OsakaUx: Metabolomics in Life Sciences

Learn about metabolomics principles and their applications in life sciences.

Beginner FriendlyCertification IncludedSelf-Paced Learning
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₹4067
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🧠 Recommended for beginners
⚠ Not ideal for advanced users

Learning Journey Context

This course serves as an entry point into Biology & Life Sciences, building foundational knowledge before moving on to advanced frameworks or specialized paths.

Career Relevance

Relevant for: Data Scientist, Data Analyst, Machine Learning Engineer.

Quick Facts

4 weeks
OsakaUx
Beginner
Self-Paced Online
Online Course
edx
English
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What You’ll Learn

This course is an introduction to metabolomics principles and their applications in various fields of life sciences. We will provide a summary of all steps in metabolomics research; from experimental design, sample preparation, analytical procedures, to data analysis. The course also provides case studies of various kinds of research samples to attract students that are not familiar with metabolomics, providing them enough explanation to utilize metabolomics technology for their respective research fields. Several examples of metabolomics applications willĀ be introduced throughout the lectures. These include examples within food science and technology, metabolic engineering, basic biology, introduction to imagingĀ mass spectrometry, and application in medical science.No previous knowledge on metabolomics is needed but we recommend that students have anĀ undergraduate-level understanding of Biochemistry, Analytical Chemistry, andĀ Biostatistics, and that they learn about basic principles of multivariable analysis prior to taking this course.

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Outcomes

  • The basic principles of metabolomics.
  • Workflow of metabolomics research from design of experiment to data interpretation.
  • Applications of metabolomics in various fields of life sciences.
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FAQs

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OsakaUx: Metabolomics in Life Sciences
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āœ“ Compare side-by-side before spending money
Check Latest Price →
Price may vary. Check latest price on provider site.
🧠 Recommended for beginners
⚠ Not ideal for advanced users