Students
Tuition Fee
Not Available
Start Date
Not Available
Medium of studying
Not Available
Duration
Not Available
Details
Program Details
Degree
Masters
Major
Artificial Intelligence | Data Analytics | Data Science
Area of study
Information and Communication Technologies
Course Language
English
About Program

Program Overview


The M.S. in Data Science at Avila

Overview

The M.S. in Data Science program is designed to equip students with the analytical, computational, and business knowledge required to extract meaningful insights from complex data. Whether applied in corporate enterprises, research institutions, government, or nonprofit organizations, this program prepares students for high-impact roles in the evolving data-driven world.


Course Requirements

This interdisciplinary program blends mathematics, statistics, programming, machine learning, and business intelligence. It emphasizes ethical data use, innovation, leadership, and strategic thinking to solve real-world problems using data.


Program Outcomes

Students will gain practical experience using leading tools in data analytics, machine learning, and artificial intelligence, while developing key leadership and communication skills to manage data-driven projects and teams.


Career Opportunities

  • Data Scientist
  • Machine Learning Engineer
  • Data Analyst
  • Business Intelligence Analyst
  • Data Engineer
  • Quantitative Analyst
  • AI/ML Researcher
  • Data Science Manager
  • Cloud Data Architect
  • Predictive Analytics Specialist
  • Big Data Engineer
  • Data Governance Analyst
  • Data and AI Strategy Consultant
  • Operations Research Analyst
  • Applied Statistician
  • Data Visualization Expert
  • Marketing Data Analyst
  • Healthcare Data Analyst
  • Financial Risk Analyst
  • NLP Specialist

Program Details

  • Interpret and analyze large, complex data sets to inform decision-making and drive strategic growth.
  • Apply data science techniques including machine learning, data mining, predictive modeling, and statistical inference.
  • Utilize tools such as Python, R, SQL, and cloud-based analytics platforms to build and deploy data models.
  • Demonstrate leadership, innovation, and collaboration in multidisciplinary teams.
  • Evaluate the ethical implications and data governance concerns related to data use and privacy in today’s digital world.
  • Integrate business acumen with technical proficiency to deliver data solutions that align with organizational goals.
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