Industrial Robotics and Emerging Technologies
University of Burgos offers 7 specialized courses in the field of Industrial Robotics and Emerging Technologies, providing participants with cutting-edge knowledge and hands-on experience. Each course delves into key areas such as automation, AI integration, advanced manufacturing processes, and the latest in robotic technologies. Through practical applications and real-world case studies, attendees will gain the skills necessary to leverage these technologies and drive industrial innovation. Please choose a course:
Duration: 6 hours (3 hours face-to-face and 3 hours of autonomous work)
Format: Blended learning
Objective: This course aims to foster participants' experience in using LLMs to boost their productivity and efficiency in various aspects of their professional lives. The 2-hour session focuses on providing participants with an overview of LLMs and their potential, while cultivating the transversal skills needed to implement digital transformation within their organization.
Syllabus:
- Brief introduction to LLMs (10 min).
- Key Guidelines and Recommendations for Lead Generation (10 min).
- Set of practical exercises (70 min):
- Example of a synthesis of documents.
- Video summary.
- Generation of online meeting minutes.
- Generation of content for social networks.
- Generating emails and templates.
- Translation.
- Follow-up of customer reviews.
- Power Point slide generation.
- Comparison of the performance of ChatGPT and Bard in the same tasks (10 min).
- Expert Content: Introduction to more advanced aspects of LLMs, such as vector databases, text embedding, and retrieval-augmented generation (20 min).
Editions:
Edition 1: 19 (face-to-face session) to 26 July 2024.
Edition 2: To be determined.
Edition 3: To be determined.
Registration:
https://bit.ly/EAGLE-2024
Duration: 16 hours (8 hours face-to-face and 8 hours autonomous work)
Format: Blended learning
Objective: The course is intended as an introduction to the general aspects of big data and business intelligence, offering an overview of the range of tools available and their application possibilities, including special topics dedicated to intuitive data visualisation and machine learning tools.
Syllabus:
- Introduction to business intelligence and big data. Concepts of big data, data literacy, data analytics, etc. Use cases.
- Big data infrastructures: Big Data storage models. Big Data programming models. Security in data storage and management.
- Data exploration and interpretation: Data visualization. Microsoft PowerBI.
- Data analysis: Machine learning (supervised leraning). Information discovery (unsupervised learning). Data flows. KNIME Analytics Platform.
- Students will work on a use case of interest to complete (a) a task related to data exploration and presentation and (b) a task related to a basic data analysis process to obtain actionable results in a company.
Editions:
Edition 1: To be determined.
Edition 2: To be determined.
Edition 3: To be determined.
Registration:
https://bit.ly/EAGLE-2024
Duration: 30 hours (20 hours of synchronous teaching and 10 hours of autonomous work)
Format: Online.
Objective: This course will equip the assistants with essential skills to manipulate and visualize data, master both supervised and unsupervised learning, and tackle real-world problems. Dive into hands-on projects and discover how to turn data into actionable insights. It is aimed to students with basic knowledge of computer programming.
Syllabus:
- Introduction to Data Science in R. Main types of data and programming structures. Vectors and matrices. Dataframes. R Markdown.
- Data manipulation and visualization. Types of variables. Standardization. One-hot encoding. Plotted with ggplot.
- Supervised learning and unsupervised learning. Classification, regression and clustering tasks. Linear, nonlinear and projection models. Evaluation strategies. Performance metrics.
- Students will work on a real-life problem use case where they will apply the knowledge gained during the course.
Editions:
Edition 1: To be determined.
Edition 2: To be determined.
Edition 3: To be determined.
Registration:
https://bit.ly/EAGLE-2024
Duration: 30 hours (16 hours of face-to-face teaching and 14 hours of autonomous work)
Format: Blended learning
Objective: This course aims to equip participants with a comprehensive understanding of IoT and smart systems within the context of Industry 4.0. Students will gain practical skills in programming, electronics, network communications, and data processing, essential for developing and deploying IoT solutions. The course will cover the selection and application of appropriate IoT technologies and communication protocols based on specific use cases, with a focus on edge computing and energy management in embedded systems.
Syllabus:
- Programming in C.
- Basic electronics.
- Network communications.
Data processing. - Embedded Systems and IoT Systems
- IoT technologies applied to industry.
- Communication protocols in IoT.
- How to be able to choose the most appropriate IoT technology based on the specific use case. Take into account all the features required in a use case to select the most suitable protocols and devices for this purpose.
- Edge computing in the context of IoT (Artificial Intelligence + IoT).
- Fundamentals of energy management in embedded systems.
- Students will be given a hands-on IoT scenario as homework. For example, students must be able to choose the most appropriate technology and protocols to solve the challenge proposed in a typical IoT scenario and also deploy the designed solution.
Editions:
Edition 1: January 13th to February 10th, 2025.
Edition 2: September 8th to October 6th, 2025.
Edition 3: November 24th to December 22nd, 2025.
Registration:
https://bit.ly/EAGLE-2024
Duration: 8 hours (4 hours of face-to-face teaching and 4 hours of autonomous work)
Format: Blended learning
Objective: This course aims to provide participants with a thorough understanding of optimization techniques and their application in enhancing products, processes, and business resources. By the end of the course, students will be able to formulate and solve optimization problems using mathematical programming and Excel. They will gain insights into the importance of optimization across various fields, learn to identify decision variables, cost functions, and constraints, and explore different algorithms and solvers to tackle optimization challenges effectively.
Syllabus:
- Why to use optimization. Fields of interest.
- Introduction to optimization and mathematical programming. Basic concepts. Decision variables, cost function and constraints. How to formulate an optimization problem. Different kind of formulations.
- What is a solver. Different kinds of algorithms to solve optimization problems. Main difficulties.
- Students will be given a case study, they have to understand the problem: their variables, constraints and cost function, how to formulate it as an optimization problem and finally, solve it using Excel.
Editions:
Edition 1: Weeks of November 4 and 11, 2024.
Edition 2: Weeks of March 3 and 10, 2025.
Edition 3: Weeks of September 13 and 20, 2025.
Registration:
https://bit.ly/EAGLE-2024
Duration: 8 hours (4 hours of face-to-face teaching and 4 hours of autonomous work)
Format: Blended learning
Objective: This course aims to provide participants with a fundamental understanding of process control in the industry, with a specific focus on setting up and tuning PID controllers. By the end of the course, students will be able to identify and understand the components of a control loop, apply PID controller tuning methods, and select the appropriate type of controller for various industrial applications. Through practical case studies, participants will learn to specify the desired behavior and tune the controller to optimize process performance.
Syllabus:
- Introduction to process control. Control pyramid, types of processes. The control loop and the variables involved. Application examples.
- The PID regulator. Proportional term, integral term and derivative term. Effect of parameters on response type. Adjustment methods: trial and error, based on experiments.
- PID, PI-D and I-PD controllers. Derivative filters. Antiwind-up, reference torsion, bumpless transfer.
- Students will receive a practical case, understand the operation of the process, the control objectives and the variables of the control loop. Specify the desired behavior and select the type of controller. Tune the controller.
Editions:
Edition 1: Weeks of October 21 and 28, 2024.
Edition 2: Weeks of January 8 and 13, 2025.
Edition 3: Weeks of September 15 and 22, 2025.
Registration:
https://bit.ly/EAGLE-2024
Duration: 16 hours (8 face-to-face and 8 autonomous work)
Format: Blended learning
Objective:
Syllabus:
- What is a robot? Types of robots. Applications of robots.
Parts of a robot. Technical parameters in robots. Selection of robots. Basic movements. Robot programming. Security basics. - Kinematic model. Singularities. Robot interfaces. Simulation of components in production.
- Students will receive an application, they will have to understand the movements to be made, design the trajectories, identify the signals and program the robot to complete the task.
Editions:
Edition 1: To be determined.
Edition 2: To be determined.
Edition 3: To be determined.
Registration:
https://bit.ly/EAGLE-2024
Who are these courses for?
This course is designed for employees of small and medium-sized enterprises (SMEs), job seekers, and individuals seeking to reskill or upskill in cybersecurity. It is not intended for advanced IT professionals.
How will my business benefit?
By attending this course, your business will be better prepared to defend against cyberattacks, ensuring business continuity and compliance with legal requirements. You'll also gain tools to assess risks and protect your data from potential threats, significantly reducing the likelihood of costly security breaches.
How much does this course costs?
This course is completely free. Co-funded by the European Union.
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