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  • Comprehensive understanding of basic and advanced concepts, techniques and applications of R in business scenarios.
  • Easy to use, reusable and flexible code sharing features extensive graphical representation and dashboarding capabilities,
  • Powerful range of statistical techniques with business applications of machine learning algorithms
  • Versatility to perform analytics in several fields such as academia, engineering, business, finance and Insurance
  • Knowledge exchange & experiences sharing with – over 2 million users and 1200 libraries available
  • Experience sharing by industry experts form different business sectors 
  • Important skills for Fresher’s and working professionals to enhance their careers
  • Membership to KJA–KAALP Job Assistance program

70hrs

E-learning

Practice Datasets

& Case Studies

40+

Quizzes

Learn Anywhere

Anytime

Industry

Relevant

Webinars by

Industry Experts

Certification

by Kaalp

70hrs E – learning

Practice Datasets & Case Studies

40+ Quizzes

Learn Anywhere Anytime

Industry Relevant

Webinars by Industry Experts

Certification by Kaalp

R is one of the most leading and effective programming languages used for data analysis and statistical modelling. This R training course provides you in depth learning in understanding concepts of data analytics as well as application of R language in data manipulation, calculation and graphical display. In addition this course covers statistical functions and techniques and machine learning which will enable you to learn how to user R features such as random forest and decision trees for applications to learn from data and arrive at decisions with minimal human intervention. This course offers an overview and practical knowledge of how industry experts use R for finding solutions to real life business challenges. Our learning management portal has comprehensive study material along with practice data sets and case studies to enhance your learning. The Online quiz-bank will help you to self-assess your comprehension as you progress through the course.
Machine Learning (ML) is a method of data analysis that automates analytical model building.It is a branch of artificial intelligence,based on the idea that systems can learn from data,identify patterns and make decisions with minimal human intervention
Advantages of Machine Learning
  • ML is useful when large volume of data is available.
  • Machine learning is used to handle multi-dimensional and multiple types of data in dynamic environments.
  • Social media is using machine learning to push relevant advertisements.These advertisements are based on users past search behaviour.
Students from B.Sc, B.Com, BBA, Engineering and MBA disciplines who are looking for better employment opportunities. ​
Research scholars, academicians and scientists who wish use R for quantitative analysis and research projects. ​
Corporate professionals who wish to learn business analytics or pursue careers in data science. ​
Software and ITES professionals who wish to use R for data analysis and statistical modelling with advanced visualization and machine learning techniques. ​
  • Installing & configuring R & setting up environment for analysis
  • Using the R Programmable Environment and Command Line scripting
  • Mastering various techniques like Assign variables, analyze vectors, matrices, factors, Lists & Data frames , Functions to name a few
  • Basic and advanced statistical functions like, Testing of Hypothesis, Control Charts, Cluster Analysis, Regression Analysis
  • The course covers extensively advanced statistical concepts including regression, forecasting & clustering techniques.
  • Machine learning Techniques such as - Random Forests, Decision Trees, Artificial Neural Networks, Support Vector Machines, K-Nearest Neighbor , Ensemble, Gradient Boosting
Elementary knowledge of mathematics or statistics and basic programming skills will be an added advantage to those who attend this course. Exposure to SQL commands or Excel capabilities will be of added advantage.

Description

R is one of the most leading and effective programming languages used for data analysis and statistical modelling. This R training course provides you in depth learning in understanding concepts of data analytics as well as application of R language in data manipulation, calculation and graphical display. In addition this course covers statistical functions and techniques and machine learning which will enable you to learn how to user R features such as random forest and decision trees for applications to learn from data and arrive at decisions with minimal human intervention.

 

This course offers an overview and practical knowledge of how industry experts use R for finding solutions to real life business challenges. Our learning management portal has comprehensive study material along with practice data sets and case studies to enhance your learning. The Online quiz-bank will help you to self-assess your comprehension as you progress through the course.

Machine Learning (ML) is a method of data analysis that automates analytical model building.It is a branch of artificial intelligence,based on the idea that systems can learn from data,identify patterns and make decisions with minimal human intervention
Advantages of Machine Learning
  • ML is useful when large volume of data is available.
  • Machine learning is used to handle multi-dimensional and multiple types of data in dynamic environments.
  • Social media is using machine learning to push relevant advertisements.These advertisements are based on users past search behaviour.

Who Should Attend?

Students from B.Sc, B.Com, BBA, Engineering and MBA disciplines who are looking for better employment opportunities. ​

Research scholars, academicians and scientists who wish use R for quantitative analysis and research projects. ​

Corporate professionals who wish to learn business analytics or pursue careers in data science. ​

Software and ITES professionals who wish to use R for data analysis and statistical modelling with advanced visualization and machine learning techniques. ​

WHAT YOU WILL LEARN

  • Installing & configuring R & setting up environment for analysis
  • Using the R Programmable Environment and Command Line scripting
  • Mastering various techniques like Assign variables, analyze vectors, matrices, factors, Lists & Data frames , Functions to name a few
  • Basic and advanced statistical functions like, Testing of Hypothesis, Control Charts, Cluster Analysis, Regression Analysis
  • The course covers extensively advanced statistical concepts including regression, forecasting & clustering techniques.
  • Machine learning Techniques such as - Random Forests, Decision Trees, Artificial Neural Networks, Support Vector Machines, K-Nearest Neighbor , Ensemble, Gradient Boosting

PREREQUISITES

Elementary knowledge of mathematics or statistics and basic programming skills will be an added advantage to those who attend this course. Exposure to SQL commands or Excel capabilities will be of added advantage.

Curriculum

Get an overview of OOPS concepts through R programming
  • R Environment
  • Using R Interactively
  • R commands, case sensitive etc.
Learn how to use operations applicable to simple manipulations; numbers & vectors.
  • Vectors & Assignment
  • Vector Arithmetic
  • Generating regular sequences
  • Logical vectors & Index vectors
  • Missing values
  • Character values
  • Array indexing
  • Index matrices
  • Forming partitioned matrices
  • Frequency tables from factors
  • The concatenation function with arrays
Learn how to use Lists & Data Frames
  • Constructing & modifying Lists
  • Working with data frames
  • Managing search path

Know how Open database connectivity is used in R

Reading data from files & different sources

The chapter gives an overview of introduction various theoretical distribution of data
  • Checking normality/Normal distribution
  • Frequency distributions & Contingency Tables
  • Binning
  • Binomial distributions
  • IQR & Empirical rule for symmetric distributions
  • Probability distributions
  • Proportion tables & Confidence Interval
This chapter covers various parametric tests used in statistics to validate Hypothesis
  • T-test
  • F-test
  • Sampling distributions
  • Chi-Square
  • ANOVA
  • Correlation
The below topics describes various visualization techniques to show the relationship of the variables 
  • Bar-plot
  • Pie chart
  • Stacked Bar chart
  • Histogram
  • Line chart
The below mentioned  topics cover unsupervised machine learning techniques
  • Cluster Analysis
  • Principal Component Analysis
  • Factor Analysis
Learn how to use supervised machine learning algorithms Regression Analysis
  • Simple Linear Regression
  • Multiple Linear Regression
  • Logistic Regression
Learn how to build robust machine learning models when data is non linear
  • Random Forests
  • Decision Trees
  • Support Vector Machines
  • K-Nearest Neighbor
  • Ensemble
  • Gradient Boosting
Regularization
This topic introduces to the backbone of artificial intelligence including  architecture of Neural networks
  • Artificial Neural Networks
In this chapter learn easy to use interactive web based dashboards with R
  • R-Shiny

Preview

Level 1

Level 2

Testimonials

I completed the Introduction to Business Analytics training course conducted by Kaalp Consulting. The course material was easy to understand and I got hands on experience to practice the software commands. The instructors had good knowledge and gave us practical tips on application of analytics in problem solving. I was very satisfied with the training course.
BBA Student, Bangalore
Kaalp Consulting conducted a training program in R Programming for our institute. The course material is very extensive and well designed. The instructors were working professionals who have good experience in using R in business analytics. They explained the topics extremely well and gave us a good practical understanding on how R is used in real life scenarios. We very satisfied with the course and highly recommend it to others.
Lecturer and Trainer, TN.
Kaalp Consulting conducted a course on Introduction to Business Analytics with SQL, Excel and Tableau for our B.Com and BBA students. We were very pleased with the manner in which the courses were presented by their instructors who are industry professionals. The instructors explained the topics very well and shared their practical experience on how the business analytics is applied in real life. The course content is well designed and the program was managed very professionally by Kaalp Consulting. We have no hesitation in recommending them to any institution or individual who are interested in joining their training courses.
Dr. Geethu, KJC, Bangalore

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