Exploratory and objective data analysis methods applied to the physical, engineering, and biological sciences.
This course is about learning the fundamental computing skills necessary for effective data analysis.
This course on Grid Computing aims to provide you with an understanding of the key concepts that underlie Grid technology and the role that Grid Computing can play in computationally intensive problems. It also aims to help researchers, regardless of their major (High Energy Physics, Biology, Earth observation, etc), to feel confident of their ability to use the Grid Infrastructure.
Learn about the most effective data analysis methods to solve problems and achieve insight.
Introductory Machine Learning course covering theory, algorithms and applications. Our focus is on real understanding, not just "knowing."
Investigate the flexibility and power of project-oriented computational analysis, and enhance communication of information by creating visual representations of scientific data.
Learn critical concepts and practical methods to support research data planning, collection, storage and dissemination.
This course is an introduction to the key ideas and principles of the collection, display, and analysis of data to guide you in making valid and appropriate conclusions about the world.
With existing data, you will develop skills in data analysis and basic statistics by exploring your own research question.
When we use programming for problem-solving purposes, data must be stored in certain forms, or Data Structures, so that operations on that data will yield a specific type of output.