Fundamental Skills in Bioinformatics
Master essential bioinformatics and data analysis skills using R and Python. Perfect for beginners in biological and biomedical fields.
Master essential bioinformatics and data analysis skills using R and Python. Perfect for beginners in biological and biomedical fields.
This comprehensive course provides a practical introduction to bioinformatics and data analysis, specifically designed for biological and biomedical students with minimal programming background. The curriculum covers fundamental programming skills in both R and Python, along with essential statistical concepts and their applications in bioinformatics. Students learn to analyze RNA-seq data, perform quality control, and work with both bulk and single-cell data analysis. The course emphasizes hands-on practice through coding lectures and programming assignments, ensuring students develop practical skills while building a strong foundation in bioinformatics principles.
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What you'll learn
Master fundamental R programming concepts and data structures
Develop Python programming skills for bioinformatics applications
Analyze bulk RNA-seq count data using statistical methods
Perform single-cell RNA-seq data analysis
Apply quality control and data visualization techniques
Understand key bioinformatics concepts and workflows
Skills you'll gain
This course includes:
8.2 Hours PreRecorded video
13 assignments
Access on Mobile, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive bioinformatics course combines theoretical knowledge with practical programming skills in R and Python. The curriculum progresses from basic programming concepts to advanced bioinformatics applications, including RNA-seq analysis. Students learn through a combination of lectures, coding exercises, and hands-on projects, developing essential skills for biological data analysis. The course structure ensures a solid foundation in both programming and bioinformatics principles.
Introduction to Programming (using R)
Module 1 · 4 Hours to complete
Introduction to Programming II (using R)
Module 2 · 9 Hours to complete
Programming in Python
Module 3 · 5 Hours to complete
Bioinformatics case study - RNA-seq bulk and single-cell data analysis
Module 4 · 4 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructors
Research Scientist
Vincenzo Lagani is an experienced data scientist primarily working on developing statistical methods and software tools for predictive analytics, risk stratification, feature selection and causal analysis.
Digital Learning Specialist
Zafer Ali is a Digital Learning Specialist known for his course "Fundamental Skills in Bioinformatics" offered on Coursera. His expertise lies in enhancing digital learning experiences, particularly in the field of bioinformatics
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