JAIN | UCAM
Global Campus
School of Global Studies

/Programme Overview

The Bachelors (BS) and Masters (MSc) programme in Data Analytics and Applied Artificial Intelligence is an industry-aligned, globally benchmarked, practically oriented programme offered by School of Global Studies, JAIN (Deemed-to-be University) in partnership with UCAM University, Spain. The programme enables learners to progress from mathematical and computational foundations to Building and Deploying Predictive Analytical Solutions and Production-Grade AI Systems.

/Key Programme Features

Practical-Oriented

Over 60% of the programme consists of practical lab components including code, dashboards, and deployed models

Industry-Embedded

Integrated internships and apprenticeships with real-time industry exposure and mentor scorecards

Learning-to-Product

Focus on developing publishable artefacts and deployable solutions through an applied research continuum

Micro-credential Stack

Job-readiness via industry badges and skill certifications integrated directly into the academic curriculum

Entrepreneurial Approach

Studio-style labs and masterclasses to support idea-to-product incubation and startup development

Domain-Embedded Tracks

Deep dives into AI applications for specialized sectors like FinTech, Health, Retail, and Manufacturing

/Global Academic Exposure

International Immersion :
Spain | Dubai | Australia | Vietnam

Real-World industry projects

Global Semester / Short-term Exchange
@ UCAM, Murcia, Spain

/9x9 Teaching and Learning Model

Methodology and Innovation.

01

Advanced Pedagogy Framework

Embedded with Advanced Pedagogical Practices to enhance knowledge retention, skill orientation, digital dexterity, entrepreneurial mindset, ability enhancement and development of integrative competencies

02

Design-to-Product Studios

Design-to-Product Studios to develop systems thinking and solutions mindset starting each project with a creative problem, defining KPIs, building the feature / solution plan and culminating in deployable solutions

03

Production-Grade Learning

Production-Grade Learning Practices to help learners align their outcomes to industry needs and approaches through reviews, tests, experiment tracking, end-point inferencing, and continuous monitoring

04

Real-World Case Learning

Real-World Case with Indian and Global problem statements (open and partner -provided) to align all learning to create impactful industry and societal outcomes

05

Dual-Mentor Model

Dual-Mentor Model by engagement of academic and industry mentors for studios, projects, internships and apprenticeships

06

Innovative Assessment Mix

Innovative Assessment Mix to evaluate development of skills and competencies that include 50% continuous assessments, 20% multi-term practical and 30% final demo / jury / viva / product or solution pitch with reproducible artefacts

07

Safety Clinics and Research Hotspots

Safety Clinics and Research Hotspots to enhance research-based learning and learning while doing through red-teaming sessions, hackathons and ideathons, incident post-mortems, and publishable and patentable works approach

08

Global Masterclasses

Global Masterclasses conducted by faculty and industry experts from across the globe, entrepreneur shadowing week, etc

09

Learning Analytics and Competency Transcripts

Learning Analytics and Competency Transcripts to get a better understanding of real outcomes through the learning journey, enabling students to course-correct and do remedials for better learning experience

/Programme Educational Objectives

Analytics and Applied AI Careers

Graduates will build successful careers as data analysts, business intelligence professionals, data scientists, applied ML experts, data engineers, or related roles by applying strong foundations in statistics, computing, and applied AI

Data-to-Decision
Capability

Graduates will design and implement data-driven solutions across the full lifecycle—data acquisition, cleaning, exploration, modelling, visualisation, and communication—for real-world industry and societal problems

Responsible and Ethical Data Practice

Graduates will demonstrate ethical responsibility in designing, developing, and deploying AI systems, with deep sensitivity to privacy, bias, fairness, security, accessibility, and long-term sustainability

Industry and Domain
Impact

Graduates will contribute meaningfully across domains such as BFSI, retail, healthcare, manufacturing, media, sports, telecom, and public services through industry-aligned projects, internships, and solution-building

Lifelong Learning and
Growth

Graduates will pursue continuous lifelong learning, professional certifications, advanced studies, and evolving tool competence in response to rapid shifts in analytics platforms, AI techniques, and dynamic enterprise needs

/Learning Outcomes

Mathematical and Statistical Foundations
Apply mathematics, probability, statistics, and linear algebra to analyse data and support AI and ML modelling
Computing and Programming Proficiency
Develop efficient programs and analytical workflows using appropriate languages, libraries, and tools for data and ML tasks
Data Acquisition and Modelling
Collect, integrate, clean, and transform structured and unstructured data using sound data modelling practices
Exploratory Data Analysis and Visualisation
Perform EDA to extract insights and communicate findings through effective visual analytics and storytelling
Applied Machine Learning
Build, evaluate, and interpret ML models for prediction, classification, clustering, and recommendation using appropriate metrics
Domain-Oriented Problem Solving
Translate domain problems into analytical or AI tasks, define measurable objectives, and propose viable solution strategies
Model Evaluation and Experimentation
Design experiments, validate models, handle overfitting/underfitting, and perform error analysis for continuous improvement
Tools, and Deployment
Use modern analytics tools and demonstrate foundational awareness of deployment and automation workflows
Collaboration and Project Management
Work effectively in teams, manage analytical projects with iterative methods, and maintain clear documentation
Communication and Professionalism
Communicate analytical insights and AI outcomes to technical and non-technical stakeholders through reports, dashboards, and presentations
Ethics, Privacy, and Responsible AI
Identify ethical risks and apply responsible practices in data collection, model design, and AI usage
Innovation and Lifelong Learning
Demonstrate readiness to adapt to new methods, tools, and domain demands, including entrepreneurial and innovation pathways

/Learning Arenas

/Curriculum Structure

Future-Ready Programmes Across Disciplines:

    • Mathematics I (Discrete Mathematics)
    • Programming Basics and Python
    • Data Literacy and Visualisation
    • Logic and Calculus for Data Science
    • Mathematics II (Probability and Statistics)
    • Data Structures and Algorithms
    • Databases with SQL
    • Data Visualisation and Storytelling

    • Software Engineering Basics and APIs
    • Mathematics III (Probability and Statistics 2 and Statistical Learning)
    • Data Engineering I (ETL and Data Warehousing)
    • Introduction to Machine Learning and AI
    • Responsible AI and Data Governance
    • Machine Learning Systems (Feature Stores, Eval, Leakage)
    • Time Series and Forecasting
    • Experimental Design and Inferencing
    • Data Engineering II (Spark and Data Lakes)

    • Deep Learning I (CNN / RNN and Representation Learning)
    • Natural Language Processing I (Tokenisation, Classic and Neural)
    • Cloud for Data Analytics and AI
    • MLOps
    • Recommender Systems
    • Graph Analytics
    • Steaming and Real-Time Analytics
    • Privacy-Preserving Analytics

    • Advanced Machine Learning and Applied AI
    • Deep Learning II (Advanced Deep Learning Systems, Transformers and GenAI)
    • Optimisation for Large-Scale Learning
    • Generative AI
    • Causal Inference and Uplift Modelling
    • Research Methods and Scientific Writing
    • Applied Research or Industry Research Practicum
    • Capstone Project / Graduate Project / Internship

/Academic Backbone

SoGS is academically anchored by JAIN (Deemed-to-be) University and UCAM University, Spain, ensuring strong governance, academic rigor, and institutional credibility.

JAIN (Deemed-to-be University) India's fastest-growing university

  • 35+ years of educational excellence
  • 30,000+ students across multiple campuses
  • Strong emphasis on entrepreneurship, research and sports

UCAM Spain Europe's innovation-driven Catholic university

  • Founded 1996 | Murcia, Spain
  • 16,000+ students from 115+ countries
  • International ranking for excellence in education

/Global Education Blogs and Insights

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