The aim of this course is to complete the presentation of data science-related topics bent towards business applications. Starting from the topics presented in the Intelligence systems and Data Mining courses, this course will provide methods and techniques geared towards the implementation of projects suitable for production environments. This course relates the knowledge of theoretical aspects of data science with the most relevant technologies for manipulating, managing and visualizing data. Students will be taught about data analysis through datasets available online. Throughout the course activities, predictive experiments (machine learning and deep learning) will be shown in order to fulfill the requirements of the use cases. The learning objectives and expected results of this course are: To define an architecture that allows for the development of a data science project, with respect to data volume, velocity and availability, along with computing power and implementation and maintainability requirements. Select adequate methods for solving the proposed problems, with machine learning and deep learning technologies. Analyze, visualize and meaningfully interpret the obtained results, given the proposed solution methods. Implement simple projects in order to gain hands-on experience on methods and techniques in data analysis.
Course Prerequisites
The student knows about the topics presented in the courses of Intelligent Systems and Data Mining. A knowledge of at least one programming language is helpful. Also, it is suggested to bring a laptop.
