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Covers observation methods in social sciences, emphasizing direct and indirect observation, participant observation, and multi-situated ethnography.

Report Structure: Acid-Base and pH Titration

Explores the structure of scientific reports and acid-base titration experiments, emphasizing accurate data recording and clear presentation.

Respiration Figures: Normal Breathing Patterns

Covers the analysis of respiratory figures and ECG heart rate data.

Collaborative Data Science: Tools and Techniques

Introduces collaborative data science tools like Git and Docker, emphasizing teamwork and practical exercises for effective learning.

Critical Data Studies: Reproducibility and Renku

Explores the significance of reproducibility in data science and introduces Renku, a platform for managing data-driven projects.

Introduction to Machine Learning: Course Overview and Basics

Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.

Digital Humanities Workflow

Explores the workflow in Digital Humanities, emphasizing data collection and visualization.

Clustering: K-means & LDA

Covers clustering using K-means and LDA, PCA, K-means properties, Fisher LDA, and spectral clustering.

Memory Management & Crash Programs

Covers memory management for engineers, focusing on crash programs related to memory access errors.

Scientific Fraud and Research Integrity

Explores scientific fraud, research integrity, guidelines, and notable cases like the Schön scandal, emphasizing the importance of upholding honesty and professionalism in scientific research.