Python Course: Machine Learning, Optimization and Applications (VII Edition)

Pre-registration period: Until October 20, 2024

Registration Period: From October 1 to 20, 2024

Course start: November 20, 2024

End of course: January 30, 2025

Credits: 10 ECTS

Price: €560 (taxes included)

More information : https://cfp.us.es/cursos/fc/python-machine-learning-optimizacion-y-aplicaciones/4724/storal@us.es , d.gutierrez.reina@gmail.com

The continuing training course in Python: Machine Learning, Optimization and Applications (VIII Edition), worth 10 ECTS credits, and which can be taken in person/online, is offered by the Permanent Training Center of the University of Seville. The classes will be transmitted synchronously and will be recorded and available to students through the Virtual Teaching platform of the University of Seville.

This course offers a complete tour of programming Machine/Deep Learning algorithms and optimization using the Python programming language. For this, the course is structured in five modules:

· Module 1 covers the basics of programming in Python and the numpy, matplotlib, pandas and scipy modules. As a prerequisite, you only need basic programming knowledge, not necessarily in Python where you start from scratch.

· In module 2, students will learn the fundamentals of machine learning techniques with application to regressions, classifiers and clustering. The classes include theoretical explanations and application scripts in Python using the scikit-learn library.

· Module 3 comprises various meta-heuristic optimization methods using the Python DEAP module: trajectory-based local search methods and population-based global search methods. A section dedicated to reinforcement learning using the Python Gym library is also included.

· In module 4 students will learn the fundamentals of deep learning in Keras and Tensorflow, and how to apply these techniques to solve real-world problems. A wide variety of neural network architectures such as dense networks, convolutional networks, recurrent networks and deep reinforcement learning will be studied from a theoretical and practical point of view.

· Module 5 is dedicated to applications. Over 5 sessions and in self-contained classes, various academic and industry professionals will show examples of applications of the previous modules.

The course will be taught by experts in the field of machine learning and optimization, who will share their extensive knowledge and experience with students, and is aimed at

students who are passionate about technology and eager to make the most of the opportunities offered by machine learning and optimization. The skills acquired on this course are highly valued in the industry and can open doors to a wide range of career opportunities.

Student selection criteria by Pre-registration Order. No university degree is necessary to access the course.

Pre-registration period: Until October 20, 2024

Registration Period: From October 1 to 20, 2024

Course start: November 20, 2024

End of course: January 30, 2025

Credits: 10 ECTS

Price: €560 (taxes included)

More information : https://cfp.us.es/cursos/fc/python-machine-learning-optimizacion-y-aplicaciones/4724/storal@us.es , d.gutierrez.reina@gmail.com

The continuing training course in Python: Machine Learning, Optimization and Applications (VIII Edition), worth 10 ECTS credits, and which can be taken in person/online, is offered by the Permanent Training Center of the University of Seville. The classes will be transmitted synchronously and will be recorded and available to students through the Virtual Teaching platform of the University of Seville.

This course offers a complete tour of programming Machine/Deep Learning algorithms and optimization using the Python programming language. For this, the course is structured in five modules:

· Module 1 covers the basics of Python programming and the numpy, matplotlib, pandas and scipy modules. As a prerequisite, you only need basic programming knowledge, not necessarily in Python where you start from scratch.

· In module 2, students will learn the fundamentals of machine learning techniques with application to regressions, classifiers and clustering. The classes include theoretical explanations and application scripts in Python using the scikit-learn library.

· Module 3 comprises various meta-heuristic optimization methods using the Python DEAP module: trajectory-based local search methods and population-based global search methods. A section dedicated to reinforcement learning using the Python Gym library is also included.

· In module 4 students will learn the fundamentals of deep learning in Keras and Tensorflow, and how to apply these techniques to solve real-world problems. A wide variety of neural network architectures such as dense networks, convolutional networks, recurrent networks and deep reinforcement learning will be studied from a theoretical and practical point of view.

· Module 5 is dedicated to applications. Over 5 sessions and in self-contained classes, various academic and industry professionals will show examples of applications of the previous modules.

The course will be taught by experts in the field of machine learning and optimization, who will share their extensive knowledge and experience with students, and is aimed at

students who are passionate about technology and eager to make the most of the opportunities offered by machine learning and optimization. The skills acquired on this course are highly valued in the industry and can open doors to a wide range of career opportunities.

Student selection criteria by Pre-registration Order. No university degree is necessary to access the course.