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Bioinformatics and Data Analysis
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MOOC
In this course you will be introduced to the basic ideas behind the qualitative research in social science. You will learn about data collection, description, analysis and interpretation in qualitative research. Qualitative research often involves an iterative process. We will focus on the ingredients required for this process: data collection and analysis. You won't learn how to use qualitative methods by just watching video's, so we put much stress on collecting data through observation and interviewing and on analysing and interpreting the collected data in other assignments. Obviously, the most important concepts in qualitative research will be discussed, just as we will discuss quality criteria, good practices, ethics, writing some methods of analysis, and mixing methods. We hope to take away some prejudice, and enthuse many students for qualitative research.
- Subjects:
- Statistics and Research Methods
- Keywords:
- Qualitative research -- Methodology Social sciences -- Research -- Methodology
- Resource Type:
- MOOC
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Courseware
From satellites gathering imagery from hundreds of miles above the Earth's surface to aerial systems mounted with lasers capable of generating 3D maps with centimeter accuracy, we're gathering more data about our Earth from above than ever before. This course will help you make sense of these complex and exciting datasets. Whether your interest is in natural disasters, environmental assessment, or national security, we'll give you the tools, methods, and techniques to extract actionable and meaningful information from these data.
- Subjects:
- Land Surveying and Geo-Informatics
- Keywords:
- Remote-sensing images Image processing -- Digital techniques
- Resource Type:
- Courseware
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Courseware
In this data rich world, we need to understand how things are organized on the Earth's surface. Those things are represented by spatial data and necessarily depend upon what surrounds them. Spatial statistics provide insights into explaining processes that create patterns in spatial data. In geographical information analysis, spatial statistics such as point pattern analysis, spatial autocorrelation, and spatial interpolation will analyze the spatial patterns, spatial processes, and spatial association that characterize spatial data. Understanding spatial analysis will help you realize what makes spatial data special and why spatial analysis reveals a truth about spatial data.
- Subjects:
- Land Surveying and Geo-Informatics
- Keywords:
- Spatial analysis (Statistics) Geographic information systems
- Resource Type:
- Courseware
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Courseware
This course focuses on the use of remotely sensed imagery and elevation data in GIS applications. Students enrolling in this course should have a solid conceptual foundation in geospatial information science and technology. The course is appropriate for those who are already working in the geospatial profession and wish to use imagery and elevation data in visualization and spatial analysis.
- Subjects:
- Land Surveying and Geo-Informatics
- Keywords:
- Geographic information systems Image processing -- Digital techniques
- Resource Type:
- Courseware
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MOOC
basics of questionnaire design, data collection methods, sampling design, dealing with missing values, making estimates, combining data from different sources, and the analysis of survey data.
- Course related:
- HTM3205 Analysing and Interpreting Research
- Subjects:
- Statistics and Research Methods
- Keywords:
- Social surveys -- Methodology Social sciences -- Research -- Methodology
- Resource Type:
- MOOC
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e-book
A Brief Introduction to Engineering Computation with MATLAB is specifically designed for students with no programming experience. However, students are expected to be proficient in First Year Mathematics and Sciences and access to good reference books are highly recommended. Students are assumed to have a working knowledge of the Mac OS X or Microsoft Windows operating systems. The strategic goal of the course and book is to provide learners with an appreciation for the role computation plays in solving engineering problems. MATLAB specific skills that students are expected to be proficient at are: write scripts to solve engineering problems including interpolation, numerical integration and regression analysis, plot graphs to visualize, analyze and present numerical data, and publish reports.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Mechanical Engineering
- Keywords:
- MATLAB Engineering mathematics
- Resource Type:
- e-book
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Courseware
This course provides a broad introduction to machine learning and statistical pattern recognition. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Pattern perception -- Statistical methods Machine learning
- Resource Type:
- Courseware
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e-book
In the era of Internet of Things (IoT) and with the explosive worldwide growth of electronic data volume, and associated need of processing, analysis, and storage of such humongous volume of data, several new challenges are faced in protecting privacy of sensitive data and securing systems by designing novel schemes for secure authentication, integrity protection, encryption, and non-repudiation. Lightweight symmetric key cryptography and adaptive network security algorithms are in demand for mitigating these challenges. This book presents some of the state-of-the-art research work in the field of cryptography and security in computing and communications. It is a valuable source of knowledge for researchers, engineers, practitioners, graduates, and doctoral students who are working in the field of cryptography, network security, and security and privacy issues in the Internet of Things (IoT). It will also be useful for faculty members of graduate schools and universities.
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Video
How to use Bloomberg to find data related to environmental, social, and governance (ESG)
- Subjects:
- Finance
- Keywords:
- Corporations -- Investor relations Social responsibility of business Business enterprises -- Environmental aspects
- Resource Type:
- Video
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Video
How to use Bloomberg to search fixed income data
- Subjects:
- Finance
- Keywords:
- Investment analysis Bonds
- Resource Type:
- Video