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Machine Learning Fundamentals Humanities & Social Sciences Program Fall 2024 Semester CEA CAPA & UNYP - Prague

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Machine Learning Fundamentals

Machine Learning Fundamentals Course Overview


CEA CAPA Partner Institution: University of New York in Prague
Location: Prague, CZECH REPUBLIC
Primary Subject Area: Computer Sciences
Instruction in: English
Course Code: ITM360
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 45
Prerequisites: Calculus, Statistics I


The purpose of the course is to introduce machine learning fundamentals. Machine Learning lies at the hearth of many applications in today?s world that we take for granted, from automatic translation to recommendation systems in streaming platforms and detection of fraudulent credit card transactions. The impact of machine learning and its closely related field of Artificial Intelligence in the economy is huge and only expected to become more and more prevalent, thanks to the rise or low/no-code platforms that enable users without a technical background to apply those algorithms in different real-life situations.

Hence, our focus in the course is more on the grasping of the fundamentals and the understanding, as well as the limitations, caveats and situations that arise in practice, rather than doing a deep dive in the mathematical theory behind them.

We will start by a review of the data manipulation tool par excellence, Microsoft Excel, which will allows the students to grasp the intuition and core ideas without getting lost in programming, and gradually introduce commonly used tools like R, Python and SQL.

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