Pratt Institute · USA

Master's in Data Analytics and Visualization

Campus Masters Full Time

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Delivery

Campus

Study mode

Full Time

Level

Masters

Starts

Fall, Spring

Introduction

Data Analytics and Visualization is a Masters program taught at Pratt Institute, USA. Intake: Fall, Spring. The program is offered in campus-based modes with full-time (1–2 years) options.

The Master's Degree in Data Analytics and Visualization at Pratt Institute equips students with essential skills for making sense of complex data and conveying information through clear visual representations. This course covers a multitude of topics, including statistical analysis, predictive modeling, and data visualization techniques, ensuring that students have a robust understanding of both the theoretical and practical aspects of data analytics.

Throughout the program, students will engage in hands-on projects that apply their knowledge to real-world scenarios, honing their ability to guide decision-making through data-driven insights. The curriculum is designed to foster creativity and critical thinking, enabling students to articulate their findings effectively through engaging visual formats.

Studying at Pratt Institute places students in a vibrant urban environment rich in diversity and innovation. The dynamic culture of the United States encourages creativity and inter-disciplinary approaches, making it an ideal location for an immersive learning experience in data analytics and visualization.

Admission Requirements

The minimum requirements for admission in Data Analytics and Visualization at Pratt Institute for all applicants (Domestic or International) are:

program specific academic requirment set by Pratt Institute.
English Language OR any other language requirments as set by Pratt Institute as pre-requiste for admission in Data Analytics and Visualization.

Note: Please check the university website in the link below.

Applicants should possess a bachelor’s degree in a related field, such as mathematics, computer science, or statistics. Additionally, a strong foundation in quantitative analysis and familiarity with programming languages, such as Python or R, will be beneficial. Relevant work experience or internships in data-related roles may also enhance an applicant's candidacy.

Non-native English speakers are typically required to demonstrate proficiency through recognized tests such as IELTS or TOEFL. A minimum score of 6.5-7.0 in IELTS or 80-100 in TOEFL is generally expected, though students are encouraged to verify specific requirements.