Master of Science in Data Science in Data Science and Artificial Intelligence
*This Impact Degree Program provides eligible students with full tuition-free scholarships for 2 years, with an assessment and administration fee of 1,000€. To begin this process, complete your online application from our website www.ebu.lu
Skilled professionals in the new technologies of industry 4.0 are highly sought-after individuals. Their ability to decipher the ever-growing complexity in the world of Data Science & A.I. is a quality that is not only more demanded but also additionally rewarded in equal measure. Data Science and Artificial Intelligence are amongst the hottest fields of the 21st century, that will impact all segments of daily life by 2025, from transport and logistics to healthcare and customer service.
The MSc Data Science and A.I. provides training in data science methods, emphasizing statistical perspectives. This Master’s Program offers extensive training on the most demand Data Science and Artificial Intelligence skills with hands-on exposure to critical tools and technologies including R, Python, Big Data, Machine Learning, Natural Language Processing, Deep Learning, and Tableau. You will receive a thorough grounding in theory, as well as the technical and practical skills of Data Science & A.I.
Teaching Methods and Style
The Master of Data Science and AI program offers everything a person needs to master these two complementary disciplines. The curriculum covers all concepts of Data Science and Artificial Intelligence helping you master the specialized skills that organizations around the world are currently seeking. This Master of Data Science and AI program covers Data Science and Artificial Intelligence skills with hands-on exposure to critical tools and technologies including R, Python, Big Data, Machine Learning, Natural Language Processing, Deep Learning, and Tableau.
Your theoretical learning will be at a high mathematical level, while the technical and practical skills you will gain will enable you to apply advanced methods of data science and statistics to investigate real-world questions.
Students will be invited to participate in campus week events and seminars once before they graduate. However, participation in more than one campus week is also allowed and encouraged. During campus week, students will complete end of term exams, visit companies and notable industries, and socialize and network with each other.
Luxembourg is not only a financial hub but a multicultural city and seat of many European institutions. Between tradition and modernity. You will be able to enjoy different landscapes of nature parks, medieval castles, and numerous hiking or mountain biking trails throughout the region. Luxembourg and the Chateau Wiltz welcome you.
Why Choose this Course?
A Data Science and Artificial Intelligence role requires an amalgam of experience, knowledge, and discernment to use the correct tools and technologies. It is a solid career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue this Dual Master’s Program in Data Science and Artificial Intelligence.
The courses presented here offer a menu of choices in each required discipline, calibrated to your skills, experience, and future goals. The Master of Data Science and AI is a one-year degree program specifically designed to prepare graduates as the next generation of IT professionals and Managers.
The aim of the Master of Science in Data Science & A.I. is to ensure that students are able to effectively engage in an increasingly globalized, diverse, and multifaceted world having acquired the requisite skills. Students will, at the end of the program, be able to confidently engage as:
Master of Science in Data Science and Artificial Intelligence Program Learning Outcomes
EBU learning goals are intended to enhance student learning in the following areas: communication, ethical reasoning, analytical skills, information technology, global outlook, critical thinking, and understanding of synergy. Upon completion of the MSc Program, graduates will among others have:
In-depth understanding of data structure and data manipulation.
Understand supervised and unsupervised learning models including linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline.
Perform scientific and technical computing using the SciPy package and its sub-packages including Integrate, Optimize, Statistics, IO, and Weave.
Gain expertise in mathematical computing using the NumPy and Scikit-Learn.
Master the concepts of recommendation engine and time series modeling.
Comprehend the principles, algorithms, and applications of Machine Learning.
Learn the applications of Artificial Intelligence across various use cases across different fields like customer service, financial services, healthcare, and more.
Implement classical Artificial Intelligence techniques such as search algorithms, neural networks, and tracking.
Learn how to apply Artificial Intelligence techniques for the problem- solving and explain the limitations of current Artificial Intelligence techniques.
Design and build your own intelligent agents and apply them to create practical Artificial.
Intelligence projects including games, Machine Learning models, logic constraint satisfaction problems, knowledge-based systems, probabilistic models, agent decision-making functions, and more.
Understand the concepts of TensorFlow, its main functions, operations, and the execution pipeline.
Master advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks, and high-level interfaces.
Analyze data using Tableau and become proficient in building interactive dashboards.
Understand the different components of the Hadoop ecosystem and learn to work with HBase, its architecture and data storage, learning the difference between HBase and RDBMS, and use Hive and Impala for partitioning.
Understand MapReduce and its characteristics, plus learn how to ingest data using Sqoop and Flume.
Understand the fundamentals of Natural Language Processing using the most popular library; Python’s Natural Language Toolkit (NLTK).
Duration: 2 Years
Credits: 90 ECTS
Format: Full-time or Part-time
Start dates: September