DSP

DATA SCIENCE PRODEGREE

In collaboration with Genpact, a Global Leader in Analytics

200 Hours of Learning delivered in Classroom and Online format

Hands-on learning with 6 industry projects

Course covering Data Science, Statistics, SAS, R, Python and Tableau

Pay your program fee through EMI’s

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In Collaboration with:

Classroom Training
र 72,500/-

Online Instructor-Led Training
र 55,000/-

Online Self Paced Videos

Data Science Certification Course

The Data Science Prodegree, in association with Genpact as the Knowledge Partner, is a 200 hour training course that provides comprehensive coverage of Data Science and Statistics, along with hands-on learning of leading analytical tools such as SAS, R, Python and Tableau through industry case studies and project work.

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Genpact Endorsed

Cutting-edge program designed and delivered in collaboration with Genpact, a global leader in Analytics solutions

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Leading Tools

Master Data Science using leading tools such as SAS, R, Python and Tableau

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Experiential Learning

Hands-on learning through 6 industry projects, across multiple tools and industries

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Placement Assistance

Extensive support via resume building, interview prep, mentorship and interview opportunities

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Genpact Endorsed

Cutting-edge Data Science training program designed and delivered in collaboration with Genpact, a global leader in Analytics solutions

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Leading Tools

Master Data Science using leading tools such as SAS, R, Python and Tableau

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Experiential Learning

Hands-on learning through 6 industry projects, across multiple tools and industries

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Placement Assistance

Extensive support via resume building, interview prep, mentorship and interview opportunities

Data Science Course Curriculum

The Data Science Prodegree has been designed in conjunction with multiple industry leaders to ensure that you learn exactly what employers need.

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Learn more about the curriculum for the DSP program

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13%
Data Science
19%
Python
35%
R
22%
SAS
4%
Tableau
7%
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All about Data Science

  • Data, Data Types
  • Meaning of Variables
  • Central Tendency
  • Measures of Dispersion
  • Data Distribution

Predictive Modelling

  • Decision Trees
  • Neural Networks
  • Predictive Modeling with Decision Trees

Neural Networks

  • Perceptron
  • MLP
  • Back Propagation
  • Revision of Key Concepts

ANOVA/ Regression Analysis

  • Analysis of Variance & Covariance
  • Analysis of Variance
  • ANOVA Results
  • Examine Regression Results
  • Regression Analysis
  • Linear and Logistic Regression

Tree and Bayesian Network Models

  • Decision Trees
  • Bagging
  • Random Forests
  • Boosted Trees
  • Bayesian Classification Models

R Basics

  • R Base Software
  • Understanding CRAN
  • RStudio The IDE
  • Sequence of Numbers
  • Vectors
  • Basic Operations
  • Operators and Types
  • R Functions

Logistic Regression in R

  • Reason for Logistic Regression
  • The Logistic Transform
  • Logistic Regression Modelling
  • Model Optimisation
  • Understanding ROC Curve
  • Default Modelling using Logistic Regression in R

Decision Trees

  • Theory of Entropy & Information Gain
  • Stopping Rules
  • Cross Validations for Overfitting Problem
  • Pruning as a Solution for Overfitting
  • Ensemble Learning
  • Bootstrap Aggregation
  • Random Forests
  • Intrusion Detection in IT Network

Linear Regression in R

  • Covariance and Correlation
  • Multivariate Analysis
  • Hypothesis Testing
  • Limitations of Regression
  • Business Case: Managing Credit Risk
  • Loss Given Default using Linear Regression

Support Vector Machine

  • Classification as a Hyper Plane Location Problem
  • Motivation for Linear Support Vectors
  • Quadratic Optimization
  • Non Linear SVM
  • Kernel Functions
  • Default Modelling using SVM in R

Python Basics

  • What is Python?
  • Installing Anaconda
  • Understanding the Spyder Integrated Development Environment (IDE)
  • Lists, Tuples, Dictionaries, Variables

Data Frame Manipulation

  • Data Acquisition
  • Indexing, Filtering
  • Sorting & Summarizing
  • Descriptive Statistics
  • Combining and Merging Data Frames
  • Discretization and Binning
  • String Manipulation

Projects

  • Default Modeling using Logistic Regression in Python
  • Credit Risk Analytics using SVM in Python
  • Intrusion Detection using Decision Trees & Ensemble Learning in Python

Data Structures in Python

  • Intro to Numpy Arrays
  • Creating ndarrays
  • Indexing
  • Data Processing using Arrays
  • File Input and Output
  • Getting Started with Pandas

Other Predictive Modelling Tools

  • Intro to Machine Learning
  • Random Forests
  • Sklearn Library and Statsmodels

SAS Basics

  • Key Features
  • Submitting a SAS Program
  • SAS Program Syntax
  • Examining SAS Datasets Accessing SAS Libraries
  • Sorting and Grouping
  • Reporting Data
  • Using SAS Formats

Data Transformations

  • Writing Observations
  • Writing to Multiple Datasets
  • Accumulating Total
  • Creating Accumulating Total for a Group of Data
  • Data Transformations

SQL

  • SQL & RDBMS
  • SQL Procedures
  • Presenting & Summarizing Data
  • Join Queries using SQL
  • Subqueries, Indexes and Views
  • Set Operators
  • Creating Tables and Views using Proc SQL

Reading and Manipulating Data

  • Reading SAS Datasets
  • Reading Excel Data
  • Reading Raw Files
  • Reading Database Data
  • Creating Summary Reports
  • Combining Datasets

Macros

  • Automatic Macro Variables
  • User Defined Macro Variables
  • Macro Variable Reference
  • Defining and Calling Macros
  • Macro Parameters
  • Global and Local Symbol Tables
  • Macro Variables in the Data Step

Project

  • Store Data Analytics in SAS
  • ETL, Analysis and Reporting using SAS

Tableau Basic

  • Introduction to Visualization
  • Working with Tableau
  • Visualization in Depth
  • Data Organisation
  • Advanced Visualization
  • Mapping
  • Enterprise Dashboards
  • Data Presentation

Best Practices for Dashboarding and Reporting and Case Study

  • Have a Methodology
  • Know Your Audience
  • Define Resulting Actions
  • Classify Your Dashboard
  • Profile Your Data
  • Use Visual Features Properly
  • Design Iteratively

Mock Interviews

  • Resume Building and Interview Prep
  • 1:1 Mock Interviews with Industry Veterans
  • Clear the Technical Round of Interviews
  • Give You Confidence to Face Real World Scenarios

Group Project Presentation or Refresher

  • CLASSROOM: Groups present their Project Presentation in front of their peers and industry experts evaluate the solution
  • ONLINE: Refresher on Domain

Training Methodology

With a strong emphasis on ‘learning by doing’, our programs are developed with the goal of creating well-rounded, job-ready professionals that can add immediate value to any organization.

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STEP 1: INSTRUCTION

Flexible Delivery: The Prodegree is delivered in two modes: Classroom and Online (Live Virtual Classes) to cater to your learning preferences.

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STEP 2: EXPERIENTIAL LEARNING

Real Life Learning: Go beyond traditional rote learning through the use of 6 projects, real-life scenarios, and classroom discussions.

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STEP 3: REINFORCEMENT

Assessments: Each topic is followed by Quizzes, Tests and Assignments that help understand and internalize key concepts.

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STEP 4: TECHNOLOGY AIDED

Centralized Learning: Manage your performance across the program through a state-of-the-art learning management system.

24/7 Support

Get 24/7 access to your Data Science course material on our state of the art learning management system; extended access to all course material after the batch ends, and a dedicated student hotline with 24/7 support to help resolve queries.

Case Studies and Projects

CASE STUDY 1
  • Default Modelling using Logistics Regressions in R Language
  • Default Modelling in Support Vector Machines using R Language
CASE STUDY 2
  • Default Modelling using Logistics Regression in Python
CASE STUDY 3
  • Intrusion detection using Decision Trees in Python
  • Intrusion detection using Ensemble Learning in Python
CASE STUDY 4
  • Intrusion Detection in Network using Decision Tree in R Language
  • Intrusion Detection in Network using Ensemble Learning in R
CASE STUDY 5
  • Credit Risk Analytics using Support Vector Machines in Python
CASE STUDY 6
  • Data Analytics storage in SAS

Career

The Career Assistance Services (CAS) team works hand in hand with you to further your career aspirations. We thoroughly prepare you to be interview-ready through resume building sessions and interview preparation workshops, and provide you with interview opportunities with leading analytics firms.


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“Studying in the Data Science domain at Imarticus has been an outstanding learning experience for me. The trainers and teaching staff have always been supportive and efficient in their respective fields. They continuously inculcate valuable knowledge and guide us throughout. The collaboration of thorough practical knowledge along with theoretical studies makes the Imarticus team highly suitable for those looking to gain important knowledge. I am extremely satisfied by acquiring the knowledge and experiences related to Data Science from Imarticus.”

– Priti Motiwani

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“Belonging to a non-technical background, the whole idea of studying Data Science was extremely traumatic for me. But with Imarticus, the overall experience was very satisfying. The in-depth teaching and additional practical knowledge provided at Imarticus about Data Science has helped me achieve great heights in my career. The teaching staff and the learning atmosphere were very supportive. Especially, both the faculties of R and Python were well-experienced, knowledgeable and simultaneously helpful. This highly boosted up my knowledge regarding Data Science.”

– Rajashree Pakhare

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“My experience at Imarticus Learning was really helpful and informative. They establish a strong platform for their students with the help of their knowledgeable curriculum, experienced and helpful trainers, and a unique learning environment. Along with the in-depth knowledge about the Data Science concepts and theories, they provide you with efficient placement skills. The amalgamation of theoretical and practical exposure make the Imarticus platform suitable one. In addition to this, the job opportunities provided encourage us to establish a steady career.”

– Nachiket Thakur

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Business Intelligence Analyst

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Web & Social Media Analyst

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Business Analytics Specialist

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Research Analyst

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Business Analytics Tech Consultant

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Data Mining Specialist

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CRM Analyst

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Data Warehousing Specialist

LARGE IT COMPANIES WHO HAVE AN ANALYTICS PRACTICE

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ANALYTICS KPOs

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IN-HOUSE ANALYTICS UNITS OF LARGE CORPORATES

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NICHE ANALYTICS FIRMS

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Imarticus provides 100% assistance throughout the program to guide and navigate ample career options, and assist you with job readiness from day 1.

GETTING STUDENTS JOB READY

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RESUME BUILDING

Refining and polishing the candidate’s resume with insider tips to help them land their dream job

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INTERVIEW PREP

Preparing candidates to ace HR and Technical interview rounds with model interview questions and answers

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MOCK INTERVIEWS

Preparing candidates to face interview scenarios through 1:1 and panel mock interviews with industry veterans

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ACCESS TO OUR PLACEMENT PORTAL

Access to all available leads and references from open and private networks on our placement portal

Certification

On completion of the Data Science Prodegree, aspirants will receive an industry endorsed Certificate of Achievement, which is co-branded by Genpact and Imarticus Learning.

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Collaboration with Genpact

The Data Science Prodegree is co-created with Genpact as the Knowledge Partner and comes with a cutting edge industry aligned curriculum and learning methodology. You will benefit in terms of:

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SHARING OF CASE STUDIES

You will build multiple projects based on real-life scenarios. Genpact will assist in evaluating project submissions and provide constructive feedback

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GUEST LECTURES

Senior leaders will conduct guest lectures on key trends and real-world challenges plaguing the industry and mentor you towards job-readiness

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INDUSTRY APPROVED CURRICULUM

You learn in-demand skills and sought-after tools and techniques required by the Data Science industry through interactive case studies and hands-on projects

About Genpact

Genpact is a global leader in digitally-powered business process management and services across technology, analytics, and organizational design. The company boasts net revenues of US$2.46 billion with more than 70,000 employees spread across 25 countries and 1/5th of the Fortune Global 500 companies as its clients.

Industry Advisors

The Data Science program is developed in consultation with senior Industry experts to ensure a high degree of relevance in accordance to the needs and demands of the industry.

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IQBAL KAUR

Ex- Target and Genpact

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AMIT KHANNA

Managing Partner – YDatalytics (Antuit & Y Group)

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AKASH BHATIA

Founder And CEO,
Infinite Analytics, Kyazoonga

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Admissions

The Data Science Prodegree is ideal for students and experienced professionals who are interested in working in the analytics industry, and are keen on enhancing their technical skills and business understanding of data science.

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Experienced Professionals

Professionals who are looking to up-skill or change career paths. Technical experience is a plus.

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Job Seekers

Recent Graduates in Bachelors or Masters in Science, Math, Statistics, Engineering, Finance or Computer Applications/IT.

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Global Certifications

Those looking to enhance their resumes & build a portfolio of demonstrable work in one of the most coveted professions of this century.

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Experienced Professionals

Professionals who are looking to up-skill or change career paths. Technical experience is a plus.

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Job Seekers

Recent Graduates in Bachelors or Masters in Science, Math, Statistics, Engineering, Finance or Computer Applications/IT.

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Global Certifications

Those looking to enhance their resumes & build a portfolio of demonstrable work in one of the most coveted professions of this century.

To enroll for the Data Science Prodegree, please click below:

Faculty

Prachi Samant

VB. Net,Machine learning techniques

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Tharangini Vijay Kumar

Basic and Advanced Statistical Techniques, Predictive Modelling

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Y Laxmi Prasad

Python, ML, Deep Learning and R Programming

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Sonal Ghansani

Basic and advanced statistical techniques

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Data Science Course Videos


Genpact talks about the Imarticus Data Science Prodegree and the current skill gap while hiring for data scientists

Importance of Data Science and why Imarticus partnered with Genpact to deliver it

Learn more about the curriculum for the DSP program

FAQs

What is the Genpact collaboration about?
Genpact is a global leader in digitally-powered business process management and services and works with over 1/5th of the Fortune Global 500 companies across technology and analytics with revenues of $2.46 billion and 70,000 employees spread across 25 countries.

Genpact is involved in the Data Science training course through curriculum design, project reviews, guest lectures and mentorship. A partnership with such an industry leader ensures that the curriculum is timely and industry relevant.

What is the format of the Data Science course?
The Data Science Prodegree is a 200 hour classroom or online training program, that provides aspirants with an in-depth understanding of Data Science, Statistics, as well as hands-on learning of leading analytical tools such as SAS, R, Python and Tableau. The delivery hours include 140 hours of live instructor led training, and 60 hours of self paced instructor videos.

Classroom batches: Classroom training by expert faculty at our Imarticus centers in Mumbai, Bangalore, Chennai, Gurgaon, Hyderabad, Coimbatore and Pune.
Online batches: Live Instructor-led Virtual Classes (Webinars) with expert faculty for real-time learning and interaction with batch mates.

Class times for both formats are fixed and you are required to be available for your classes at a predefined time each week. Both formats come with 60+ hours of engaging Instructor videos that you can watch as per your convenience before attending your lecture (be it in class or virtually).

What is the duration of the Data Science course?
The DSP is a 4-month program done part time (on weekends), and a 2 month program if done full time on the weekends. Please contact the nearest center for more information.
What study material will be provided to us for the Data Science course?
The core learning will happen via 140 hours of classroom or virtual online lectures depending on your learning preference. You will also have access to additional study material like recordings of previous virtual classes, power-point presentations, case studies, quizzes and eBooks on the learning portal. You will be given extended access to a fully integrated online learning portal where all your learning materials will be uploaded. You will need to log in to the learning portal using the credentials provided and navigate through the portal as required.
What certificate will I get ?
Post the successful completion of the program, you will be awarded the DSP Certification, co-branded with Genpact, as a Knowledge Partner.
What should be my expectation from the Data Science training program?
The program is designed for aspirants with no or limited data analytics experience. As a result, the curriculum covers basics to advance topics. The program is rigorous and requires a time commitment from any participant (about 8-12 hours a week including delivery hours).
Do you guarantee placements?
As a policy, we do NOT guarantee placements. Our Placement Assistance team will provide you the ideal platform to launch your career through resume building sessions, mock interviews, mentorships, interview preparation. Our team will also work towards finding you interview opportunities, as well as thoroughly prepare you prior to every interview.
What is the fee of the Data Science training course?
The Data Science training course is Rs.72500 for the classroom mode, and Rs.55,000 for the online mode. You can pay by Credit card, Debit Card or Net banking from all leading banks to the nearest Imarticus center, or online. In the event you are unable to pay, please contact 18001037480 for further assistance.

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Speak to a Career Advisor