Master’s Degree in
Data Science & Business Analytics

• Bachelor's degree or its equivalent.
• Bachelor's degree credits or grades or their equivalent.

• Identity document (passport in case of foreigners residing in Panama).
• A current passport-size photo.
• Fill out the admission form in electronic format with the promoter.

• Study in teams and individually.
• Develop research skills based on discovery learning.
• Deepen in the disciplinary knowledge that is of interest to them.
• Respect and comply with the regulations established by the statutes that regulate the relationship between the University and the students.
• Be up to date with their Attend at least 80% of the meetings in the semi-face-to-face mode.
• For studies under the virtual modality, attendance is regulated by constant interaction in all activities planned on the platform, including synchronous and asynchronous meetings, as well as the development of the student's autonomous work.
• In case of prolonged absence, the student must present a justified argumentation.
• All students of the Specialization programs must have basic computer skills.

• Maintain a minimum cumulative index of 2 on a scale of 1 to 3.

• Pass each subject with a minimum grade of 81 on a scale of 1 to 100 which is equivalent to B.

In order to obtain the title of Specialist, the following is required:

Index

• Maintain a cumulative academic index of not less than two (2.00) on a scale of three (3.00).

To obtain the Master's Degree, the following is required:

• Maintain a cumulative academic index of not less than two (2.00) on a scale of three (3.00).
• Second language recognized by UNESCO

In order to obtain the title of Specialist, the following is required:

• Take a certification exam of a second language recognized by UNESCO, in accordance with internal regulations.

To obtain the Master's Degree, the following is required:

Note

In order to obtain the title of Specialist, the following is required:

• Complete and pass all the subjects of the curriculum with a minimum grade of 81 points equivalent to a B.

To obtain the Master's Degree, the following is required:

• Complete and pass all the subjects of the curriculum with a minimum grade of 81 points equivalent to a B.
• Take a certification exam of a second language recognized by UNESCO, in accordance with internal regulations.
• Final Project (Degree)

In order to obtain the title of Specialist, the following is required:

• Carry out an 80-hour internship and present a final report with case studies. It must be aligned to the last subject of the specialization: Research I: Planning, Monitoring and Evaluation of Projects.
• Be in good standing with the institution (financial, academic, and library).

In order to obtain the Master's Degree it is required:

Final Project (Degree)

• Elaborate, support and approve the degree work.
• Align Action Research: Development of degree work.
• Complete and pass all the academic content of the program enrolled.
• Be in good standing with the institution (financial, academic, and library).

• Receive the understanding of the data, its importance, its use, its interpretation and the way to extract value from them.
• Find out about the main data science tools that allow the company or institution to benefit from the amount of data it collects.
• It manages to know how packages or libraries are used to extend the functionalities of a programming language.
• Understand what big data is, the causes that have led to the appearance of big data technologies and learn about the evolution of big data in its historical context.
• Understand the concept of "data science", its relationship with other disciplines, its methods and its practical application.
• Master the data processing techniques and understand their relevance, both in improving the quality of the data and in increasing its usefulness for the models, algorithms, consolidations, visualizations and other elements that are required.
• You know about the principles and benefits of business intelligence.
• Identify a complete big data solution in a Hadoop ecosystem and practice it on a virtual machine.
• Understands that the techniques that allow to extract the knowledge of the population from the sample that is the most evident for the approximation to the reality of the population the more representative the sample of this.
• Learn about machine learning and how it can help the business; as well as understand the main types of machine learning algorithms and the moment in which each type should be applied
• Knows and understands artificial intelligence, its meaning and the type of problems it can solve; decision-making techniques (expert systems and supervised learning), as well as their applications.

• Interpret the information that can be extracted from the data and know what questions can be asked to solve before the data, is to be aware of the domain that the data presents.
• It uses the main tools of data science to be able to present the data with precision and value to it.
• Install and use packages or libraries to extend the functionalities of a programming language.
• Applies the main programming fundamentals for both Python and R.
• It develops the data-driven company model and how it is articulated around the exploitation of its data platform; when characterizing the new profiles that arise in the company as a consequence of the adoption of a strategy based on the exploitation of data.
• Formulate a data science project based on the establishment of the problem to be solved, including the different stages, the type of tools to be used, the professional profiles that need to be involved, the type of obstacles that could arise and the ways to overcome them.
• Perform effective displays of information and convey the appropriate message.
• Solve a data processing solution with Spark in a notebook environment.
• Analyze and interpret data, to drive value and applied innovation in various industries.
• Use other tools and services from companies that are ready to support your own projects.
• It manages to process natural language, what types of problems it solves and its applications.

• Analyzes situations critically and proposes viable solutions with objectivity and realism.
• It elaborates a global and totalizing vision of the complex socio-labor relations that arise in the different modes of production historically developed and in force.
• Perfect the theoretical bases of the specialty and guide it in the best possible direction.

• Feel the dynamics of data management and transform it into information with the help of a specialized workforce. Understands the importance of human resources within the development of a company
• Contributes to the construction of the social fabric from the management of the company's human talent

• Presents proposals for the optimization of computing resources.
• Generate analysis and optimization models of data in a company
• Ability to generate new companies with feasibility evaluation of the data and the way to create value from them.