Bachelor in Business Administration
The Bachelor in Business Administration (BBA) at Collège de Paris is designed to...
Master of Science in Computer Science (Data Science and Artificial Intelligence)
Paris
INTAKE: Jan, April, July & Oct
Program Overview
The Master of Science in Computer Science (Data Science and Artificial Intelligence) at Collège de Paris is a forward-thinking postgraduate program designed to equip students with advanced analytical, computational, and AI-driven skills for data-intensive industries. With a strong foundation in both theoretical and applied computer science, this two-year degree prepares students to become leaders in AI development, machine learning, big data analytics, and intelligent automation. It is ideal for those seeking impactful careers at the convergence of technology and decision-making.
Curriculum: The curriculum is structured to cover the entire data science lifecycle while integrating artificial intelligence techniques. Students begin with core modules such as Programming for Data Science, Probability and Statistics, and Data Structures. Advanced coursework includes Machine Learning, Deep Learning, Natural Language Processing, Data Mining, Neural Networks, and AI Ethics. Tools like Python, R, TensorFlow, PyTorch, and cloud-based platforms are used extensively in lab sessions and assignments. A capstone project or thesis based on real-world AI or data science problems concludes the program, encouraging students to translate their learning into tangible innovations.
Research Focus: Collège de Paris fosters a robust research culture that emphasizes real-world impact in AI and data science. Students and faculty collaborate on projects involving predictive modeling, autonomous systems, computer vision, speech recognition, and ethical AI governance. Through dedicated research labs and interdisciplinary collaborations, the program supports publications, prototype development, and AI applications across healthcare, finance, retail, and sustainability sectors.
Industry Engagement: The program maintains strong ties with global tech firms, AI startups, and data-centric enterprises. Students benefit from hands-on industry experiences through internships, live projects, and mentorships. Regular guest lectures, hackathons, and collaborative workshops provide exposure to current industry practices in data pipelines, AI deployment, and agile development. These engagements ensure that students graduate with the technical expertise and soft skills sought by employers.
Global Perspective: Recognizing the global demand for data science and AI professionals, Collège de Paris integrates international perspectives through its diverse faculty, multicultural student body, and worldwide academic partnerships. Exchange programs, dual-degree opportunities, and participation in international research networks and conferences further enhance students’ global competencies. Graduates are well-prepared to work in multinational environments and adapt to the evolving dynamics of the digital economy.
Location
Paris
Score
IELTS 6.5
Tuition Fee
€ 12000
Postgraduate Entry Requirements
Academic Qualifications: Applicants for postgraduate programs typically require a minimum academic achievement of 60% or above in their bachelor's degree.
English Language Proficiency:
- IELTS: Overall band score of 6.5 or 7.0 with a minimum of 6.0 in each component.
College de Paris acknowledges the importance of supporting international students in pursuing their educational aspirations. To facilitate access to quality education, the institution offers various scholarship opportunities tailored to assist deserving international students.
Scholarship: 25% Scholarship on tuition fees if paid within the deadline of 07 working days.
Graduates of the Master of Science in Computer Science (Data Science and Artificial Intelligence) at Collège de Paris are equipped with advanced analytical and computational skills to excel in AI-driven industries and data-centric roles.
Data Scientist: Design and implement data models to extract insights from large datasets using machine learning algorithms and statistical analysis tools like Python, R, and SQL.
Machine Learning Engineer: Develop and deploy scalable ML models and algorithms for predictive analytics, recommendation engines, and automation systems in diverse industries.
AI Research Scientist: Conduct cutting-edge research in artificial intelligence domains such as computer vision, natural language processing, and reinforcement learning, contributing to scientific and technological advancement.
Data Analyst: Interpret complex data sets, create dashboards, and provide actionable business intelligence using tools such as Tableau, Power BI, and Excel.
Deep Learning Engineer: Specialize in building and optimizing deep neural networks for tasks like image recognition, voice synthesis, and autonomous decision-making.
NLP (Natural Language Processing) Engineer: Develop applications that understand, interpret, and generate human language, including chatbots, sentiment analysis engines, and language translation systems.
Business Intelligence Developer: Design and maintain BI systems and tools that help organizations make data-driven decisions by transforming raw data into meaningful insights.
Big Data Engineer: Build and manage scalable big data infrastructures using technologies such as Hadoop, Spark, and Kafka to support large-scale analytics.
AI Ethics Consultant: Advise companies and governments on the ethical implications of AI technologies, focusing on fairness, transparency, accountability, and data privacy.
Robotics and Automation Specialist: Integrate AI with robotics and automation systems in industries such as manufacturing, healthcare, and logistics to optimize efficiency and performance.
