Data Analysis, Mining and Modelling using R Training & Certification

  • Course Duration35 Hrs.
  • Course ModeInstructor Led Training
  • Course Fee₹ 6800

About The Course

AICouncil creates training and development program with maximum focus over hands 0n learning experiences. This training will lead to in depth knowledge of R programming and its use cases in Data Science domain. You will develop experience over inbuilt functions and libraries of R and understand its robustness, flexibility and ease of coding. The techniques such as clustering, time-series analyses and classification techniques, nonlinear/linear modelling and classical statistical tests will be used in different data science computations. The course will cover data exploration, data visualization, predictive analytics, and descriptive analytics techniques with the R language. You will learn about R packages, how to import and export data in R, data structures in R, various statistical concepts, cluster analysis, and forecasting.

Key Features

Instructor–led training

Highly interactive instructor-led training

Free lifetime access to recorded classes

Get lifetime access of all recored classes in your profile

Regular assignment and assessments

Real-time projects after every module

Lifetime accessibility

Lifetime access and free upgrade to the latest version

3 Years of technical support

Lifetime 24/7 technical support and query resolution

Globally Recognized Certification

Get global industry-recognized certifications


  • Various analysis and visualization tools such as Ggplot and plotly
  • Build significant models to understand Statistics Fundamentals after knowing behaviour of Data
  • Will know about the various R libraries like Dplyr, Data.table etc.
  • Data manipulation, data preparation and data explorations
  • How to use R graphics libraries like Ggvis, Plotly etc.
  • Advanced Statistics & Predictive Modeling using OLS, Logistic Regression using MLE, KNN, Decision Trees

Mode of Learning and Duration

  • Weekdays – 5 to 6 weeks
  • Weekend – 6 to 7 weeks
  • FastTrack – 4 to 5 weeks
  • Weekdays – 5 to 6 weeks
  • Weekend – 6 to 7 weeks
  • FastTrack – 4 to 5 weeks


Course Agenda

  • What is Data Science
  • What is Machine Learning
  • Machine Learning vs. Data Science vs. AI
  • How leading companies are harnessing the power of Data Science with Python?
  • Different phases of a typical Analytics/Data Science projects and role of python
  • Anaconda vs. Python
  • Machine Learning flow to code
  • Regression vs. Classification
  • Features, Labels, Classes
  • Supervised Learning, Semi-Supervised and Unsupervised Learning
  • Cost Function and Optimizers
  • Installation and Setup
  • Installing R
  • Installing RStudio
  • Installing Packages
  • Working with Vectors
  • Vectors
  • Random Numbers, Rounding, and Binning
  • Missing Values
  • The which() Operator
  • R Essentials
  • Set Operations
  • Sampling and Sorting
  • Check Conditions
  • For Loops
  • Dataframes and Matrices
  • Importing and Exporting Data
  • Matrices and Frequency Tables
  • Merging Dataframes
  • Aggregation
  • Melting and Cross Tabulations with dcast()
  • Functions
  • Debugging and Error Handling
  • Fast Loops with apply()
  • Fast Loops with sapply(), lapply() and vapply()
  • Normal Distribution, Central Limit Theorem, and Confidence Intervals
  • Skewness in data
  • Correlation and Covariance
  • Statistical Tests – F Test, T-Test
  • DPlyR and Caret Packages
  • Aggregation and Special Functions
  • Understanding Syntax, Creating and Updating Columns
  • Chaining, Functions, and .SD
  • Fast Loops with set (), Keys, and Joins
  • Probability
  • Probability Distribution: Discrete
  • Probability Distribution: Continuous
  • Sampling Distribution
  • Estimation
  • Hypothesis Testing ANOVA
  • Importing Data from various sources (CSV, txt, excel, access etc)
  • Database Input (Connecting to database)
  • Viewing Data objects - subsetting, methods
  • Exporting Data to various formats
  • Cleansing Data with R Programming
  • Data Manipulation steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type conversions, renaming, formatting etc)
  • Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays etc)
  • Scaling and Normalizing data
  • Pre-processing and Formatting data
  • Feature selection – Correlation, P Values, Multi-Collinearity etc
  • Introduction exploratory data analysis
  • Basic Plots Vs. GGPLOT Library
  • Making Plots with Base Graphics
  • Drawing Plots with 2 Y Axes
  • Multiplots and Custom Layouts
  • Creating Basic Graph Types
  • Creating graphs using GGPLOT
  • Descriptive statistics, Frequency Tables and summarization
  • Univariate Analysis (Distribution of data & Graphical Analysis)
  • Bivariate Analysis(Cross Tabs, Distributions & Relationships, Graphical Analysis)
  • Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ densityplot etc)
  • Overview
  • Introduction to Regression Analysis
  • Types of Regression Analysis Models
  • Linear Regression
  • Model
  • Model statistics
  • Gradient Descent Algorithm
  • Demo: Simple Linear Regression
  • Demo: Regression Analysis with Multiple Variables
  • Cross Validation
  • Factor Analysis
  • Fitting model and Predictions
  • Logistic Regression
  • Decision Tree Classification
  • Entropy & Gini Index
  • Classification and Regression Trees
  • Decision Tree Statistics
  • Decision Tree
  • Demo: Decision Tree Classification
  • Evaluating Classification Report
  • ROC Curve
  • Random Forest Classification
  • Gradient Boosting
  • Introduction to Data mining principles
  • Data mining and knowledge discovery
  • Overview of Data warehousing and mining
  • Advantages and challenges
  • Data mining applications in various application areas
  • Data warehousing
  • Data warehouse architectures,
  • Datawarehouse design
  • Steps in Datawarehousing (ETL)
  • Data marts and OLAP
  • Design and performance considerations
  • Overview
  • Introduction to Clustering
  • Clustering Example
  • Clustering Methods: Prototype Based Clustering
  • Centroids and Means
  • Eucledian Distance Formula
  • Elbow Method – Picking values of K
  • Demo: K-means Clustering
  • Clustering and association Rule mining
  • EM technique
  • Hierarchical Clustering
  • Dendrogram
  • Density based methods
  • Grid based methods
  • Cluster Analysis and Outlier Analysis
  • Association Rule mining
  • Stream mining and Fraud Detection



Industry: - Banking and Finance

Problem Statement: - Analyse customer and applicant data to identify any possible fraudulent activity or operation

This project will let you work with credit card dataset for real time analysis and defining attributes describing customer characteristics to build a classification model to predict which customer is likely to default a credit card payment next month. The process will involve performing data analysis and plotting score performance with respect to variables

Industry: - Entertainment and E-Commerce

Problem Statement: - Develop a recommender system for shows and movie recommendation over platform like Netflix

This project will let us understand how to work with raw data and make use of processes like Data Cleaning, Data Visualization, Distribution, Recommender Lab to develop a system to recommend specific movie or show after understanding and analysing the preferences of users

Industry: - Healthcare

Problem Statement: - Make a prediction model to know how likely is a patient to get chronic kidney disease

This project will be done using health history data of a patient to know about the probability of getting infected or suffering from chronic kidney disease

Industry: - Inventory Management

Problem Statement: - A company wants a build a tool to help their managers to in analysing the inventory to increase cross selling

This project will make use of tools and techniques like Association Rule, Mining, Data Extraction and Data Manipulation to work upon real time inventory data and make a model analysed to manage whole thing quite effectively and maintain the product associated with crossponding products requirement

Industry: - Banking

Problem Statement: - Predict the approval rate of loan for an applicant

The project will help the banking system by using Data Pre-processing, PCA, Cleaning Ops and Data Visualization to make prediction that about how much is it safe to grant a loan to a person. You will build a machine learning based model to predict the loan application status based upon the user earnings, expenses, banking transaction, financial behaviour and other loan or lending status



Career Support

We have a dedicated team which is taking care of our learners learning objectives.


There is no such prerequisite if you are enrolling for Master’s Course as everything will start from scratch. Whether you are a working IT professional or a fresher you will find a course well planned and designed to incorporate trainee from various professional backgrounds.

AI Council offers 24/7 query resolution, you can raise a ticket with a dedicated support team and expect a revert within 24 Hrs. Email support can resolve all your query but if still it wasn’t resolved then we can schedule one-on-one session with our instructor or dedicated team. You can even contact our support after completing the training as well. There are no limits on number of tickets raised.
AI council provide two different modes for training one can choose for instructor lead training or learning with prerecorded video on demand. We also offer faculty development programs for college and schools. apart from this corporate training for organization/companies to enhance and update technical skills of the employees. We have highly qualified trainers who are working in the training industry from a very long time and have delivered the sessions and training for top colleges/schools and companies.
We are providing a 24/7 assistance for the ease of the student. Any query can be raised through the interface itself as well as can be communicated through email also. If someone is facing difficulties with above methods mentioned above we can arrange a one on one session with the trainer to help you with difficulties faced in learning. You can raise the query throughout the total training period as well as after the completion of the training.
AI Council offers you the latest, appropriate and most importantly the real-world projects throughout your training period. This makes student to gain industry level experience and converting the learning’s into solution to create the projects. Each Training Module is having Task or projects designed for the students so that you can evaluate your learning’s. You will be working on projects related to different industries such as marketing, e-commerce, automation, sales etc.
Yes, we do provide the job assistance so that a learner can apply for a job directly after the completion of the training. We have tied-ups with companies so when required we refers our students to those companies for interviews. Our team will help you to build a good resume and will trained you for your job interview.
After the successful completion of the training program and the submission of assignments/quiz, projects you have to secure at least B grade in qualifying exam, AI Council certified certificate will be awarded to you. Every certificate will be having a unique number through which same can be verified on our site.
To be very professional and transparent No, we don’t guarantee the job. the job assistance will help to provide you an opportunity to grab a dream job. The selection totally depends upon the performance of the candidate in the interview and the demand of the recruiter.
Our most of the programs are having both the modes of training i.e. instructor led and self-paced. One can choose any of the modes depending upon their work schedule. We provide flexibility to choose the type of training modes. While registering for courses you will be asked to submit your preference to select any of the modes. If any of the course is not offered in both modes so you can check in which mode, the training is going on and then you can register for the same. In any case if you feel you need any other training mode you can contact our team.
Yes, definitely you can opt for multiple courses at a time. We provide flexible timings. If you are having a desire for learning different topics while continuing with your daily hectic schedule our course timing and modes will help you a lot to carry on the learning’s.
Whenever you are enrolling in any of the courses we will send the notification you on your contact details. You will be provided with unique registration id and after successful enrollment all of the courses will be added to your account profile on our website.AI Council provides lifetime access to course content whenever needed.
A Capstone project is an outcome of the culminating learning throughout the academic years. It is the final project that represents your knowledge, efforts in the field of educational learning. It can be chosen by the mentor or by the students to come with a solution.
Yes, for obtaining the certificate of diploma programmer you have to submit the capstone project.