MSc in Applied Data Science and Machine Learning

The MSc in Applied Data Science and Machine Learning at Vedere University is a professionally focused degree program designed to be delivered fully online as part of an innovative, staggered approach to mastering data science, business analytics, and machine learning. Through a highly structured curriculum, you will develop a comprehensive set of work-ready skills that will prepare you to excel in a wide range of companies and industries.


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In today’s era of big data and AI, employers need business analysts and data scientists who can harness advanced skills and technologies to drive insight and decision-making. This program builds these essential and in-demand competencies.
Dr. David Lopez
Faculty and Program Director

Program Overview

The primary aim of this program is to train recent graduates in securing their first job as entry-level data scientists or business analysts, as well as to assist working professionals in transitioning to more quantitative roles in their respective industries.

The program utilizes a problem-based learning method. This approach is esteemed for its ability to cultivate advanced competences and versatile skills valued by both public and private industries. By following this method, students gradually gain and enhance a comprehensive and precisely tailored set of skills including Python programming, statistical modeling, deep machine learning, and decision theory within the realm of business analytics.

The program is divided into three stages:
  • Stage 1 will ensure that students acquire basic programming skills and introduce them to basic statistical analysis techniques and data visualization.
  • Stage 2 will expose students to advanced programming and statistical analysis.
  • Stage 3 will introduce them to machine learning techniques and allow them to apply their skills in industry contexts.

Program Outcomes

By completing the program, students will learn to:

Analytical Competencies

  • Build statistical models and understand their power and limitations.
  • Design and experiment.
  • Apply problem-solving strategies to open-ended questions.

Technical Competencies

  • Acquire, clean, and manage data.
  • Manage and analyze massive data sets.
  • Use machine learning and optimization to make decisions.
  • Assemble computational pipelines to support data science from widely available tools.

Communication Competencies

  • Visualize data for exploration, analysis, and communication
  • Collaborate within and across functional teams.
  • Deliver reproducible data analysis
  • Conduct data science activities aware of and according to policy, privacy, security and ethical considerations

Program Structure

The program consists of a total of 36 credits and 12 required courses. It is structured to be completed in a specific sequence, as indicated by the prerequisites mentioned in the Course Descriptions section below. The Capstone Project serves as a platform to integrate and apply the knowledge acquired throughout the degree program.
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Course Descriptions

Admission Requirements:

  • An undergraduate degree from an accredited Institution – with a preferred GPA of 3.0 or higher
  • A quantitative background from prior academic study or work experience
  • Completed application form including personal statements/essays
  • Resumé and letters of recommendation
  • Official academic transcripts and certificates
  • TOEFL/IELTS or other English language proficiency test if applicable

Costs & Fees

15,984 USD
Total Program Fee
36
Credits
444 USD
Cost per Credit
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