Igor Arambašić, PhD, is a senior data science leader with extensive experience managing and guiding diverse teams across multiple countries. His expertise spans people management, data science, and big data technologies, making him a versatile and accomplished professional in his field. He currently serves as the Program Director for the Master of Science in Data Science at AUG Global Campus, where he applies his deep industry knowledge to shape the next generation of data professionals.

In his industry role, Igor is the Head of the Creation Platform Data Science Unit at Amadeus IT Group, leading a team of over 20 data scientists, data engineers, and DevOps professionals. He works closely with senior executives to identify and prioritize data science opportunities, ensuring business relevance and actionable results.

His career journey reflects a steady progression through both academia and industry. He earned his Master of Science in Electrical Engineering from the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split, Croatia, in 2002. He then pursued scientific research at the Polytechnic University of Madrid (UPM), where he worked on signal processing projects and earned his PhD in Telecommunications in 2008. Transitioning to Amadeus IT Group in 2014, he advanced through roles as a data engineer, data scientist, and data science manager, eventually becoming Head of the Data Science Unit in 2019.

Beyond his industry leadership, Igor has made significant contributions to academia. He was the director and lecturer for the Master in Data Science program at KSchool in Madrid for six years and has authored 13 publications at international conferences and contributed to three book chapters. His combined expertise in both research and applied data science makes him a valuable leader in bridging academic rigor with industry innovation.

The Master of Science in Data Science at AUG Global Campus is a 12-course program designed to provide a comprehensive and flexible learning experience. Our curriculum is structured to help students build strong foundational knowledge, develop advanced data science skills, and gain specialized expertise in cutting-edge domains like Deep Learning, Generative AI, and Time Series Forecasting.

Program Structure

The MS in Data Science program follows a well-structured sequence to ensure students progressively build their knowledge and expertise. The program includes core courses, elective specializations, and a capstone project to provide a well-rounded and hands-on learning experience.

1. Intake Course: Data Science Fundamentals

All students begin their journey with Data Science Fundamentals, a critical course designed to:

• Build a strong foundation in programming, mathematics and data science tools and concepts.
• Set up a professional data science environment using tools like Python, Jupyter Notebooks, Anaconda, PySpark and Git.
• Provide hands-on experience of typical data science project covering data analysis, data manipulation, and data visualizations based on real-world datasets.
• Build confidence by empowering students to achieve early success in model-building, including regression, classification, and clustering techniques.

2. Core Courses (8 Required Courses)

These core courses ensure a comprehensive understanding of key data science principles:

• Data Science Fundamentals (Intake Course)
• Data Analysis and Statistics
• Data Engineering
• Big Data Processing & Cloud Computing
• Feature Engineering
• Advanced Machine Learning Methods
• Data Visualization and Storytelling for Business Intelligence & Decision Making
• Project Management in Data Science complying with Ethics & Responsible AI

3. Specialization Electives (Choose 3 Courses)

Students have the flexibility to customize their learning experience by selecting three specialization courses:

• Deep Learning and Neural Networks
• Generative AI Applications
• Time Series Forecasting
• Natural Language Processing
• Information Retrieval and Recommender Systems
• Business ML Applications

4. Capstone Project & Portfolio Development

The program culminates with a capstone project, where students apply their knowledge to a real-world data science challenge. This project will be:

• Industry-focused, solving real business problems with advanced data science techniques.
• Portfolio-enhancing, allowing students to showcase their projects on GitHub to boost employability.
• Mentored by experts, ensuring students receive feedback and industry insights throughout the process.

Technology Requirements:

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Develop Future-Ready Data Science Expertise

The Master of Science in Data Science at AUG Global Campus equips students with the technical, analytical, and strategic skills required to excel in today’s data-driven world. Our program-level competencies ensure that graduates are proficient in key areas such as machine learning, artificial intelligence, data engineering, and business intelligence. Whether you are aspiring to be a Data Scientist, AI Specialist, or Business Intelligence Analyst, our program prepares you to lead with confidence.

The Master in Data Science program emphasizes hands-on lab experience throughout the entire curriculum. From the early phases of the program, Data Science foundational course introduces transversal components such as setting up and managing Python environments, programming with Notebooks, version control with GitHub, creating pipelines with Kedro etc. As students progress, they engage with real datasets, learning to clean and prepare data, and build machine learning models in a lab-like environment. The program includes practical exercises and projects that utilize various Python libraries, including NumPy, Pandas, Matplotlib, Seaborn, and Scikit-Learn.

In addition to these, students gain experience with data engineering tools such as Airflow, MySQL, MongoDB, REST APIs, and BeautifulSoup, always maintaining a hands-on approach. The integration of Amazon Web Services (AWS) into the program provides students with practical experience in cloud platforms and cluster management. Throughout the program, students will collaborate in teams on GitHub projects, simulating real-world work environments and enhancing their teamwork and project management skills. This collaborative approach helps students understand the dynamics of working in professional data science teams.

From the very beginning, students are encouraged to build a portfolio of end-to-end data science solutions. They are guided to publish these projects on their GitHub accounts, showcasing their skills and expertise to potential employers.

Core Competencies

1. Data Science Fundamentals & Analytical Thinking

• Develop a strong foundation in statistics, probability, and linear algebra to understand and apply data science concepts effectively.
• Gain expertise in exploratory data analysis (EDA) to derive insights from structured and unstructured data.
• Learn how to evaluate and interpret data-driven results to make informed business decisions.

2. Programming for Data Science

• Master Python, an industry-standard programming language for data manipulation, analysis, and visualization.
• Work with key data science libraries such as NumPy, Pandas, Matplotlib, Seaborn, Streamlit, Scikit-Learn, BeautifulSoup and Git.
• Understand best practices for writing efficient and scalable code for data science projects.

3. Machine Learning & AI Implementation

• Design and implement supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning.
• Utilize state-of-the-art AI models and frameworks such as TensorFlow and PyTorch.
• Apply model evaluation metrics (accuracy, precision, recall, F1 score) to assess and optimize model performance.

4. Big Data & Cloud Computing

• Work with large-scale datasets using big data technologies such as Apache Spark, Hadoop, and SQL-based systems.
• Implement cloud-based solutions using AWS, Google Cloud, or Microsoft Azure for scalable data storage and processing.
• Learn distributed computing techniques to handle real-world, large-scale data challenges.

5. Data Engineering & Data Preparation

• Gain expertise in data preprocessing, cleaning, and transformation to ensure high-quality data inputs.
• Learn to use ETL (Extract, Transform, Load) processes for handling structured and unstructured data.
• Work with relational and non-relational databases such as MySQL, PostgreSQL, or MongoDB.

6. Business Intelligence & Data-Driven Decision Making

• Develop skills in data visualization using tools like Matplotlib, Seaborn, Plotly, and Streamlit.
• Learn to communicate data-driven insights to stakeholders through compelling storytelling.
• Apply data science to solve real-world business challenges across industries, including finance, healthcare, and e-commerce.

7. Ethics & Responsible AI

• Understand the ethical implications of data science, including bias detection, privacy concerns, and fairness in AI.
• Learn how to apply responsible AI practices to ensure transparency and accountability in machine learning models.
• Develop a strong understanding of regulatory frameworks like GDPR and CCPA.

8. Hands-On Portfolio Development & Real-World Applications

• Build a professional portfolio by working on real-world projects and case studies.
• Publish end-to-end data science solutions on GitHub to showcase your expertise to employers.
• Participate in industry-driven capstone projects that solve business-critical data problems.

Graduate Outcomes & Career Readiness

By the end of the MS in Data Science program, graduates will:

• Be proficient in designing, developing, and deploying end-to-end machine learning solutions.
• Have a competitive edge in the job market with industry-ready data science and AI skills.
• Be capable of leading data-driven decision-making processes in organizations across various sectors.
• Be prepared for roles such as Data Scientist, Data Analyst, AI Engineer, Machine Learning Engineer, Business Intelligence Analyst, (Big) Data Engineer and similar.

Join the Future of Data Science

Advance your career with the AUG Global Campus MS in Data Science and become a leader in the data revolution. Whether you are an aspiring data scientist or a professional looking to upskill, this program will provide you with the competencies needed to succeed in a world driven by data and AI.

Enroll today and shape the future with data science!

Affording Your Master of Science in Data Science at the American University of Greece Global Campus

The American University of Greece Global Campus (AUGGC) is proudly accredited by the New England Commission of Higher Education (NECHE) and authorized by the Massachusetts Board of Higher Education. As an international institution from a financial aid perspective, AUGGC students are not eligible for U.S. federal financial aid. However, we are committed to making high-quality, globally recognized education accessible and affordable.

Our base tuition is highly competitive by North American standards, and we encourage students to explore a variety of funding options, including private loans, employer tuition benefits, and other financial resources.

Our admissions team is available to discuss payment plans and help you identify the best options for making your education at AUGGC a reality.

MS in Data Science Full Degree Cost:

• European Union Resident Base Tuition: $15,300
  • With scholarships tuition can be as low as $9,753.75 for the full MS in Data Science Degree*
  • Scholarships opportunities from 25%-36% off of tuition
  • Scholarships ranging from $3.825 - $5,546
• North American National and other Nationals Base Tuition: $15,300
  • With scholarships tuition can be as low as $10,404 for the full MS in Data Science Degree*
  • Scholarships opportunities from 10%-32% off of tuition
  • Scholarships ranging from $1,530 - $4,898

*Please note that base tuition does not include technology and graduation fees. AUGGC reserves the right to adjust pricing as needed.

Ask about our special Alumni Award (15% scholarship) and our Study Abroad Ambassador Award (10%).

Our Master of Science in Data Science program is designed for ambitious professionals and aspiring data scientists looking to develop in-demand technical and analytical skills. Whether you are transitioning into data science or advancing in your current role, our program provides the tools to help you thrive in today’s data-driven world.

Ideal Candidates for the MS in Data Science:

1. Aspiring Data Scientists

• Individuals with a strong interest in analytics, programming, and machine learning.
• Recent graduates in STEM fields (Computer Science, Engineering, Mathematics, Statistics) looking to enter the data science job market.
• Career changers seeking a high-growth industry with lucrative job opportunities.

2. Professionals Looking to Upskill

• Software engineers, IT professionals, and analysts looking to transition into data science.
• Business analysts and financial professionals eager to apply data-driven decision-making to their work.
• Professionals seeking to integrate AI and machine learning into their industries (e.g., healthcare, marketing, supply chain, travel, etc).

3. Business Leaders & Managers

• Executives and managers who need to lead data-driven initiatives and make strategic decisions.
• Team leaders responsible for managing data science and analytics teams.
• Entrepreneurs who want to leverage data science for business growth and innovation.

Join the next generation of data scientists and transform your career with the MS in Data Science program at AUG Global Campus!

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The field of data science continues to offer promising career opportunities, with competitive salaries and a robust job outlook. There's a shift towards specialized roles such as machine learning engineers, data engineers, and AI/ML engineers, moving away from generalist data scientist positions. (GSD Council) with a notable demand for the following skills: 

Python is the most in-demand programming language, appearing in 78% of data scientist job postings in 2023. 

Machine learning is mentioned in 69% of job listings. 

The demand for natural language processing (NLP) skills has risen from 5% in 2023 to 19% in 2024. (365DataScience) 

Graduates of the MS in Data Science program will have an advantage in these careers in view of the skills they will develop as a result of the MS Data Science program. 

• Programming & Tool Proficiency – Master Python, Anaconda, Jupyter Notebooks, Pandas, PySpark, BeautifulSoup, Plotly, Streamlit, SQL, Tensorflow, LangChain, Git etc. 
• Data Science Fundamentals – Exploratory data analysis, regression and classification techniques with corresponding model evaluation metrics and visualizations. 
• Data Engineering – collect, store, and manage data, data wrangling, creation of pipelines, monitor model performance and data drift. 
• Big Data – Work with large-scale datasets using PySpark, and cloud computing. 
• Machine Learning & AI – Build complex ML models and work with deep learning and generative AI applications. Learn how to design experiments, evaluate adequately model performance and how to squeeze the maximum out of the available data. 
• Business Intelligence & Storytelling – Present your findings in a compelling way that drives business decisions. 
• Project Management – Understand the bigger picture, manage stakeholders, and lead data science projects in large organizations. 
• Portfolio Development – Create end-to-end data science solutions, documented on GitHub, showcasing expertise to potential employers. 

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