Fundamentals of Data Science
Degree programs: MSc Business Analytics and Data Science, MSc Logistics & SCM, MSc International Management
In this module, students will be equipped with the skills and knowledge necessary to excel in the dynamic field of data science. This module covers a wide range of topics, blending theoretical foundations with hands-on practical experience. Students will delve into various stages of the data science lifecycle, from data collection and preprocessing to advanced analysis and visualization. Key components of the module include: foundational concepts, data preparation, machine learning, deep learning, and natural language processing.
On successful completion of this module, the students will be able to:
• collect, clean, preprocess, and analyze diverse datasets using a range of different data science techniques.
• understand and apply various machine learning algorithms, enabling them to build, evaluate, and optimize predictive models for diverse applications
• analyze textual data using NLP techniques, e.g. for tasks like sentiment analysis, text classification, and language generation.
Course facts
Offered by | Prof. Dr. Henrik Leopold |
---|---|
ECTS credits | 5 Credit Points |
Tracks | Standard Track, Fast Track |
Method of examination | 100% Project Work |