Kurse
18844 Kurse
Challenges in Fostering Trust and Distrust in AI Systems
Explore key challenges in AI trust development, from benchmark construction and evaluation methods to data quality issues and human trust factors in artificial intelligence systems.
Visualization for Data Science - Creating Views and Dashboards
Master data visualization techniques for creating impactful views and dashboards, focusing on best practices for effective data presentation and communication in data science applications.
Introduction to Machine Learning Model Explanations and Interpretability
Explore key concepts in data science explanations, from gradient-based highlighting to contrastive editing, covering essential techniques for understanding and interpreting complex models.
The Importance of Arts and Crafts in ThreatOps - Effective Visual Communication for Cybersecurity Analysis
Master effective visualization techniques for cybersecurity incidents and threat intelligence, enhancing your ability to communicate complex security concepts through clear, standardized diagrams.
Deep Learning and Process Understanding for Data-Driven Earth System Science - Lecture 37
Explore deep learning applications in Earth System Science, focusing on process understanding and data-driven approaches to environmental research and analysis.
Creating Your AI/BI Genie Space for Business Data Analytics
Discover how to empower business teams with AI/BI Genie - a conversational interface that enables natural language data exploration and self-service analytics for instant insights.
Practical Machine Learning for AI: Foundational Skills and Experiments
Discover machine learning principles and applications on this course for non-ML specialists.
Synthetic Data Generation and Applications in Python
Discover how to generate synthetic data for machine learning and data analysis projects, with practical Python examples and implementation strategies.
High Performance Machine Learning, Deep Learning, and Data Science - Principles and Practice
Master high-performance computing principles for machine learning and deep learning, focusing on practical implementation strategies and advanced techniques for optimizing data science workflows.
Parameter-Efficient Automation of Data Wrangling Tasks with Prefix-Tuning
Explore how prefix-tuning offers an efficient alternative to LLM fine-tuning for data wrangling tasks, requiring minimal parameter updates while maintaining comparable performance in data integration and cleaning.
Humans and AI: Understanding LLM Impact on Human Decision Making
Explore the synergistic potential between humans and LLMs in decision-making tasks, examining active learning, ML fairness, and collaborative approaches to AI implementation.
Use of AI in Modern Data Visualization - Making Complex Data Sets Accessible
Explore how AI-driven tools revolutionize data visualization creation and consumption, making complex datasets more accessible and actionable while enhancing developer productivity.