24 Months | Accredited Degree Program

MBA IN APPLIED Data science

Accelerating your career in Data Science

24 Months | Accredited Degree Program

MBA IN APPLIED Data science

Accelerating your career in Data Science

BECOME A DATA SCIENCE MANAGER

A unique program that combines the depth of data science and machine learning to business decision making and analytics. The MBA in Applied Data Science is a 24-month experiential degree program that focuses on transforming you into a hands on skill driven, strategic Data Science Manager in today's data driven economy.
This program helps build YOUR competencies around:
1. Mastering the nuances of data science, analytics, machine learning and its industry applications and business impact.
2. Translating data analysis into actionable insights and providing recommendations through data visualiazations to create business impact and
3. Better Interlock with Data Scientists on one hand to Executive Management team on the other side.

WHO IS IT FOR!

If you want a general purpose management program - this is NOT for you!

If you are a Student, Engineer, Quality Assurance Engineer, Project Lead, Business Analyst, Financial Executive, Marketing professional, Customer Service Executive, Consultant, or a Sales Executive, who loves to apply his/her analytical thinking to uncover data driven solutions to business challenges, then this MBA is for you. If you are passionate about building a career in the hot field of data science, machine learning, Artificial Intelligence and also leverage that to drive business innovation then this course is for you.
Remember, Data Science is not just a career choice, it is a paradigm shift that is shaping the future that we are moving into.

WHY MBA in DATA SCIENCE?

BUSINESS + DATA + TECH = MBA in Applied Data Science

Industry as Hiring Partners, Global Network for Continuous Growth

Our impeccable council of industry leaders in data science is a great network for early career professionals to tap into, build their career in data science and learn the latest and greatest in the field of data science. Our Career Management Cell is not just about getting a job, its about jumpstarting with an awesome Data Science Career thats relevant!

Instead of becoming a generic business professional, build a career as a Data Science Manager

Focus is to build hands on skills in analytics and data science and the necessary business and strategic acumen to become a leader in the field of data science. You will be able to analyze business problems, ask the right questions, apply the most cutting edge computational methods, and advanced machine learning techniques to come up with data driven solutions that are high impact and actionable.

Skills based Curriculum

Our unique experiential Learning-By-Doing pedagogy, helps you acquire the required skill-sets, frameworks and mental models which are expected in the industry and builds a portfolio of demonstrable assets through data hackathons and industry internships.

Program Highlights

Focus on Applied Data Science

Practical and hands-on engagement that focuses on using data science to improve business performance and strategic decision making. McKinsey research emphasized the need for applied data science skills that combine deep analytical skills and the knowledge to make sense of this for everything from finance to marketing. The MBA program builds that combination skill set for you so that you become the first choice for hiring managers.

Industry Internships and Projects

Industry sponsored projects and internships are the finest opportunity that you will have to work on real world data problems that will create an impact for your career.

Experiential Learning through Skill Labs

Data Science Skill-labs provide a hands-on simulated platform for you to discover the ocean of data science. Skill labs is a sandbox for you to experiment and build your data science skills with real data in a real lab environment. This allows you to experience how an end to end data science algorithm is implemented from back-end to front-end. Become hands-on in Data Science technologies by working on the latest and greatest technology tools like R, Python, Flask, Spark, Hadoop, MapReduce, TensorFlow, Cloud, etc., enabled by our labs.

Program ROI

Building a portfolio of demonstrable assets, is an assured way of breaking into senior roles

Compensation Premium

Job Guarantee for full time students and Career Acceleration for working professionals.

Future proof yourself

Move up in the organization, by driving decision making through data skills.

Showcase your Data Science Portfolio

Demonstrable Assets of having worked on real world scenarios showing data, business and strategy acumen.

Network Effect

Global Industry network that can continuously propel your career beyond the current job.

Industry wants to hire professionals who not only understand the depth of data science but can leverage that to business outcomes.

Atul Batra, CTO, Manthan Systems
Industry Coach, Institute of Product Leadership

One Program, two modes

Residential Focus vs Learning while you are working

Full time Model Weekend Part time Model
Campus based Immersive Learning Online & Campus Learning
Classes Monday to Thursday Weekly Live Class, One weekend Campus
Job Guarantee Career Management Cell Resources
Industry Connect & Field Visits Industry Connect & Field Visits
3 Months Industry Internships Industry Projects
24x7 Access to Learning 24x7 Access to Learning
Management Systems and Skill Labs Management Systems and Skill Labs

Curriculum

The comprehensive Data Science curriculum is designed in collaboration with our expert industry council, veteran faculty and European Union’s EDISON group. The course is a 102 credits holistics program that equips you with the essential know how and critical skills to work on real world data science problems and build data science products. The curriculum provides concrete outcomes. The skills are mapped to job requirements in the data science space that will help you get jobs that you aspire, guaranteed!

Courses

Cutting Edge Curriculum with concrete outcomes

Industry Integrated Curriculum design by Executives and Global experts.This keeps the focus on relevant, real world scenarios and minimizes purely academic discussions.
Skillathons replaces exams and Harvard case study discussions replaces one way lectures!

Statistical paradigms(regression, time series, dimensionality, clusters)
Probabilistic representations(causal networks, Bayesian analysis, Markov nets)
Frequentist and Bayesian statistics
● Exploratory and confirmatory data analysis

● Predictive Analytics
● Inferential and predictive statistics
● Regression and Multi Analysis
● Generalised linear models
● Time series analysis and forecasting
● Deploying and refining predictive models
● Modelling and simulation theory and techniques (general and domain oriented)
● Operations research and optimisation

Big Data Cloud platforms (Azure, AWS)
Approaches to data ingestion at scale
● Parallel and distributed computer architectures (Cloud Computing, client/server, grid)
● Large scale storage systems, SQL and NoSQL database
● Computer networks architectures and protocols
● Storage for big data infrastructures and high-performance computing (HDFS, Ceph)

● Deep Learning  
● The History of Artificial Neural Networks
● Deep Learning 
● Keras
● Reinforcement Learning

● Text analytics including statistical, linguistic, and structural techniques to analyse structured and unstructured data
Data mining and text analytics
● Natural Language Processing
● Predictive Models for Text
● Retrieval and Clustering of Documents
● Information Extraction
● Sentiment analysis

● Big Data Cloud platforms (Azure, AWS)
● Approaches to data ingestion at scale
● Parallel and distributed computer architectures 
● Large scale storage systems, SQL and NoSQL databases
● Computer networks architectures and protocols
● Storage for big data infrastructures and high-performance computing (HDFS)

● Data security, accountability, protection
● 
Blockchain, and corresponding infrastructure
● Access control and Identity management
● Compliance and certification
● Data anonymization and privacy

● Decision support systems
● Data warehousing and expert systems
● Enterprise information systems (data centers, intra/extra-net)
● Multimedia information systems

● Value proposition and buyer persona
● Segmentation and Target market sizing
● 
Positioning
● 
Sales Management
● 
Pricing and monetization

● Art of Story Telling
● Decision Making
● Communication and feedback
● 
Influence and Power
● 
Conflict Management
● Change management

Getting Started with R
Manipulating data with R-EDA and Data Cleaning
Python Programming
Manipulating Data with Python
Basic Visualization with Python

● Machine learning theory
● Supervised learning methods- Linear regression, Random forest, Support vector machines Unsupervised learning methods- Clustering and Association

● Cloud Computing architecture and services
● Cloud Computing engineering (design, management, operation)
● Cloud-enabled applications development (IaaS, PaaS, SaaS, autoscaling)
● Capex vs Opex consideration

● Game theory and mechanism design
● Classification methods
● Ensemble methods
● Cross-validation

● Neural networks, deep learning and reinforcement learning
● Convolutional neural networks (CNNs)
● 
Recurrent Neural Networks (RNNs),
● Long Term Short Memory (LSTM)
● Deploying deep neural networks

● Line charts, Bar charts- grouped, stacked, Scatter, Pie, Donut, Histograms, Polars etc.
● 
Advanced charts- box, bubble, interactive charts,Violinplot and Swarmplot
● 
Using charts for storytelling
● 
Strategic data science
● 
Leveraging data for value – from data to insight
● 
Business Case studies in Data Science
● 
Data Consulting

● Big data frameworks (Hadoop, Spark, HortonWorks, others)
● Algorithms for large scale data processing methods for pre-processing data implemented in MapReduce, including problems of correct data spliting in clusters
● 
Approaches to Big Data analysis
● Algorithms for visualization of large data sets

● Introduction to Finance
● Analysis of Financial Statements & Ratio Analysis
● Profit & Loss
● Revenue Forecasting and Business Plan Modeling
● 
Capital Budgeting
● Costing

● Introduction to Strategy and strategic frameworks
● Competitor Analysis ● Distinctive Competencies & Competitive Differentiation
● 
Product Line and Portfolio ● Platform & Technology Strategy

● The capstone project is the fulcrum of the program. This project involves a 3 months internship or industry project for the part time MBA, with an organization of repute and a report that is compiled at the end of the program. The project will involve a real data science problem in a business context that students will work on.

Learning Data Science is the best investment you can make for your career

Skill Labs

Learning by Doing

Skill Labs is a sandbox to build hands on data science skills with real data in a real lab environment. This allows one to experience how and end to end data science algorithm is implemented from back-end to front-end

Admissions

How to Get Admitted to the MBA Program?

Eligibility

A Bachelor's Degree with minimum 50%. Strong analytical, critical thinking and communication skills.
0-7 years of work experience. Freshers can apply for fulltime program. Passion to build a career in Data Science!

Admission Timelines

Timelines Weekend Fulltime
Early (5% Waiver) Aug 25 Oct 25
Regular Sep 30th Nov 25
Classes Start Nov 2018 Jan 2019

● Online Classes and Material Access from the Day of Admission so it makes sense to apply early!

Admission Process

Admissions are done via the 3-step process outlined below. Please follow step 1 below to start the process. MBA cohorts typically submit applications several months before the program starts, so we urge you to start the process early. If you need any help during the process, contact us.

Application Form

Fill the online application form

Data Science Aptitude Test

Appear for the online Data Science Aptitude Test

Personal Interview

Group discussion and interview at campus

Command your compensation premium with Guaranteed Jobs in Data Science.

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