MBA – Analytics & Data Science

MBA - Analytics & Data Science

Program Highlights

Preface: Digital India’s data explosion & Analytics

India is experiencing a data revolution. As a nation brimming with digital adoption and a young, tech-savvy population, data generation is at an all-time high. This surge creates a massive opportunity for Analytics & Data Science. From driving business strategies to tackling social challenges, data-powered insights are transforming every sector. With a growing demand for skilled professionals, this field offers exciting prospects. Emerging trends like Artificial Intelligence and Big Data further amplify the potential of data science, shaping the future of decision-making in India.

In today's data-driven world, organizations are increasingly seeking professionals who can extract meaningful insights from vast amounts of information. The Work Integrated MBA - Analytics & Data Science equips you with the skills and knowledge to become a sought-after expert in this dynamic field. This unique program combines the strategic acumen of a traditional MBA with the technical expertise of data science, preparing you to lead and innovate in the age of big data.

An MBA with a difference - Work Integrated Learning

An MBA in Digital Marketing with Work Integrated Learning offers a unique blend of academic rigor and practical experience. This format empowers students to immediately apply classroom-learned concepts, strategies, and tools to real-world marketing challenges within their organizations. By bridging the gap between theory and practice, WIL programs accelerate skill development and provide a tangible competitive advantage in the job market.

In a rapidly evolving digital landscape, the importance of continuous learning and adaptability is paramount. A WIL program enables students to stay current with the latest trends and technologies. The scope of such a program extends far beyond core digital marketing principles. It fosters strategic thinking, data analysis, and communication skills, all of which are highly valued in a multitude of industries.

For students, this represents an opportunity to gain valuable experience, build a professional network, and potentially secure advancement within their current companies while simultaneously earning their MBA degree.

Executive Summary

The MBA in Analytics & Data Science with Work Integrated Learning is a pioneering program designed to equip students with the knowledge and skills required to excel in the dynamic field of data analytics and business intelligence. Through a combination of rigorous academic study and practical, hands-on experience gained through work-integrated learning, students will develop a deep understanding of analytics techniques and their application in real-world business scenarios. This program is structured to meet the growing demand for professionals who can harness the power of data to drive strategic decision-making and innovation across industries.

Program Overview

The MBA in Analytics & Data Science with Work Integrated Learning is a comprehensive two-year program offered by [Institution Name]. The program is designed to provide students with a solid foundation in business management principles, combined with advanced training in analytics and data science. Throughout the program, students will have the opportunity to work on real-world projects, gaining valuable experience and building a professional network in the industry.

Advantage – MBA – League from the rest

Features Work Integrated learning Traditional Education
Learning Focus
Real World Experience + Theory
Theory Imparted in Classroom Environment
Learning Environment
In Real World Workplace
Classroom Environment
UGC + Industry Recognised
UGC Recognised
3 Years
3 Years
Knowledge Application
70% practical + 30% Theory
70% Theory + 30% Practical
Industry Readiness
Skill & Personality Development
Industry Professionals + Academics
Industry Professionals + Academics
Not Flexible
Domain Focused
Generic Academic Program
From Day 1
No Internships Provided
Upto Rs. 10000/- per Month
No Stipends
Industry Experience
3 years of Industry Experience Certification
No Experience at Passout
No Guarantee
Industry Oriented

Methodology & Structure

The program employs a blend of theoretical learning and practical application to ensure that students develop both the knowledge and skills necessary to succeed in the field of analytics and data science. Courses are taught by industry experts and experienced faculty members who bring real-world insights into the classroom. The curriculum is structured to cover a wide range of topics, including statistical analysis, machine learning, data visualization, and business intelligence.

Program Outcomes

Curriculum Design

The curriculum is designed to provide students with a comprehensive understanding of analytics and data science, while also ensuring they develop the necessary business acumen to succeed in managerial roles. Courses are structured to cover both foundational concepts and advanced topics in analytics, including predictive modeling, data mining, and big data analytics. Students will also have the opportunity to specialize in areas such as marketing analytics, financial analytics, or operations analytics.

Semester 1 : Detailed Curriculum

Introduction to Analytics and Data Science
  • Overview of analytics and data science
  • Historical perspective and evolution
  •  Importance in business decision-making
Statistics for Data Analysis
  • Descriptive statistics
  •  Probability distributions
  • Hypothesis testing
  •  Regression analysis
Data Visualization and Storytelling
  • Principles of data visualization
  • Tools and techniques for effective visualization
  • Communicating insights through storytelling
  • Best practices in data presentation
Foundations of Business Management
  • Organizational behavior
  • Strategic management
  • Marketing management
  • Financial management
Programming for Data Science
  • Introduction to programming languages such as Python or R
  • Basic syntax and data structures
  • Data manipulation and analysis
Business Communication Skills
  • Written and oral communication
  • Presentation skills
  • Business correspondence
  • Negotiation and conflict resolution

Semester 2: Advanced Analytics

Machine Learning Algorithms
  • Supervised learning algorithms (e.g., linear regression, logistic regression)
  • Unsupervised learning algorithms (e.g., clustering, dimensionality reduction)
  • Ensemble methods (e.g., random forests, gradient boosting)
Big Data Analytics
  • Introduction to big data technologies (e.g., Hadoop, Spark)
  • Data pre-processing and cleaning
  • Distributed computing
Predictive Modeling
  • Model evaluation and selection
  • Feature engineering
  • Cross-validation techniques
Optimization Techniques
  • Linear programming
  • Integer programming
  • Non-linear programming
  • Optimization in business decision-making
Marketing Analytics
  • Customer segmentation
  • Market basket analysis
  • Customer lifetime value
  • Marketing mix modeling
Financial Analytics
  • Risk analysis
  • Portfolio optimization
  • Fraud detection
  • Algorithmic trading

Semester 3: Specializations and Electives

Specialization Course 1: Marketing Analytics
  • Advanced customer analytics
  • Social media analytics
  • Digital marketing analytics
Specialization Course 2: Financial Analytics
  • Credit risk modeling
  • Financial forecasting
  • Asset pricing models
Specialization Course 3: Operations Analytics
  • Supply chain analytics
  • Inventory optimization
  • Quality control and Six Sigma
Elective Course 1
  • Topics may include healthcare analytics, sports analytics, or other emerging areas in analytics and data science.
Elective Course 2
  • Topics may include text mining, image recognition, or other advanced data science techniques.
Capstone Project Preparation
  • Proposal development
  • Literature review
  • Project planning and timeline

Semester 4: Capstone Project and Internship

Capstone Project Execution
  • Implementation of the proposed analytics solution
  • Data collection and analysis
  • Iterative development and refinement
  • Presentation of findings and recommendations
Internship/Work Integrated Learning
  • Placement with industry partners for practical experience
  • Application of analytics skills to real-world problems
  • Mentorship and guidance from industry professionals
  • Reflection and learning synthesis
Professional Development
  • Career planning and goal setting
  • Networking and job search strategies
  • Resume writing and interview skills
  • Personal branding and online presence
  • Final Presentation and Evaluation
Presentation of capstone project findings to faculty and industry mentors
  • Evaluation of internship performance by industry partners
  • Assessment of overall learning outcomes and competency development
Elective Course 2
  • Topics may include text mining, image recognition, or other advanced data science techniques.
Capstone Project Preparation
  • Proposal development
  • Literature review
  • Project planning and timeline

This comprehensive four-semester curriculum provides students with a solid foundation in analytics and data science, along with opportunities for specialization and practical experience through internships and capstone projects. It equips graduates with the skills and knowledge necessary to excel in a variety of roles in the rapidly growing field of analytics and data-driven decision-making.

Benefits to Students

Benefits to Industry

On the Job Training Model

The program incorporates a unique work-integrated learning model, which allows students to gain practical experience through internships, industry projects, and on-the-job training opportunities. Students are placed with industry partners for a period of time, where they work on real-world projects under the guidance of experienced professionals. This hands-on experience not only enhances students' learning but also provides them with valuable insights into the industry and helps them develop essential skills for their future careers.

Assessments & Examinations

Assessment in the program is designed to evaluate students' understanding of key concepts and their ability to apply analytical methods to solve real-world problems. Assessments may include:

Overall, the MBA in Analytics & Data Science with Work Integrated Learning offers a unique opportunity for students to gain the knowledge, skills, and experience needed to excel in the rapidly evolving field of analytics and data science. By combining rigorous academic study with practical, hands-on learning, the program prepares students for successful careers as data-driven business leaders and innovators.

Internships & Course Fees

Internships are a vital component of our program, allowing students to gain practical experience and make meaningful connections within the industry. Through our network of partner organizations, students have the opportunity to intern at prestigious software companies and corporates both locally and internationally.

During their internships, students work closely with industry mentors, gaining hands-on experience in various departments such as front office, housekeeping, food and beverage, and sales. These immersive experiences not only enhance students' skills but also provide valuable insights into different aspects of Business analytics operations.

Stipend during Internships

During your internship as part of our Work Integrated MBA in Analytics & Data Science you may be eligible to receive a stipend from our partner companies. These stipends are designed to support you financially while you gain valuable hands-on experience in the field. While stipend availability may vary depending on the internship placement and company policy, we strive to provide opportunities that offer fair compensation for the contributions. Additionally, the stipend serves as recognition of your dedication and commitment to professional development, further enhancing your overall internship experience. Students can also use this stipend for financing their Course Tuition Fee, in such case, equivalent Installment of Tuition fee amount would be deducted automatically at the end of the month.

Stipends amount

Vary from Rs. 10000/- per month to Rs. 15,000/- per month. Certain companies also provide Boarding & lodging facilities only in certain cases as per company policy. However the same is as per Company policies and may not be provided to all students

Course Fees

We understand that investing in education is a significant decision, and we are committed to providing exceptional value to our students. Our program offers competitive tuition fees, along with various financial assistance options, including scholarships, grants, and student loans.

Fee Details Year 1 Year 2 Total
Admission Fees
₹ 10,000

₹ 10,000

Tuition Fees
₹ 90,000
₹ 90,000

₹ 1,80,000

Exam Fees
₹ 10,000
₹ 10,000



₹ 1,10,000

₹ 1,10,000

₹ 2,10,000

Students Availing Work Integrated programs need to pay only 1st Semester fees and the remaining 5 semester fees would be adjusted against the stipend availed by the student. Student need not pay entire annual fees, if they avail this facility.


The program is delivered in Six Semesters – i.e 2 Semesters a year
Student has to Pay Rs. 10,000/- on Admission with the University in first year
1st Semester Fees of Rs. 25,750/- Need to be paid  by Student before beginning of OJT (On Job Training)

Program Fee:

₹ 2,10,000


2 years (4 semesters)

Program Starts:

15th September, 2024

Degree From:

Centurion University

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