • The 'Certified Business Analytics Practitioner' (CBAP) certification is rewarding and a great career switch
  • Add your name next to the Hallmark of Global Credential-CBAP Professional to your business card
  • The best way to improve your CV and LinkedIn profile is to develop your skills
  • Provide high ROI support for startups
  • Become a leader in today's most exciting field, Analytics!

The Career Benefits of R Programming Training :

  • We offer our students a variety of career-related benefits. Students who go through this course often get better jobs as a result of their education. Other people started their own businesses as well, including consulting firms. We have a student who became so passionate about machine learning and statistics that he is now doing a Ph.D. in machine learning full time.

  • A candidate's aspirations determine how much he or she will gain from a career change. In fact, many of our students moved into data-science roles after taking this course, whether looking for a new job or even moving within their company. Freshers seeking career advancement who do not only wish to do web development, testing, or typical software engineering jobs may find this course to be a great difference maker in their career and life goals.

  • Therefore, we suggest to our students to not worry too much about benefits. Rather, learn all the concepts, learn the skill, become confident in coding and solving problems, and then you will certainly receive the benefit because you will be the one receiving it, not the third person. In fact, R programming is more relevant now than it has ever been, and we cover everything a student needs with extensive practice and real-world applications. This seventy-hour course covers everything a student needs.

At the End of the Training, You will Get :

You will learn all the topics required to pass the Business Analytics with R certification course in our Business Analytics with R course. Participants will receive a Business Analytics with R certification guide, Business Analytics with R certification practice questions, and Business Analytics with R certification sample questions.

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Key Features

ACTE offers Business Analytics With R Training in more than 27+ branches with expert trainers. Here are the key features,

  • 40 Hours Course Duration
  • 100% Job Oriented Training
  • Industry Expert Faculties
  • Free Demo Class Available
  • Completed 500+ Batches
  • Certification Guidance

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Singapore.


Syllabus of Business Analytics With R Training
Module 1: Data Science Project Lifecycle
  • Recap of Demo
  • Introduction to Types of Analytics
  • Project life cycle
  • An introduction to our E learning platform
Module 2: Introduction To Basic Statistics Using R And Python
  • Data Types
  • Measure Of central tendency
  • Measures of Dispersion
  • Graphical Techniques
  • Skewness & Kurtosis
  • Box Plot
  • R
  • R Studio
  • Descriptive Stats in R
  • Python (Installation and basic commands) and Libraries
  • Jupyter note book
  • Set up Github
  • Descriptive Stats in Python
  • Pandas and Matplotlib / Seaborn
Module 3: Probability And Hypothesis Testing
  • Random Variable
  • Probability
  • Probility Distribution
  • Normal Distribution
  • SND
  • Expected Value
  • Sampling Funnel
  • Sampling Variation
  • CLT
  • Confidence interval
  • Assignments Session-1 (1 hr)
  • Introduction to Hypothesis Testing
  • Hypothesis Testing with examples
  • 2 proportion test
  • 2 sample t test
  • Anova and Chisquare case studies
Module 4: Exploratory Data Analysis -1
  • Visualization
  • Data Cleaning
  • Imputation Techniques
  • Scatter Plot
  • Correlation analysis
  • Transformations
  • Normalization and Standardization
Module 5: Linear Regression
  • Principles of Regression
  • Introduction to Simple Linear Regression
  • Multiple Linear Regression
Module 6: Logistic Regression
  • Multiple Logistic Regression
  • Confusion matrix
  • False Positive, False Negative
  • True Positive, True Negative
  • Sensitivity, Recall, Specificity, F1 score
  • Receiver operating characteristics curve (ROC curve)
Module 7: Deployment
  • R shiny
  • Streamlit
Module 8: Data Mining Unsupervised Clustering
  • Supervised vs Unsupervised learning
  • Data Mining Process
  • Hierarchical Clustering / Agglomerative Clustering
  • Measure of distance
  • Numeric - Euclidean, Manhattan, Mahalanobis
  • Categorical - Binary Euclidean, Simple Matching Coefficient, Jaquard’s Coefficient
  • Mixed - Gower’s General Dissimilarity Coefficient
  • Types of Linkages
  • Single Linkage / Nearest Neighbour
  • Complete Linkage / Farthest Neighbour
  • Average Linkage
  • Centroid Linkage
  • Visualization of clustering algorithm using Dendrogram
Module 9: Dimension Reduction Techniques
  • PCA and tSNE
  • Why dimension reduction
  • Advantages of PCA
  • Calculation of PCA weights
  • 2D Visualization using Principal components
  • Basics of Matrix algebra
Module 10: Association Rules
  • What is Market Basket / Affinity Analysis
  • Measure of association
  • Support
  • Confidence
  • Lift Ratio
  • Apriori Algorithm
Module 11: Recommender System
  • User-based collaborative filtering
  • Measure of distance / similarity between users
  • Driver for recommendation
  • Computation reduction techniques
  • Search based methods / Item to item collaborative filtering
  • Vulnerability of recommender systems
Module 12: Introduction To Supervised Machine Learning
  • Workflow from data to deployment
  • Data nuances
  • Mindsets of modelling
Module 13: Decision Tree
  • Elements of Classification Tree - Root node, Child Node, Leaf Node, etc.
  • Greedy algorithm
  • Measure of Entropy
  • Attribute selection using Information Gain
  • Implementation of Decision tree using C5.0 and Sklearn libraries
Module 14: Exploratory Data Analysis - 2
  • Encoding Methods
  • OHE
  • Label Encoders
  • Outlier detection-Isolation Fores
  • Predictive power Score
Module 15: Feature Engineering
  • Recurcive Feature Elimination
  • PCA
Module 16: Model Validation Methods
  • Splitting data into train and test
  • Methods of cross validation
  • Accuracy methods
Module 17: Ensembled Techniques
  • Bagging
  • Boosting
  • Random Forest
  • XGBM
  • LGBM
Module 18: KNN And Support Vector Machines
  • Deciding the K value
  • Building a KNN model by splitting the data
  • Understanding the various generalization and regulation techniques to avoid overfitting and underfitting
  • Kernel tricks
Module 19: Regularization Techniques
  • Lasso Regression
  • Ridge Regression
Module 20: Neural Networks
  • Artificial Neural Network
  • Biological Neuron vs Artificial Neuron
  • ANN structure
  • Activation function
  • Network Topology
  • Classification Hyperplanes
  • Best fit “boundary”
  • Gradient Descent
  • Stochastic Gradient Descent Intro
  • Back Propogation
  • Intoduction to concepts of CNN
Module 21: Text Mining
  • Sources of data
  • Bag of words
  • Pre-processing, corpus Document-Term Matrix (DTM) and TDM
  • Word Clouds
  • Corpus level word clouds
  • Sentiment Analysis
  • Positive Word clouds
  • Negative word clouds
  • Unigram, Bigram, Trigram
  • Vector space Modelling
  • Word embedding
  • Document Similarity using Cosine similarity
Module 22: Natural Language Processing
  • Sentiment Extraction
  • Lexicons and Emotion Mining
Module 23: Naive Bayes
  • Probability – Recap
  • Bayes Rule
  • Naive Bayes Classifier
  • Text Classification using Naive Bayes
Module 24: Forecasting
  • Introduction to time series data
  • Steps of forecasting
  • Components of time series data
  • Scatter plot and Time Plot
  • Lag Plot
  • ACF - Auto-Correlation Function / Correlogram
  • Visualization principles
  • Naive forecast methods
  • Errors in forecast and its metrics
  • Model Based approaches
  • Linear Model
  • Exponential Model
  • Quadratic Model
  • Additive Seasonality
  • Multiplicative Seasonality
  • Model-Based approaches
  • AR (Auto-Regressive) model for errors
  • Random walk
  • ARMA (Auto-Regressive Moving Average), Order p and q
  • ARIMA (Auto-Regressive Integrated Moving Average), Order p, d and q
  • Data-driven approach to forecasting
  • Smoothing techniques
  • Moving Average
  • Simple Exponential Smoothing
  • Holts / Double Exponential Smoothing
  • Winters / HoltWinters
  • De-seasoning and de-trending
  • Forecasting using Python and R
Module 25: Survival Analysis
  • Concept with a business case
Module 26: End To End Project Description With Deployment
  • End to End project Description with deployment using R and Python
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Get Hands-on Knowledge about Real-Time Business Analytics With R Projects

Project 1
Uber Data Analysis

The Uber Analysis Project is a assignment in statistics visualization, wherein R and its libraries are used to research parameters or variables just like the journeys in the course of a day, or the month-to-month journeys in a year.

Project 2
Customer Segmentation

Customer Segmentation is one of the maximum essential R assignment topics. Whenever groups want to become aware of and goal the maximum capability patron base, the Customer Segmentation technique is available in handy.

Project 3
Movie Recommendation System

A Recommendation System may be constructed in R the use of the “MovieLens Dataset” and the packages – “ggplot2”, “encouraged lab”, ”statistics. table”, and “reshape2”.

Project 4
Sentiment Analysis

Sentiment evaluation is the manner of reading phrases to check evaluations and sentiments which have distinct polarities – positive, negative, or neutral.

Our Best Hiring Partner for Placements

ACTE offers placement opportunities as an add-on to all students/professionals who have taken classrooms or online education. Some of our students work for the following companies.
  • Among our clients is IBM India Pvt. Limited, Wipro, Novartis Healthcare Pvt. Ltd., VMware, Google, CTS, TCS, IBM, and others. It allows us to place our students in leading global organizations all around the world.
  • We have separate student placement webpages where you can access all of the interview schedules and receive email notifications.
  • Upon completion of 70% of Business Analytics With R training course content, prepare students for interview calls and prepare for F2F interactions.
  • We have a professional placement support team to help ensure placement according to student needs.
  • The emphasis is entirely on placing students in firms where they will fit in intellectually and culturally.
  • Trainers in Business Analytics with R aid students in constructing a resume that is relevant to current industry needs.

Get Certified By Business Analytics With R & Industry Recognized ACTE Certificate

Acte Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher's as well as corporate trainees.

Our certification at Acte is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC's of the world. The certification is only provided after successful completion of our training and practical based projects.

Complete Your Course

a downloadable Certificate in PDF format, immediately available to you when you complete your Course

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a physical version of your officially branded and security-marked Certificate.

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About Satisfactory Business Analytics With R Training Mentors

  • Our Business Analytics With R Training Tutors are certified professionals with 9+ years of experience in their respective domains as well as they are currently working with Top MNCs.
  • Since all trainers are experts in the operation of the Business Analytics R domain, there are many live projects, so trainers will use these projects during their training sessions.
  • All our Trainers are working with companies such as IBM India Pvt. Limited, Wipro, Novartis Healthcare Pvt. Ltd., HCL Technologies, etc.
  • Our trainers also assist candidates in being placed in the company through an employee nomination / internal employment process.
  • Our training program is designed to provide students from all disciplines with instruction in a variety of technologies, depending on their area of interest.
  • We have received various prestigious awards for Business Analytics With R Training from recognized IT organizations.

Business Analytics With R Course Reviews

Our ACTE Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of ACTE & Video Reviews.



I underwent Business Analytics With R training in ACTE, Porur. The training session was good. My tutor Mr.Anbu have been outstanding. I liked the sessions taught by him who is an experienced faculty. Each and every topic is explained very clearly. Materials provided by him were useful. He is really good with his training and has the best content with him for the training which is really useful for a fresher like me to learn.

Dinesh Karthik


Good Institute for getting your basics right in any course, Thanks to Prabhu sir for training me for Business Analytics With R has around 10+ years of experience in Business Analytics With R and covers all the real time scenario's in the classes



I have enrolled for Business Analytics With R course in ACTE, Chennai It is a very nice experience. Trainer is very good and talented. All the concepts are thoroughly explained by the time you don't understand. Facilities are good. There is the provision of paying fees in instalment. Hence overall it's nice to choose



It was a great learning experience in ACTE, Banglore. The entire course structure designed for its students, the teaching methodology, as well as placement assistance, is really good. ACTE helped me a lot to get my first job. Had a wonderful opportunity to learn under the guidance of dedicated faculty team headed and gain knowledge in the field of Business Analytics With R . I would recommend ACTE to people who are interested to learn Business Analytics With R .



Very motivational environment. Best way to teach. Really appreciate the efforts they put from there side to increase the knowledge and development of students. Thanks, ACTE

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  • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
  • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
  • More than 3500+ students placed in last year in India & Globally
  • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
    ACTE Gives Certificate For Completing A Course
  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Business Analytics With R training has been built around Real Time Implementation
  • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
  • GitHub repository and Showcase to Recruiters in Interviews & Get Placed
All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

Why Should I Learn Business Analytics With R Course At ACTE?

  • Business Analytics With R Course in ACTE is designed & conducted by Business Analytics With R experts with 10+ years of experience in the Business Analytics With R domain
  • Only institution in India with the right blend of theory & practical sessions
  • In-depth Course coverage for 60+ Hours
  • More than 50,000+ students trust ACTE
  • Affordable fees keeping students and IT working professionals in mind
  • Course timings designed to suit working professionals and students
  • Interview tips and training
  • Resume building support
  • Real-time projects and case studies
Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.
You will receive ACTE globally recognized course completion certification Along with National Institute of Education (NIE), Singapore.
We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.
We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Business Analytics With R batch to 5 or 6 members
Our courseware is designed to give a hands-on approach to the students in Business Analytics With R . The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
You can contact our support number at +91 93800 99996 / Directly can do by's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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