Machine Learning Practical Applications Course, Deep Learning and Data Science

In an era where Machine Learning, Deep Learning and Data Science are pillars of innovation, our course provides strategic immersion in these disciplines. Through the exploration of algorithms in Python and the use of specialized tools, the student will be trained in the effective implementation of automatic and deep learning solutions, both supervised and non -supervised. Critical analysis and data modeling will be encouraged, allowing the creation of insicious reports and interactive command tables through Powerbi. Training culminates with the development of real applications, amalgamating theory and practice to address complex challenges. This course raises essential competences through practical exercises, establishing the basis for solving industry problems with vision and skill.

The objective pursued is the implementation of the theoretical knowledge of Machine Learning, Deep Learning and Data Science, through the realization and resolution of practical cases. 1. Development of the ability to implement Machine Learning and Deep Learning algorithms. - Implementation of supervised learning algorithms. - Implementation of non -supervised learning algorithms. - Implementation of supervised and non -supervised learning algorithms using tools and libraries of Machine Learning and Deep Learning 2. Development of capacities in Data Science such as: Analyze and model data. - Prepare reports. - Develop interactive command pictures. 3. Development of strategy capabilities to solve a Machine Learning problem, Deep Learning or Data Science. - By performing practical exercises, the student will implement through programming language the necessary functions for the construction of algorithms of Machine Learning and Deep Learning. In addition to facing a set of data, where they will analyze them, generating reports, studying the relationships between them, as well as visualizing them clearly and intuitively. - Finally, the student will face a real application, in which he uses his theoretical and practical knowledge to solve using the most appropriate strategy of a Machine Learning problem.

After completing the training in Machine Learning and Deep Learning, with skill skill and specialized tools, graduates are ready to lead AI projects in technological, financial or health sectors. In addition, with skills in Data Science and visual analysis in Powerbi, they can perform as data analysts, designing strategies based on quantitative information. Finally, with experience in developing real applications, they will be candidates for software engineer roles with an artificial intelligence focus.

The course "practical applications of Machine Learning, Deep Learning and Data Science" prepares you to effectively apply supervised learning algorithms and not supervised with Python and specific bookstores. You will acquire the ability to analyze and visualize data using Power BI, creating interactive reports and dashboards. Through practical exercises, you will learn to build solutions for real challenges, optimizing your strategy to face problems in the field of Machine Learning with a practical and strategic approach.

This course is designed for professionals and enthusiasts who seek to apply and strengthen their skills in Machine Learning and Deep Learning, using Python and specialized bookstores. Data science is also addressed, learning to analyze and interpret data sets with Power BI. At the end of, the participants will be able to transfer the theory to the resolution of specific cases and develop real applications, perfecting their analytical and technical strategy.