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For the past two decades, drastic global changes have been experienced in every society due to rapid and disruptive advancements in the field of IT and related areas. Growth of computer power, abundance of smart phones, cloud technology and artificial intelligence enabled successful digital transformation in all corners of business and technology. As a result, required skill bases for new normal activities have shifted dramatically, generating hunger for new skills in the business and industries.

Amid such skill crisis, JAGSoM came up with a Tomorrow’s technology driven business analytics practice oriented module in their PGDM program. Aspiring graduates will be provided with a ten-credit sandwiched course between business houses and academic campus. The course will primarily have objectives of keeping pace with technological and managerial advancements and learn the stuff at the industry bench.

The course includes all possible data oriented advanced skills on end-to-basis. A capstone project to solve challenging business problems, is also included, guided by industry mentors. Contextual data analyses including, pre-processing, visualization, machine learning models and deep learning models and optimization algorithms, are in the central focus.

CAREER TRACK COURSES

  • Analytics Concepts with Python

  • Supervised Machine Learning using Python

  • Data Preprocessing

  • Image Processing Fundamentals

  • Introduction to Deep Learning

  • Data Scientist or Data Engineer

    Competency

    • Understands the business domain problem
    • Create a vision for an analytical solution involving machine learning and/or computer vision
    • Converts business requirements to technical specifications
    • Identifies required data
    • Applies strong knowledge of predictive analytics
    • Creates models to deliver the business solution
    • Can work in teams and lead a team

    • Critical Skills

    • Strong Knowledge of Statistics, Machine Learning, Python and other platforms
    • Ability to do data selection and data preprocessing
    • Ability to write code (or configure workflows) to generate analytical solutions
    • Ability to test code and improve efficiency and accuracy
    • Ability to create scalable solutions with large data sets

    Interventions - Courses

    • Coding Business Applications with R and Python
    • Predictive Analytics in Business
    • Advanced Predictive Analytics
    • Business Data Visualization
    • Big Data Analytics
    • Analytics modules and Capstone project with INSOFE

    Intervention - Certifications

    Following certifications are not mandatory, but highly recommended:
    • Machine Learning on Coursera
    • Deep Learning certification from IISc
  • Product Manager / Business Analyst

    Competency

    • Liaise with Client Business Team
    • Analyse the client’s business process and understand the business problem
    • Envision one or more IT solution(s) to address the business problem
    • Generate SMART requirements for the IT solution
    • Prioritize among the requirements; resolve conflicts among stakeholders
    • Explain requirements to team of developers
    • Support solution development, validation and e2e implementation
    • Helps in estimation and budgeting

    Critical Skills

    • Excellent communication skills, both written and oral
    • Strong understanding of business domain
    • Knowledge of IT Applications & Solutioning
    • Generating SMART Business Requirements, Scoping and Documentation
    • Understanding of data from data visualization tools
    • Creating models such as DFDs, ER Diagrams, Visualizations, Predictive Models, etc
    • Basic project management skills in project scoping and estimation

    Interventions - Courses

    • Business Requirements Analysis
    • Business Data Visualization
    • Digital Project Management
    • Data Management Systems and Data Engineering

    Intervention - Certifications

    EBAP (IIBA)
  • PRE-REQUISITES (ELECTIVE COURSES) FOR THE CAREER TRACK PROGRAMME
    • Coding Business Applications in R and Python
    • Predictive Analytics in Business
    • Advanced Predictive Analytics

    1. ANALYTICS CONCEPTS WITH PYTHON

    Brief Details of the courses

    1-8

    Data Structures in Python: Lists, Dictionaries, Tuples

    Data subsetting, loop control statements in Python

    Data Ingestion (data frames) and File Management

    Jupyter Notebook and iPython CLT; Spyder;

    Associated Lab Exercises in Python

    9-10
    Numpy Arrays in Python
    11-12
    Data Visualization using Matpotlib

    Lab Exercises for Numpy and Matplotlib

  • 2. SUPERVISED MACHINE LEARNING USING PYTHON

    13-20
    Supervised Machine Learning (Classification and Regression Methods)
    • Linear Regression
    • Logistic Regression
    • Neural Networks / Backpropagation
    • Gradient Descent Algorithm and its variants
    21-24
    Accuracy in Classification Methods:
    • Confusion Matrix
    • Accuracy
    • Imbalanced Classes
    • Other metrics – Recall, Sensitivity, etc?
    • Cost of Classification
    25-26
    Related concepts in Classification:
    • Overfitting and Underfitting
    • Bias-Variance Tradeoff
    27-29
    • Concept of ensemble and majority voting principle
    • How ensembles improve the accuracy
    • Ensemble methods for classification:
    o Bagging
    o Boosting
    o Random Forest
    30-32
    • SKLearn package in Python
    • Lab session: Implementation of Regression and Classification Models in Python
  • 3. DATA PREPROCESSING

    33-34
    Missing value algorithms and their applications
    35-42
    Data Preprocessing Methods:
    • Discretization
    R• Normalization
    5-6
    • Outlier Detection
    • Scaling
    • Shuffling
    43-50
    Dimension Reduction Methods:
    • Review of Correlation Concepts
    • Principal Components Analysis
    • Factor Analysis
    50-51
    Lab Session: Dimension Reduction using SPSS / Python
  • 4. IMAGE PROCESSING FUNDAMENTALS

    55-56
    • Basics of Image Formation
    • Application of Matrix operations to Image Algebra
    • Image Quantization , Image Filters Introduction
    57-58
    • Image Preprocessing & its importance.Normalization/Scaling
    • Noise Filtering-Random, Uniform, Gaussian, Salt /Pepper Noise
    • Optimum Noise Filtering Selection
    • Edge/Line Detection: Robert, Sobel & Prewitt Filters
    • Effect of Filter Size on performance
    • Convolution Filters for Edge Detection
    • Segmentation of Images
    59
    • Region Growing & Shrinking
    60-63
    • Boundary detection
    • Morphological Filtering
    • Image Labelling
    • Image classification using Simple Neural Network
    64
    • Lab Session on Image Processing
  • 5. INTRODUCTION TO DEEP LEARNING

    65-66
    • Necessity for Deep Learning Algorithms
    • Data Management using Deep Learning
    • Problem Framing and File Management
    • Setting up of the environment and cloud accounts
    67-70
    • Deep Neural Networks
    o Over-fitting and Underfitting
    • Auto-Encoders
    • Dropouts and Batch Normalization
    71-75
    • Convolutional Neural Networks
    • Architecture of CNN
    • Concept of Convolution Operation
    • Padding and Striding
    • Transfer Learning• Applications of CNN in Image Processing
    • Applications of CNN in Image Processing
    76-77
    • Basic concepts of Text and Natural Language Processing
    • Word to Vector concept, Cosine distance
    • Filtering
    • TF/IDF algorithm
    78
    • Introduction to Topic Modeling
    78-85
    Lab Session: Image Processing using CNN in Tensorflow and Keras

Core Faculty

  • Dr. Supriyo Ghose

    Professor and Chairperson of Digital Business and Analytics area, JAGSoM

    Dr.Supriyo Ghose has an academic and corporate experience of over 25 years. He has completed his Fellow Program in Management from IIM Calcutta. His corporate affiliations include brands like TCS, PwC, Mahindra Satyam, and Infosys. He started his teaching career at IIM Calcutta, and has also served at Amrita University, Alliance University, and IIM Ranchi (as Visiting Faculty).

  • Dr. Kalyan Sankar Sengupta

    Professor, Digital Business and Analytics, JAGSoM

    Professor, researcher and consultant, Dr. Sengupta has a rich experience of academics and industry for more than three decades. He completed his graduation and post-graduation from the University of Warwick, UK, and his Ph.D. from the University of Calcutta. He was affiliated with Jadavpur University, IISWBM, ICFAI, IMT Ghaziabad, RCC, IBS, etc. He also taught at IIM- Ranchi, IIFT, IMI- Kolkata as a visiting faculty. He has a rich consulting experience across various clients in India.

  • Senior Professor, Digital Business and Analytics, JAGSoMDr. Subramanyam was the chair Professor & officiating Director at FORE School of Management, New Delhi. He has done his B.Tech and M.Tech from IIT Kanpur, and PhD from University of Georgia, USA. He has a vast experience of more than 40 years in teaching and research. He worked as Professor and Area Chair of the Quantitative and Information Systems Group at IIM Lucknow, and also a visiting Professor at Manchester Business School. He has filed two patents in Financial domain.

  • Dr. Ellur Anand

    Assistant Professor, Digital Business and Analytics, JAGSoM

    Dr.Ellur Anand is an Assistant Professor in Digital Business and Analytics area. He is Green Belt Certified in Lean Six Sigma. He has completed his post-graduation from Amrita Institute of Management and Ph.D. from Pondicherry Central University. He served in many reputed institutions, including Alliance University and Kirloskar Institute of Advanced Management Studies (KIAMS).

  • Dr. Sreerama KV Murthy

    CEO & Chief Data Scientist – Quadratyx and Principal Advisor & Mentor, INSOFE

    Dr.Sreerama KV Murthy received a PhD degree in Data Mining and Machine Learning from Johns Hopkins University. In the past 25 years, Dr. Murthy worked for world-class research labs such as Siemens Corporate Research, IBM Research and CDAC, Mumbai. He has 8 US patents and international publications, all in Data Science.

  • Dr. Suryaprakash Kompalli

    Professor, INSOFE

    Dr.SuryaprakashKompalli has an extensive research background in image processing, pattern recognition, and GPU computing. He did his Ph.D. and MS from University at Buffalo. He has multiple patents and publications, and has also taught at Carnegie Mellon University and worked at Microsoft and HP Labs.

  • Duvvarapu Maheshkumar

    Principal Data Scientist, INSOFE

    Mr. Maheshkumar is Principal Data Scientist at INSOFE. He has more than 15 years of experience in the domain of statistical modeling and analysis. He has rich experience in several challenging data science problems across domains, gaining experience in architecting solutions and end-to-end project execution. He has led teams in developing algorithms and delivering solutions on both structured and unstructured data.

  • K.L.A. Koushik

    Data scientist, INSOFE

    Mr. Koushik is a data scientist at INSOFE. He completed his post-graduation in Big Data Analytics and Optimisation in 2018. He has rich experiences in data science consultation projects such as automated resume parsing tool, automation tool for detecting defects in semiconductor wafers, an automation tool for GDPR analytics. He is an expert in NLP, Image Processing, Programming Languages, and Databases.

REQUEST FOR PROBLEMS (RFP)
INDUSTRY PROJECTS

  • Company:

    INSOFE

    Project Title:

    Food classification for grocery store management using Computer Vision

    Project Description

    A grocery store wants to automate the process of identifying the item vacancies in the racks and then immediately reporting them to the respective departments for rack-refill. It achieves it by identifying the vacancies first, and then figuring out to which food category that particular part of the rack belongs to. As part of the project the company wants to classify various images into different classes of food using Machine Learning and Computer Vision.

  • INSOFE

    Detecting driver’s attention level from eyeball movement

    Driver distraction is one of the primary causes of accidents on roads.AI systems that are able to identify unsafe driver or passenger behaviour can
    help a long way in reducing accidents. These can be used in intelligent transport systems,accident control mechanisms, an even automobile insurance industry. The purpose of this project is to use Computer Vision and Machine Learning to identify driver’s attention level from the eyeball movement.

  • Capgemini

    Portfolio Wealth Management

    Feasibility of setting up a new line of business in insurance BD

  • Capgemini

    Credit Fraud Detection

    We are assigned to build a model to detect credit fraud. The challenge is to recognize fraudulent credit card transactions so that customers of credit card companies are not changed for items that they did not purchase.Random data has been collected and we created a model, through which It helps to find fraudulent transaction happening around the world.

  • Capgemini

    Credit Card Acquisition Model

    A model to identify potential customers who are eligible and may apply for credit card using behavioral pattern using data from social media.

  • Loantap

    Scoring Model for employer of an applicant and opportunities for future product diversification.

    The objective of this project is to develop a scoring model that can help evaluate the employer of a salaried applicant and his relationship with the employer and analyze other variables /inputs relevant for employer verification from an underwriting perspective.

STUDENT PROFILES

  • ABHIJEET GODARA

    RFP Company / RFP Project Title / Short Description: CAPGEMINI-Analytics in Portfolio Wealth Management

    Other projects / Accomplishments: NASSCOM |Jun 2021 to
    Jul 2021

    - Worked on Karnataka covid data analysis and resource allocation to hospitals. Collected covid data for Karnataka state and worked on dashboard using Tableau

  • ANIL REDDY MADDI

    Qualification: B. Tech.

    Work Experience: NA

    Contact: https://www.linkedin.com/in/anil-reddy-maddi-4743301b4/

    RFP Company / RFP Project Title / Short Description: CAPGEMINI-Analytics in Wealth Management

    INSOFE-Food classification for grocery store management

    Other projects / Accomplishments: NASSCOM |Jun-Jul 2021

    - Worked on Karnataka covid data and resource allocation to public health care centres.Collected covid data for Karnataka state.Worked on covid data dashboardusing Tableau.

    Research IncubationTo build a model for predicting Enterprise Value of a company for next 6 months using News data collected from different websites.

  • SOURAV PATTNAIK

    Qualification: B. Tech Worked as Technical Support Advisor in Teleperformance (9th Apr 18-3rd Dec 18)

    Worked with CICON Ltd. As Site Supervisor(1st Sep 16- 2nd Apr 18)

    Work Experience: NA

    Contact: https://www.linkedin.com/in/sourav-pattnaik-80691b1b2/

    RFP Company / RFP Project Title / Short Description: CAPGEMINI-Credit Card Acquisition Model (A model to identify potential credit card customers through Behavioural pattern)

    INSOFE -Driver Distraction (Predict the likelihood of what driver is doing in each picture)

    Other projects / Accomplishments: Research Incubation:Financial effect of Covid-19 on Indian Companies, Event Study.

  • ARKAJIT SAFUI

    Qualification: B. Tech.

    Work Experience: NA

    Contact: https://www.linkedin.com/in/arkajit-safui-8385801b2/

    RFP Company / RFP Project Title / Short Description: Capgemini-Detecting Credit Fraud

    Other projects / Accomplishments: - Evaluation of the readiness of drones for last mile delivery by logistics service providers in Bangalore city

  • BARATH KUMAR R

    Qualification: B.E.

    Work Experience: NA

    Contact: https://www.linkedin.com/in/barath-kumar-r-6479b51b3B.E.

    RFP Company / RFP Project Title / Short Description: INSOFE - Food classification for grocery store management.

    CAPGEMINI - Credit card Fraud Detection

    Other projects / Accomplishments: Research Incubation - Studying Neo Banks and their impact on traditional banking, especially post COVID19 era. Attempting to gauge the potential challenges for Neo Banks in India.

  • UDAY KIRAN REDDY POREDDY

    Qualification: B. Tech.

    Work Experience: NA

    Contact: https://www.linkedin.com/in/udaykiranporeddy/

    RFP Company / RFP Project Title / Short Description: Loan Tap: To develop a scoring model that can help evaluate the employer of a salaried individual

    MyShubh Life: Customer acquisition & Retention, Understanding Data & Visualisation

    INSOFE:Food classification for Grocery store management

    Other projects / Accomplishments: Introduction to SQL server(certification)

    Research Incubation: Analysing financial markets using Business Analytics and Machine Learning

  • TRISHA PANICKAR

    Qualification: B. Tech.

    Work Experience: Total Exp - 4 yrs.Human Resources Manager - Hunger box

    Cost Analyst/Estimator Elimec.Ltd, Investment Analyst and Certified Financial Advisor Armstrong Capital Advisory Private Ltd.

    Contact: https://www.linkedin.com/in/rajan-trisha-panickar-05813660

    RFP Company / RFP Project Title / Short Description: CAPGEMINI Project: (Finance and Banking) - Credit Fraud Detection Model

    Other projects / Accomplishments: INSOFE Distracted Driver detection using CNN

  • UTKARSH NAYAN SATSANGI

    Qualification: B.Tech

    Work Experience: Intern in Gridlle Tech Pvt Ltd.

    Contact: https://www.linkedin.com/in/utkarsh-satsangi/

    RFP Company / RFP Project Title / Short Description: INSOFE Distracted Driver detection using CNN

    Capgemini Credit Card Acquisition Model – A model to identify potential credit card customers through Behavioural pattern.

    Other projects / Accomplishments: Research Incubation-Build a model to find the how ready are the delivery companies in Electronic City, Bangalore towards drone delivery.

  • RONIT ROY

    Qualification: B.Tech

    Work Experiance: -Project Trainee at ISRO (Jan 20 –April 21)

    -ProjectManagement Intern atOlcademy (Nov 21 – Feb 21)

    -Finance Intern at FoodVybe(Feb 21-May 21)

    -Intern atTakshashila Consulting(June- 21-1Aug 21)DerivativeResearch Intern at Alpha Derivatives(May 21-Nov 21

    Contact: https://www.linkedin.com/in/ronit-roy-profile/

    RFP Company / RFP Project Title / Short Description: LoanTap:Insurance Business Development for Fee Based Revenue:Researching on increasing revenue by selling insurance products as a Fintech & NBFC.

    Other projects / Accomplishments: Research Incubation- Estimating earnings quality for Indian stocks through mean reversion.

    HULT Prize 2021(Regional Finalist) Business Plan and research on recycling organic waste for fertiliser.

  • APURVA SUMAN

    Qualification: B.Com

    Work Experience: NA

    Contact: https://www.linkedin.com/in/apurva-suman-02390a1a7

    RFP Company / RFP Project Title / Short Description:MyShubh Life:Customer acquisition & Retention, Understanding Data & Visualisation

    Other projects / Accomplishments: Research Incubation:Predicting EV of BFSI sector through sentiment analysis and time series modeler in SPSS.Data Visualization and Communication with Tableau Certificate.

  • SAYANTAN GHOSH

    Qualification: BCom- Finance

    Work Experience: Senior Executive at Infosys Business Process Management Ltd – 28 months.Strategy Intern at Protrainy – 2 months.

    Contact: https://www.linkedin.com/in/sayantan-ghosh-1008bb1a8/

    RFP Company / RFP Project Title / Short Description: MyShubh Life:Exploratory Data Analysis

    Other projects / Accomplishments: Innovation and Incubation Program

    Developed a start-up idea in the e-commerce space to digitize the way supplies are procured by neighbourhood stores in India.

    Accomplishments: Rising Star awardee at Infosys BPM Ltd – 2019.

    Winner at Design Thinking and Innovation Exhibition, JAGSoM, 2020-21.

    Regional Finalist at HULT PRIZE Global Entrepreneurship Challenge, 2020.

    Represented Jharkhand at U-16 State Cricket Team, 2012-13.