Applied Computer Science (Machine Learning and Big Data)
Via Medina, Italy
Master of Science in Applied Computer Science (Machine Learning and Big Data)
Parthenope University of Naples
Computer Science — Machine Learning & Big Data
Program Overview — Applied Computer Science (Machine Learning and Big Data)
The Master of Science in Applied Computer Science (Machine Learning and Big Data) at Parthenope University of Naples is a two-year program covering the mathematical, statistical, and computational foundations of machine learning alongside cutting-edge big data technologies. The program trains you to model and discover patterns from observations while mastering the tools needed to handle large-scale data environments.
Housed within the Department of Science and Technology (DiST), the program features 12 exams and a final applied-experimental thesis totalling 120 ECTS. Key topics include machine learning, deep learning, scientific computing, multimedia information processing, Internet of Things, and high-performance and cloud computing, all delivered through a hands-on, lab-intensive approach.
The program also offers an Innovation curriculum developed in collaboration with MIT Sloan School of Management, giving selected students the opportunity to earn a dual qualification in Entrepreneurship and Innovation Management. Graduates emerge as highly specialized professionals ready to work in research institutions, ICT companies, banks, insurance firms, telecommunications operators, and any organization requiring advanced data-driven solutions.
Key Program Highlights
- Hands-on curriculum covering machine learning, deep learning, cloud computing, and IoT with tools such as TensorFlow, PyTorch, and Python
- Innovation curriculum track developed in collaboration with MIT Sloan School of Management
- Compulsory internship component (6 ECTS) with access to a network of over 130 partner ICT companies
- AWS Academy membership providing industry-recognized cloud computing certifications as part of the coursework
Curriculum & Modules
The program is structured across two academic years with ten compulsory modules and two student-selected electives, complemented by a mandatory internship and a final thesis. The curriculum balances rigorous theoretical foundations with extensive laboratory work, ensuring you graduate with both conceptual depth and practical proficiency in machine learning and big data technologies.
Machine Learning
12 ECTSCovers supervised and unsupervised learning algorithms, model evaluation, feature selection, and ensemble methods. You will implement solutions using Python-based frameworks such as scikit-learn and TensorFlow.
Deep Learning
9 ECTSExplores neural network architectures including convolutional networks, recurrent networks, and generative models. Emphasis is placed on practical implementation using PyTorch and TensorFlow for real-world applications.
Scientific Computing
9 ECTSFocuses on numerical methods, optimization algorithms, and high-performance computing techniques essential for processing large datasets and solving computationally intensive problems.
Multimedia Information Processing
9 ECTSCovers techniques for analyzing and processing images, audio, and video data using machine learning approaches. Includes computer vision, speech recognition, and multimedia retrieval methods.
High Performance and Cloud Computing
9 ECTSIntroduces parallel computing paradigms, distributed systems, and cloud infrastructure. You will learn to deploy scalable machine learning pipelines using platforms such as AWS and similar cloud services.
Internet of Things
6 ECTSExamines sensor networks, edge computing, and data acquisition from IoT devices. The module connects IoT data streams to big data analytics and machine learning models for smart applications.
Elective Courses
Admission Requirements
Admission to the Master's program is open to holders of a bachelor's degree or equivalent qualification from any accredited institution worldwide. Candidates must demonstrate adequate curricular preparation in computer science, mathematics, and physics. All applications and inquiries are processed through Uni4Edu.
Academic Requirements
- Degree RequirementBachelor's degree (or equivalent) in any discipline from an accredited institution
- Computer Science CreditsMinimum 22 ECTS (or equivalent) in Computer Science (INF/01)
- Mathematics CreditsMinimum 15 ECTS (or equivalent) in Mathematics (MAT/01–MAT/09)
- Physics CreditsMinimum 5 ECTS (or equivalent) in Physics (FIS/01–FIS/08)
- Total Prerequisite CreditsMinimum 45 ECTS distributed across the above subject areas
Language Requirements
- English ProficiencyMinimum B2 level (CEFR) — verified during the admission process
- IELTS (if applicable)Minimum overall band score of 5.5 (or equivalent)
- Italian LanguageNot required; the program is taught in English
Required Documents
Application Deadlines
For personalized admission guidance, document verification, and application support, please contact Uni4Edu
Scholarships & Funding
Several funding opportunities are available to support international and domestic students pursuing the Applied Computer Science master's program at Parthenope University of Naples. Financial support is administered through regional agencies and university-level initiatives. Contact Uni4Edu for personalized guidance on eligibility and application procedures.
ADISU Campania Regional Scholarship
The Campania regional agency for the right to university study (ADISURCampania) offers merit- and income-based scholarships covering tuition waivers, housing support, and meal subsidies for eligible students.
For detailed tuition fee information, please contact Uni4Edu — we will guide you through the costs and available funding options for this program.
Career Prospects
Graduates of this program are highly sought-after professionals equipped to design, develop, and manage advanced IT solutions powered by machine learning and big data. The global machine learning market continues to grow at over 40% annually, and demand for specialists far exceeds supply, particularly in Italy where the AI market doubles every year. The program also provides a strong foundation for doctoral studies and research careers.
Potential Job Roles
Typical Employer Sectors
Rankings & Recognition
Parthenope University of Naples is featured in the most prominent international university ranking systems, including QS World University Rankings, Times Higher Education, and U.S. News Global Universities. The university's Department of Science and Technology has active research output in artificial intelligence, machine learning, and computer vision, contributing to its growing international reputation.
| Subject | Ranking Body | Rank |
|---|---|---|
| Computer Science | EduRank | #1498 World / #56 Italy |
| Mathematics | EduRank | #1441 World / #53 Italy |
| Engineering | EduRank | #1680 World / #54 Italy |
| Business & Economics | THE Subject Rankings | #401+ |
How to Apply
Applying for this program is easy with Uni4Edu. Our team will guide you through every step of the process — from document preparation to final enrolment.
Contact Uni4Edu
Reach out to our team via email or phone. We will assess your profile and confirm your eligibility for this program.
Prepare Your Documents
Our advisors will provide you with a personalised checklist of required documents and help you prepare your application package.
Submit Your Application
Uni4Edu will submit your application on your behalf and keep you updated on its progress throughout the review period.
Receive Your Offer
Once accepted, we will help you understand your offer, arrange visa support if needed, and guide you through the enrolment process.
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