Have you thought of improving analytical and decision-making processes in organizational environments? Be aligned with the work market with the MBA USP/Esalq in Data Science and Analytics, an online course with exclusive tools of continuous interaction between professors and students.
Pre-requisite: to register in MBA USP/Esalq courses the candidate must have a higher education diploma. It is not necessary to have previous training or work in the Data Science or Information Technology fields.
The recognition and relevance that you need for a successful career depends on the constant update, the knowledge of main trends, and understanding of how the fundamentals and concepts of Data Science relate to practical applications, strategies, business models and technologies.
The market requires professionals with more than technical knowledge. Therefore, the MBA USP/Esalq in Data Science and Analytics goes further, seeking to develop competencies and skills of communication, critical thinking, analytical and interpretation capacity, programming and implementation of machine learning codes, problem resolution, systemic and strategic vision, among others.
At the end of the course, the professional will be able to:
- Understand the different structures of databases, types of variables, and their measurement scales
- Relate data engineering, analytics, and machine learning
- Develop skills for data manipulation, data wrangling, and data visualization
- Understand the reasons for the estimation of each of the machine learning models
- Build algorithms for model development and implementation of unsupervised, supervised, and ensemble machine learning techniques
- Develop web crawlers and implement web scraping and deep learning algorithms
- Understand and use data for geospatial analysis
- Develop business intelligence and data visualization projects, as well as build dashboards
- Implement operational research techniques from optimization and simulation models
- Present critical and strategic vision regarding information technology, artificial intelligence, big data, and data mining projects
- Establish analytics strategies for decision and risk management models
- Discuss cloud computing and cyber security
- Discuss LGPD (General Personal Data Protection Law)
Who is this course for:
Professionals acting in the most diverse areas, who need or want to acquire knowledge in data modeling, programming, technology, and strategic decision-making from the various aspects of Data Science.
Applicable teaching methodology
The course methodology is based on the interaction between theory and practice, with the objective to develop in students their critical thinking, enabling them to search for solutions, both in current and future activities, building knowledge to face challenges throughout their professional career.