Entrant profileGraduate profile
Entrant profile
- Bachelor's degree and/or professional degree in engineering, mathematics, physics or related areas.
- It is desirable that you have work experience in the industry/company.
Graduate profile
The academic profile of the graduate of the Master's Degree in Automation Engineering with Artificial Intelligence is designed in relation to four fundamental aspects, which are:
- Knowledge of engineering methodologies, concepts, and technologies: This refers to the fundamentals of each area of knowledge and includes advancements in each specialty. It relates to applied engineering competence using digital transformation tools in industry: process control and automation, industrial computing (Internet of Things, software), and smart technologies (artificial intelligence).
- Innovation management: This refers to the ability to formulate and manage innovation and research projects focused on digital transformation for the intelligent control and automation of industrial processes. It is related to the Innovation Management – Technology Transfer competency.
- Research: This refers to the reflective and analytical ability to organize complex information. This skill is developed in research courses geared towards the completion of a thesis as an objective element.
- General and humanistic training: refers to the interpersonal skills that allow a person to interact effectively with others in the workplace.
The four fundamental aspects are achieved through the following skills:
| Engineering and Specialty | 1) To know methodologies for modeling, simulation, advanced control and optimization of dynamic industrial processes. 2) Manage computational tools, industrial computing, and programming environments such as MATLAB, Python, C++, Simulink, for the development of prediction models. 3) Manage Digital Transformation tools: Internet of Things (IoT), industrial networks and Cybersecurity, applied in Industrial Automation. 4) Management of Artificial Intelligence techniques for automation: Machine Learning, Deep Learning, and Robotics implemented in the automation of industrial processes. |
| Innovation and Research Management | 5) Ability to formulate and manage innovation projects with digital transformation for the intelligent control and automation of industrial processes, considering technical, economic, and social aspects. |
| Research | 6) To know the research methodology and apply it to the planning, design and execution of research projects. |
| Soft skills | 7) Organization and information: Recognizes, organizes, and uses data to establish the most appropriate solutions to the problem. Key competency indicators: a. Identify the type of information required to address the process control problem. b. Establish the method for processing information and arriving at solutions. c. Implements, monitors, and maintains the organization of an industrial automation project. 8) Change and transformation: It is capable of developing a continuous improvement process based on existing conditions. It has the following key indicators: a. Identify the requirements for change and the opportunities for transformation. b. Develop and implement a change or transformation strategy. 9) Teamwork: Is able to work in groups of people as a leader or member, to achieve common goals. a. Promotes cooperation and interconnection among team members. b. Supports, facilitates and reviews the development of the team and its members. |