
Master in Data Analytics Intelligence MIAD
Bogotá, Colombia
DURATION
2 Years
LANGUAGES
Spanish
PACE
Part time
APPLICATION DEADLINE
Request application deadline
EARLIEST START DATE
Mar 2025
TUITION FEES
USD 10,448
STUDY FORMAT
Distance Learning
Key Summary
Introduction
The online program in Data Analytics Intelligence (MIAD) trains professionals who stand out for their technical and cutting-edge skills at the intersection of three areas of knowledge: mathematical modeling, information technologies and business management. Students learn through courses that balance theory and practice computational methods for data management, application of descriptive, predictive and prescriptive models that allow them to become leaders in Analytics that support decision making. In addition, students continually develop their soft skills in communication, teamwork and project management, necessary to make transformations that generate value in their organizations.
Currently, profiles related to analytics are the most in demand in the global labor market. Organizations around the world agree that some knowledge such as analytical reasoning, artificial intelligence, cloud computing and data-based project management are essential to succeed and differentiate themselves in the market.
The program is offered in Spanish and 100% online. Students receive the same quality standards offered in in-person programs and the same master's degree that Universidad de los Andes offers in its in-person programs. The virtual format allows students to continue working full time and continue their professional career. Being an online master's degree, it gives students the flexibility to learn when and where they want.
What will make this program unique
The most in-demand professions are related to Analytics
This program is structured for professionals, not necessarily from STEM areas, with basic knowledge in programming and statistics, who will be trained to address business questions that require analyzing a high volume and complexity of data to support decision-making processes, creation of competitive advantages and generation of value. More than 90% of global CEOs consider analytics to be strategically important and 68% believe it is the best way to create value for their stakeholders (PwC, 2016).
Close collaboration Academia - Industry
Uniandes works together with recognized public and private sector organizations and in alliance with the best universities in the world to be at the forefront of analytics knowledge and its application. This is why students take their knowledge to real problems, and are guided in this process by a teaching team that knows the demands of the market and has experience in addressing them with methods based on data analysis.
Access to the top 1% of universities in the world
In the last decade, Uniandes has been among the 10 best universities in Latin America and is currently the fifth university in the region and number 236 in the world, according to the QS 2022 ranking. The Universidad de los Andes was the first private university in Colombia than in receiving a high-quality institutional accreditation for ten years from the Ministry of National Education.
Be part of the first virtual master's degree in data analytics intelligence in Spanish offered by one of the best universities in Latin America.
This program has been designed for professionals, not necessarily from STEM areas (science, technology, engineering and mathematics, for its acronym in English), with basic knowledge in programming and statistics, who will be trained to address those business questions that require analysis. of a high volume of data and the management of its complexity to support decision-making processes, the creation of competitive advantages and the generation of value.
This program will be aimed at people with a professional degree interested in:
Lead high-impact analytical intelligence projects in organizations.
Build descriptive, predictive, and prescriptive mathematical models for decision making.
Extract, transform and load data from structured and unstructured sources with technologies for managing large volumes of data and cloud computing.
Learn about technological tools such as computer languages, analytics libraries, database and server management.
Analyze, synthesize and effectively present the results of analytical models with visualization and storytelling techniques.
Although it is advisable to know how to program in a language and have basic knowledge of probability and statistics, candidates will be recommended leveling routes to acquire this fundamental knowledge and skills.
Ideal Students
Be graduates of quantitative areas such as engineering, economics, mathematics, among others.
Are interested and motivated to apply advanced engineering techniques to support decision making in organizations.
They are graduates of other disciplines and have certified experience in data analysis and/or information management or large databases.
Be motivated to take on the teaching and learning processes through virtual means.
Admissions
Curriculum
The program has 36 credits distributed across 4 tracks, with a total duration of 24 months. Each trajectory is made up of two 8-week cycles. During each cycle students will take two courses simultaneously. The available courses will depend on the academic offering of the program, and are subject to modifications without prior notice.
Path 1 · Fundamentals of Analytics
This path provides tools to understand the strategic scope of analytics for decision making.
Cycle 1
- Decision analysis.
- Computational analytics laboratory.
Cycle 2
- Data modeling and ETL.
- Statistical analysis models.
Path 2 · Data Analytics: visualization, prediction and decision making
This trajectory covers in a transversal and basic way the different levels of the development of analytical intelligence in an organization, starting with the use of descriptive analytics (visualization), passing through the construction of predictive models (machine learning), ending with the formulation of prescriptive models for decision making (optimization).
Cycle 1
- Visualization and storytelling.
- Introduction to Machine Learning
Cycle 2
- Machine Learning and Natural Language Processing.
- Optimization for decision making.
Path 3 · Advanced Analytics Skills
Unsupervised learning modeling, large-scale computing techniques and technologies, prescriptive simulation modeling, and methodologies for formulating and managing analytics projects.
Cycle 1
- Choose between: System Dynamics or Simulation.
- Unsupervised learning.
Cycle 2
- Deployment of analytical solutions.
- Analytics Project Management - Project 1.
Path 4 · Advanced Analytics Applications and Techniques
The objective of this path is to provide flexibility and the opportunity to delve deeper according to the student's interest. Additionally, an integrative project will be developed along this path. The objective of this project is to provide the student with support for the application of the techniques in a real context, techniques to lead high-impact analytical intelligence projects in organizations, monitoring in data extraction, modeling, analysis and communication of results, as well as as teamwork tools.
Cycle 1
- Elective 1.
- Elective 2.
Cycle 2
- Elective 3.
- Applied Data Analytics Project - Project 2.
Students will be able to enroll in 3 elective courses to deepen according to their level of interest, selected according to the offer available for each cycle. Courses may vary without prior notice:
- Deep Learning.
- Forecasts.
- Financial Analytics.
- Marketing Analytics.
- Analytics in social networks.
Program Outcome
Identify opportunities to apply analytical intelligence to generate value within organizations.
Apply formal methodologies to translate business problems into analytics projects.
Extract, transform and load data from structured and unstructured sources with technologies for managing large volumes of data and cloud computing.
Formulate and build descriptive, predictive, and prescriptive mathematical models for decision making, such as machine learning, deep learning, computer vision, natural language analysis (NLP), optimization, social network analysis, among others.
Make use of technological tools such as computer languages, analytics libraries, database and server management.
Analyze, synthesize and effectively present the results of analytical models with visualization and storytelling techniques.
Lead high-impact analytical intelligence projects in organizations, using structured analytics and decision analysis methodologies, and computational technology to support large volumes of data.
Program Tuition Fee
Career Opportunities
Data is now fundamental assets in companies. However, value is generated when valuable analyzes are produced from them and decisions are made based on evidence (McKinsey&Company, 2016). These analyzes and decisions are capable of being carried out by analytics leaders trained in this master's degree.
MIAD graduates will be able to work in any private or public organization that has areas where data analytics is required to transform data into information that supports decision-making processes. Some of the positions they could occupy are:
- Data Mining Analyst.
- Financial Analyst.
- Marketing Analyst.
- Business Intelligence Analyst.
- Database Administrator.
- Human Resources Analyst.
- Systems Analyst. Chief Analytics Officer (CAO).