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IS THIS COURSE FOR YOU?


Student


Working Professionals looking for career switch to analytics


Job seekers who wants to start career to analytics


Business owner who want to grow their business using analytics


Analytics professional who want to learn advanced analytics techniques


Enthusiasts who has genuine interest in analytics and want to grow his skills

Program Overview

This course is a focused attempt to provide a solid foundation to everyone seeking to get started as a data scientist. It doesn’t matter if you are a fresher or IT professional or non-IT professional, all you need is a passion for problem solving. After completing this course you will possess all the skills required to build analytics solutions using R.

PROGRAM STRUCTURE

SELF-PACED LEARNING

Before you join in, get ready for the live sessions. Introduction to data science.

A series of online tutorials will teach you the fundamentals of data science, R and introduce you to the basic statistics

INSTRUCTOR-LED TRAINING

Learn and apply data science. 48 hours of live sessions. Build analytics solutions.

Our carefully crafted curriculum provides the right mix of theory, hands-on labs & projects. Our experienced instructors bring case from frontlines to solidify learning.

LEARN BY DOING

More learning, capstone project, case studies & doubt clearing session.

Get started on 3 capstone projects. Solidify your learning by accessing several assignments & new case studies. Doubt clearing sessions will be conducted as well.

LVC AT A GLANCE


POST COMPLETION YOU WILL BE ABLE TO…

CONCEPTUALIZED BY INDUSTRY EXPERTS


Jaydeep Chakraborty
Data Science Expert

An innovator and creator at heart. He has 10+ years of experience in building analytical solutions & digital strategy for large organizations. Specialized in business transformation through analytics.

SRINIVAS KOPPARAPU
Big Data Expert

Srinivas Kopparapu is an internationally recognized faculty, with 31 years of industry experience. He is a Franklin Covey Certified faculty and an evangelist of Big Data, Hadoop, Mark Logic , Bitcoin & Python

Gurleen Sabharwal
Data Science Expert

After graduating from SRCC & DSE, she has worked for world's top consulting firms. She brings her passion for teaching & 10+ years of analytics implementation experience at Fortune 100 companies.

Shishir Pal
Marketing Analytics Expert

A graduate from IIT Kanpur, has a passion for telling stories from big data. He has built several innovative solutions on big data while working for some of the top consulting firms in the world.

Jose Marcial Portilla
Data Science Expert

After graduating from Santa Clara University, he has gone on to lead data science teams and provided several Fortune 500 companies with Data Science and Programming Training and Consultation.

Abhishek Ranjan
Operation Analytics Expert

An analytics specialist with Masters in Business Statistics from ANU. He brings the experience of solving some of the toughest supply chain problems while working for world’s leading logistic companies.

Manish Sharma
HR Analytics Expert

A graduate from IIT Chennai has a heart of a researcher. He loves to tinker with deep learning and AI. While working for top consulting firms in the world he has helped several Fortune 100 companies.

Course Contents

Module 1 - Basics of R Programming

Supported By

  • Practice exercises
  • Assignments
  • Doubt clearing sessions
  • Data Exploration: Data Summarization techniques, An Insight into Univariate Analysis and Bivariate Analysis, Outlier Treatment, Missing Value Treatment, Case Study, Assignment.
  • Inferential Statistics: Understanding the Probability Theory, An Insight into the Bayes Theorem, Probability Distribution Functions, Hypothesis Testing, Case Study, Assignment.
  • Control flow basics: Loops in R, Drawbacks associated with using Loops, Alternatives to using Loops, Case Study, Assignment.
  • Descriptive Statistic: Measures of central tendency, Measures of dispersion, Range and Skewness, Introduction to Histograms, Assignment.
  • R fundamentals: An Overview of R, Packages, Data Structures in R, Arithmetic &Logical Operators, Case Study, Assignment.
  • R Functions: Introduction to Function, How to Build a Function of Your Own, Case Study, Assignment.
Module 2 - Advanced R Programming

Supported By

  • Practice exercises
  • Assignments
  • Doubt clearing sessions
  • Packages: Searching and Selecting a New Package, How to Install and Update a Package, How to Access Package
  • Functions, Hacking a Function, How to Develop a Package on Your Own.
  • Data Manipulation Basic: Sorting and Ranking, Understanding Data Aggregation, Merging, Case Study, Assignment.
  • Data visualization Fundaments: How to plot function, How to change the parameters, How to draw basic charts, How to add chart elements.
  • Environment objects: Saving and Loading Objects, Deleting Objects.
  • Data Manipulation Advanced: Apply, Lapply, Tapply, Replicate functions, Dplyr, Tidy.
  • Data Visualization Fundaments: qplot, ggplot, and Maps.
  • Data Import and Export: Import data from various types of files like csv, excel etc. as well as databases like MySQL, Export data to various formats like csv, excel etc. Export data to Image and PDF. Presenting the Output in HTML Webpage. Import data from various types of files like csv, excel etc. as well as databases like MySQL, Export data to various formats like csv, excel etc. Export data to Image and PDF. Presenting the Output in HTML Webpage.
Module 3 - Data Science Basics
  • Linear Regression: An Overview of the Linear Regression technique, Application of Linear Regression, Ordinary Least Squares Estimation Technique, Variable handling, Model Statistics Interpretation, Validation of Linear Regression Assumptions, Measuring Model Performance, Case Study, Assignment.
  • Logistic Regression: An Overview of Logistic Regression Technique, Application of Logistic Regression, Maximum Likelihood Estimation Technique, Dependent Variable estimation, Variable Handling, Information Value, Model Statistics Interpretation, Measuring Model Performance, Case Study, Assignment.
  • Time Series Forecasting: Basics of Time Series Modeling, Application of Forecasting, Smoothing Techniques, Decomposition, ARIMA and ARIMAX, Model Estimation & Interpretation, Forecasting with Regression on Time Series Data, Case Study, Assignment.
Module 4 - Machine Learning with R
  • Introduction to Machine Learning:
    • Introduction to Machine Learning
    • Application of Machine Learning in industry
    • Supervised Machine Learning
    • Unsupervised Machine Learning
  • Unsupervised Machine Learning:
    • What is Clustering?
    • Types and Uses of Clustering
    • K-Means Clustering
    • Hierarchical Clustering
  • Supervised Machine Learning:
    • Introduction to Naive Bayes
    • Introduction to decision trees
    • Introduction to ensemble models
    • Introduction to Artificial neural network

CASE STUDIES AND PROJECTS



LINEAR REGRESSION

  • Predict house price using 20+ attributes like number of bedrooms, bathrooms, area, views, age, etc. to predict the price of house.
  • Predict claim amount for an auto insurance company

LOGISTIC REGRESSION

  • Predict who is going to leave the telecom service provider
  • Case study on predicting customer cross sell for a large retailer

TIME SERIES FORECASTING

  • Forecast daily sales for 3000 drug stores across 7 European countries using attributes like promotions, competition, school, state holidays etc.
  • Case study on forecasting call volumes for a call center
  • Forecast temperature basis pollution, dew point, air pressure, wind direction, wind speed, rainfall & snowfall

NAÏVE BAYES

  • Prediction of cancer using Naive Bayes

DECISION TREE AND ENSEMBLE MODEL

  • Realize the profile of high value customers using Decision Trees and Ensemble Models

ARTIFICIAL NEURAL NETWORK

  • Modelling the strength of concrete with ANN 

CLUSTERING

  • Customer segmentation on hypermarket loyalty customer data Cluster insurance customers using attributes like demographics, claim behaviour, value, etc.  

CERTIFICATION

DUAL CERTIFICATIONS




CERTIFICATE of Participation

Post attending the LVC


CERTIFICATE OF ACHIEVEMENT

Post attending the LVC and completing 80% of the e-learning modules and assignments along with project submission


OUR VALUE PROPOSITION

YOU WILL LEARN TO BUILD ANALYTICS SOLUTIONS. GUARANTEED!


LEARN FROM ‘EXPERTS ONLY’

IVY league education + 10+ years of experience at world’s best consulting conpanies


REAL INDUSTRY PROJECTS

We leverage our consulting practice to bring nothing but only real industry projects


PERSONALIZED LEARNING

Handholding for analytics novices & new exposure for analytics amatuers



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