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Updated in [June 30th, 2023]

This course, Applied Data Science: An Introduction, provides an introduction to the philosophical literature about the sorites paradox and the Liar paradox, as well as to some logical developments connected to them. Students will gain an understanding of the philosophical significance of the sorites paradox and of the Liar paradox, as well as some basic reactions to them. Additionally, students will become familiar with the logics K3, LP and ST, the concepts of paracompleteness, paraconsistency and duality, and the use of multiple conclusions. Finally, students will master the tableaux technique to construct proofs for classical propositional logic, K3, LP, and ST.

[Applications]
Upon completion of this course, students should be able to apply the concepts and techniques learned to a variety of real-world problems. They should be able to use the tableaux technique to construct proofs for classical propositional logic, K3, LP, and ST. Additionally, they should be able to use the concepts of paracompleteness, paraconsistency, and duality to analyze and solve problems. Finally, they should be able to use multiple conclusions to draw meaningful conclusions from data.

[Career Paths]
One job position path that this course could lead to is that of an Applied Data Scientist. An Applied Data Scientist is a professional who uses data science techniques to solve real-world problems. They use a variety of methods, such as machine learning, natural language processing, and statistical analysis, to analyze large datasets and uncover insights. They also develop predictive models and create visualizations to communicate their findings.

The development trend for Applied Data Scientists is very positive. As more and more organizations are recognizing the value of data-driven decision making, the demand for Applied Data Scientists is increasing. Companies are investing in data science teams and hiring Applied Data Scientists to help them make better decisions and gain a competitive edge. Additionally, the emergence of new technologies, such as artificial intelligence and the Internet of Things, is creating even more opportunities for Applied Data Scientists.

[Education Paths]
The recommended educational path for learners of this course is to pursue a degree in Applied Data Science. This degree typically involves courses in mathematics, computer science, and statistics, as well as courses in data analysis, machine learning, and artificial intelligence. Students will learn how to use data to solve real-world problems, develop algorithms, and create models. They will also learn how to interpret and visualize data, and how to use data to make decisions.

The development trend of this degree is to focus on the application of data science in various fields, such as healthcare, finance, and marketing. Students will learn how to use data to improve decision-making, create predictive models, and develop strategies for data-driven businesses. They will also learn how to use data to create insights and develop strategies for data-driven decision-making. Additionally, students will learn how to use data to create visualizations and develop data-driven applications.