LEVEL 7 · EQF / MQF TOP-UP PROGRAMME

Master of Science in
Data Science and AI (Top-up) by EU Global, Malta

Master of Science (MS) in Data Science and AI (Top-up) by EU Global at Eduwatts is an advanced level programme that offers an in-depth understanding of Data Science and AI evaluated through project-based assessments and a Capstone Consulting Project. It is designed to provide in-depth knowledge and combine technical expertise, analytical thinking and AI innovation.

Duration

6–12 Months

Credits

30 ECTS

Mode

Online / Blended

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Awarding Body: EU Global, Malta Eduwatts Role: Admission Partner

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Overview Who Is It For MS Edge Accreditation Curriculum Certifications Apply What You'll Learn Career Impact Eligibility FAQs

Is This Program For You?

Who should pursue an MS in Data Science & AI (Top-up) Programme?

The Master of Science (MS) in Data Science and AI (Top-up) is designed to provide in-depth knowledge and combine technical expertise, analytical thinking, and AI innovation.

Data Analysts

Individuals seeking to strengthen their skills such as data interpretation, predictive analytics, and data-driven decision-making.

Software Developers & Engineers

Professionals who want to integrate artificial intelligence, machine learning, and advanced analytics into software solutions and digital products.

Business Leaders & Managers

Leaders and managers who are interested in using data insights and AI technologies to boost organizational growth.

Career Transition Professionals

Individuals who are interested in transitioning into the high-demand roles within data science and artificial intelligence.

The Master of Science (MS) in Data Science and AI (Top-up) edge: Outcomes that only we deliver

Our goal is not only to deliver a master’s degree but to architect global impact careers. Backed by international academic accreditations, pathways and industry integration, we ensure that you achieve outcomes that truly differentiates you at the highest level of data science, artificial intelligence, and digital innovation.

Advanced Data Science Expertise

30 ECTS Credits Towards Advanced Expertise

Artificial Intelligence and Machine Learning Proficiency

Develop Expertise in Data Preprocessing, Cleaning, and Feature Engineering

Industry-Relevant Technical Competencies

Leadership in AI and Digital Transformation

Data-Driven Decision-Making Mindset

Accreditations & Affiliations

Recognised and accredited by leading global bodies, ensuring your qualification holds international value.

Curriculum for MS in Data Science and AI

A comprehensive programme spanning 13 modules — from statistics and programming through deep learning, NLP, big data, and a hands-on Capstone Consulting Project.

Data Collection and Types of Data
Descriptive Statistics and Data Summarisation
Correlation and Regression Analysis
Probability Theory and Distributions
Time Series Analysis
Sampling Methods and Survey Design
Confidence Intervals and Estimation
Hypothesis Testing
ANOVA and Experimental Design
Non-Parametric Statistical Methods

Vector Spaces and Linear Algebra
Matrix Operations and Transformations
Orthogonality and Projections
Matrix Decomposition (SVD, PCA)
Differential Calculus and Partial Derivatives
Optimization Techniques
Convex Optimization
Gradient Descent and Variants
Bayesian Estimation and Inference
Mathematical Modeling for Machine Learning

Python Fundamentals and Environment Setup
Variables, Data Types, and Control Flow
Functions and Object-Oriented Programming
File Handling and Data I/O
NumPy and Pandas for Data Analysis
Data Transformation and Aggregation
Time Series Analysis with Python
Data Cleaning and Preprocessing
Data Visualisation with Matplotlib and Seaborn
Interactive Dashboards and Reporting

Introduction to Tableau and Interface Navigation
Data Connections and Source Management
Filtering, Sorting, and Grouping
Calculated Fields and Parameters
Data Blending and Joining
Level of Detail (LOD) Expressions
Distribution Charts and Statistical Visuals
Forecasting and Trend Analysis
Advanced Analytics and Table Calculations
Storytelling and Dashboard Design

Foundations of Artificial Intelligence
Introduction to Machine Learning
Supervised Learning Algorithms
Unsupervised Learning Algorithms
Classification Techniques
Clustering and Dimensionality Reduction
Evaluation Metrics and Model Selection
Hyperparameter Optimisation
Deep Learning Fundamentals
AI Applications in Industry

ML Workflow and Project Lifecycle
Data Preparation and Feature Engineering
Regression Models with Scikit-learn
Classification Models and Decision Trees
Ensemble Learning (Random Forest, XGBoost)
Advanced Feature Engineering
Model Validation and Cross-Validation
Performance Optimisation Techniques
Model Deployment with Flask / FastAPI
Industry Applications and Case Studies

Deep Learning Foundations and Perceptrons
Artificial Neural Networks (ANNs)
Convolutional Neural Networks (CNNs)
Image Feature Extraction and Pooling
Recurrent Neural Networks (RNNs)
Sequence Modeling and Time-Series Deep Learning
Long Short-Term Memory (LSTMs)
Advanced DL Architectures (ResNet, Attention)
Training Strategies and Optimisation
Real-World Deep Learning Applications

Computer Vision Fundamentals
Image Processing and Filtering
Feature Detection and Extraction
Object Detection (YOLO, SSD)
Image Classification with CNNs
Image Segmentation Techniques
Facial Recognition Systems
Video Analytics and Motion Detection
Vision-Based AI Applications
Computer Vision Projects and Deployment

Introduction to NLP and Text Data
Text Preprocessing and Tokenisation
Linguistic Analysis and POS Tagging
Text Classification Techniques
Sentiment Analysis and Opinion Mining
Information Extraction and Named Entity Recognition
Language Modeling (n-grams, Word2Vec)
Transformer Architectures (BERT, GPT)
Conversational AI and Chatbots
NLP Applications in Business

Big Data Ecosystem Overview
Distributed Computing Concepts
Hadoop and HDFS Architecture
Apache Spark and Spark SQL
NoSQL Database Concepts
Document and Graph Databases (MongoDB, Neo4j)
Data Storage Architectures (Data Lake, Lakehouse)
Building Big Data Pipelines
Real-Time Analytics (Kafka, Streaming)
Enterprise Big Data Solutions

Data Warehousing Fundamentals
Data Modeling (Star and Snowflake Schemas)
ETL Processes and Pipelines
Data Integration Strategies
Data Governance Frameworks
Master Data Management (MDM)
Data Quality and Profiling
Business Intelligence Systems
Data Security and Compliance
Enterprise Data Architecture

Foundations of Academic Research
Research Design and Methodology
Literature Review and Citation Management
Quantitative Research Methods
Qualitative Research Methods
Data Collection Strategies
Statistical Analysis and Interpretation
Academic Writing and Publication
Research Ethics and Integrity
Dissertation Development and Planning

Problem Identification and Scoping
Business Requirement Analysis
Project Planning and Timeline
Data Collection and Preparation
Solution Design and Architecture
Model Development and Implementation
Testing and Validation
Business Impact Assessment
Final Report and Documentation
Presentation and Defense

Certifications & Credentials

Earn globally recognised certifications alongside your MS degree — adding professional credibility and market value to your qualification portfolio.

Get PwC Directorship Certification

Fee: ₹10,000

Designed For

Mid to senior level professionals aspiring to attain expertise in Data Science and Artificial Intelligence through immersive and practice driven learning aligned with PwC frameworks

Intensive Curriculum

For AI ethics, governance, machine learning, deep learning techniques and responsible innovation.

Outcome Highlights

Advanced proficiency in data science, AI, machine learning, and digital transformation.

MS Degree Certificate - European Global Institute

Earn Master of Science (MS) in Data Science and AI (Top-up) from European Global Institute of Innovation & Technology

Earn Master's Degree

Get your MS degree from globally recognised European Global Institute of Innovation & Technology, Malta.

International Accreditations

Attain certification from an institute with EQF Level 7, MFHEA, and European ECTS-based accreditations & partnerships.

Stand Out In Your Resume

Complete your Capstone Consulting Project and earn a credential that elevates your data science and AI profile globally.

Government-Recognized NSDC Certification

Govt. Recognised

Upon completion of this MS program you shall be awarded with an additional Certification from NSDC — recognised by the Indian Ministry of Skill Development.

National Skill Development Corporation certified credential

Recognised by Ministry of Skill Development & Entrepreneurship

Enhances employability in India and globally

NSDC Certificate - Government Recognised

How Can You Apply for an Online MS Program?

Our simple 5-step application process ensures you can enrol quickly and begin your MS in Data Science and AI journey without any hassle.

Submit an Online Application

Complete the online application form with your personal details, academic qualifications, and programme preferences.

Attend a Screening Call

Our admissions counsellors review your profile, conduct a guidance call, and confirm your eligibility for the MS programme.

Get Your Offer Letter

Receive your official offer letter confirming your admission to the MS programme with all details.

Pay the Fee and Enroll

Pay your programme fee (EMI options available) and receive your official enrolment confirmation with student credentials.

Begin with Your Programwork

Access the learning management system, join your first live class, meet your academic mentor, and officially start your MS in Data Science and AI.

Apply Now →

What Will You Learn in an MS in Data Science & AI?

The MS in Data Science and AI equips you with the technical depth, analytical rigour, and strategic mindset needed to lead data-driven transformation at the highest level.

Data Science Foundations

Learn the advanced skill of statistics, mathematics, and analytical techniques used for data-driven decision-making.

Programming and Analytics

Develop expertise in Python programming for data analysis, automation, and machine learning applications.

Artificial Intelligence and Machine Learning

Master the concept of AI, machine learning methods, and advanced neural network architectures for intelligent problem-solving.

Big Data and Emerging Technologies

Gain expertise in Big Data, NoSQL databases, data warehousing, computer vision, and natural language processing.

Outcomes That Matter

Career Impact & Professional Outcomes

A Master of Science (MS) in Data Science and AI (Top-up) Programme opens doors that simply were not accessible before — not merely because of the credential itself, but because of the transformation in thinking, capability, and confidence that the master’s journey produces. Master of Science (MS) in Data Science and AI (Top-up) graduates consistently report significant career advancement, increased professional authority, and a dramatically expanded professional network as direct outcomes of their master’s journey.

99%

Career Advancement

of Master of Science (MS) in Data Science and AI (Top-up) graduates report significant career advancement within two years of graduation.

98%

Salary Increase

of Mof Master of Science (MS) in Data Science and AI (Top-up) graduates receive a substantial salary increase or promotion within 18 months of graduation.

55%

Board Appointments

of Master of Science (MS) in Data Science and AI (Top-up) graduates take on board-level, advisory, or nonexecutive director roles within five years of graduation.

Research Impact

of Master of Science (MS) in Data Science and AI (Top-up)-generated organizational research projects yields on average at least three times the measurable business impact of non-Master of Science (MS) in Data Science and AI (Top-up) consulting engagements.

Career Pathways

Data Scientist ML Engineer AI Researcher Data Architect Chief Data Officer AI Product Manager

Entry Requirements

Eligibility to Enroll in an MS in Data Science & AI (Top-up) Programme?

The candidate must meet the following criteria to enroll in a in Data Science and AI (Top-up) Programme:

Entry Criteria

Basic Eligibility

English language proficiency requirements (if applied via institution)
Clearing an admission interview or research proposal evaluation (as per the norms of the institution)

Academic Qualification

Relevant bachelor's degree with basic mathematical knowledge and English proficiency from a recognised university

Professional Experience

Minimum 3–5 years of professional experience in data science or specialised roles preferred

Mandatory Documents

Mandatory documents you need to apply for the MS in Data Science and AI (Top-up) programme:

Completed application form

Official academic transcripts

Updated resume / CV

Statement of Purpose (SOP)

Letters of recommendation

GRE / GMAT scores (if required)

Proof of English proficiency (IELTS / TOEFL) or a dissertation writing sample (for international applicants)

Frequently Asked Questions

The programme is designed to be completed within 6–12 months, depending on the learner’s pace, academic background, and other requirements.

The curriculum spans 13 comprehensive modules:

Module 1: Statistics for Data Science
Module 2: Mathematics for Data Science
Module 3: Programming for Analytics using Python
Module 4: Data Visualisation and Storytelling with Tableau
Module 5: Artificial Intelligence and Machine Learning
Module 6: Machine Learning Methods using Python
Module 7: Convolutional and Recurrent Neural Networks
Module 8: Computer Vision and Image Recognition
Module 9: Natural Language Processing
Module 10: Big Data and NoSQL
Module 11: Data Warehousing and Management
Module 12: Research Methods
Module 13: Capstone Consulting Project

EU Global awards the Master of Science (MS) in Data Science and AI (Top-up) qualification. The programme is designed to develop advanced knowledge and skills in Data Science and Artificial Intelligence.

Yes. Learners will complete a Capstone Consulting Project that allows them to establish their understanding of Data Science and Artificial Intelligence concepts while solving real-time industry problems./p>

Master of Science in Data Science and AI (Top-up) by EU Global, Malta