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MASTER OF SCIENCE IN ARTIFICIAL INTELLIGENCE AND BIG DATA

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About Course

A Master of Science program in Artificial Intelligence and Big Data is typically a two-year curriculum that combines elements of computer science, mathematics, statistics, and sometimes more specific fields like bioinformatics or finance. It is an interdisciplinary program designed to provide in-depth training in AI and Big Data, from fundamentals to advanced concepts.

The goal of this Master's program is to prepare students to become experts in Artificial Intelligence and Big Data. They should be able to understand, develop, and apply AI techniques and large-scale data management in a professional context. The skills acquired should enable students to solve complex problems in various fields, ranging from technology to finance to health.

Graduates of this program are highly sought after and can find jobs in a variety of industries. Here are some examples of possible careers:

Data Scientist : Data scientists are experts in manipulating and analyzing data. They use their skills to uncover insights and trends that can help businesses make informed decisions. Artificial Intelligence Engineer : AI engineers design and develop AI systems to solve specific problems. They may work on voice recognition, recommendation, prediction systems, and much more. Big Data Specialist : These professionals are responsible for managing and analyzing large amounts of data. They may work on issues such as data storage, large-scale data analysis, and developing new methods for processing data. AI and Big Data Consultant : These individuals may work with companies to help them integrate AI and Big Data into their operations. This may involve advising on how to implement AI, developing strategies for using Big Data, and training staff on the use of these technologies. AI/Big Data Researcher : Some graduates may choose to pursue a career in research, developing new methods and technologies in AI and Big Data.

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What Will You Learn?

  • Foundations of Artificial Intelligence
  • Machine Learning and Deep Learning
  • Management and Analysis of Big Data
  • Mathematics for AI and Big Data
  • AI Ethics and Project Management
  • In summary, debt structuring and capital management require a balanced approach that considers both growth opportunities and financial risks. Financial modeling provides a powerful framework for exploring these balances and supporting informed decision-making in corporate finance.

Course Content

Fourth year (Master 1)

UE0: Professional Integration Project in Artificial Intelligence and Big Data

SEMESTER 7

UE1: Fundamentals of Artificial Intelligence

UE2: Technologies and Tools of Big Data

8TH SEMESTER

UE3: Applied AI and Data Engineering

UE4: Writing Methodology

Fifth year (Master 2)

9th SEMESTER

UE1: Predictive Analysis and Statistics

UE2: Ethics and Legal Aspects of AI

10th Semester

UE3: Professional Project and Immersion

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