About Course
This course equips students with the skills and knowledge to leverage cloud computing resources for bioinformatics research and data analysis, focusing on AWS cloud systems and running bioinformatics resources, workflows, containers, scripts, and pipelines on AWS.
Course abbreviation: CIB
Instructor: Eng. Omar Mostafa
Senior Solution Architect
Workload: 12 lectures, 3 hours each. Total workload: 36 hours of lectures and tutorials.
Entrance requirements: None
Used media: Jupyter Notebook, PDF slides
Objectives
- Understand the basics and fundamentals of cloud computing and its benefits for bioinformatics engineers
- Gain hands-on experience working on AWS
- Manage, store, and analyze large-scale biological datasets on cloud platforms
- Optimize cloud-based bioinformatics workflows for scalability, cost-effectiveness, and data security
Competences to be Developed
- Basic cloud computing skills
- Version control tools for bioinformatics projects: Bitbucket and GitHub
- AWS core, supporting, and machine learning services
- Running bioinformatics scripts and pipelines on AWS
- Container engines: Singularity and Docker
- Nextflow and Snakemake workflow systems
- Web app development using Streamlit on AWS
Assessment
- Complete specified exercises during each lecture
- Successfully complete and present the capstone project
Course Content
Lecture 1: Cloud Computing Basics
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Cloud Computing Basics
00:00
Lecture 2: AWS Core Services
Lecture 3: Linux Machine on AWS
Lecture 4: AWS ML Services
Lecture 5: Running Python on AWS
Lecture 6: Running R on AWS
Lecture 7: Version Control for Bioinformatics
Lecture 8: Building Pipelines on AWS
Lecture 9: Running Containers on AWS
Lecture 10: Running Nextflow and Snakemake on AWS
Lecture 11: Running Streamlit on AWS
Lecture 12: Capstone Project
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