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Computing for Cancer Informatics

Learn computing basics for cancer research. Explore shared resources, etiquette, and decision-making in this 11-hour beginner course.

Learn computing basics for cancer research. Explore shared resources, etiquette, and decision-making in this 11-hour beginner course.

This course provides researchers and investigators with a comprehensive understanding of computing basics and various computing options for cancer informatics. Designed for those new to informatics work, it covers fundamental computing terminology, concepts about computer systems, shared computing resources, and their appropriate use. The curriculum explores computing resources specific to cancer research and guides participants in making informed computing decisions. Through seven modules, learners will gain insights into how computers work, data storage and processing, file sizes, and computing capacity. The course also introduces shared computing etiquette and research platforms designed for cancer researchers. By the end, participants will be equipped to make better-informed decisions about computing resources for their cancer research projects.

4.6

(11 ratings)

7,757 already enrolled

Instructors:

English

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Computing for Cancer Informatics

This course includes

11 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

2,435

What you'll learn

  • Understand basic computing terminology and concepts

  • Learn how computers and shared computing resources work

  • Explore differences between various computing resource options

  • Understand appropriate etiquette for shared computing resources

  • Discover computing resources designed specifically for cancer research

  • Gain insights into making informed computing resource decisions

Skills you'll gain

bioinformatics
cancer
cloud computing
computer networks
data management
shared computing
research platforms

This course includes:

4 Hours PreRecorded video

Access on Mobile, Tablet, Desktop

FullTime access

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There are 7 modules in this course

This course offers a comprehensive introduction to computing for cancer informatics, designed for researchers with limited to intermediate experience in informatics research. It covers fundamental computing concepts, shared computing resources, and their application in cancer research. The curriculum is structured to provide learners with a solid understanding of how computers and computing systems work, the differences between various computing resources, and the etiquette for using shared resources. Participants will explore computing resources specifically designed for cancer research and learn important considerations for making computing decisions. The course aims to equip research leaders with the knowledge to effectively manage and analyze large datasets from multiple sources, addressing one of the key challenges in cancer informatics.

Welcome

Module 1 · 19 Minutes to complete

Basic Building Block of Computers

Module 2 · 2 Hours to complete

Binary data to computations

Module 3 · 2 Hours to complete

Computing Resources

Module 4 · 1 Hours to complete

Shared Computing Etiquette

Module 5 · 1 Hours to complete

Research Platforms

Module 6 · 1 Hours to complete

Data Management Decisions

Module 7 · 2 Hours to complete

Fee Structure

Payment options

Financial Aid

Instructor

Carrie Wright, PhD
Carrie Wright, PhD

3.9 rating

16 Reviews

3,977 Students

6 Courses

Pioneering Data Science Education and Computational Biology Innovation

Carrie Wright, PhD, serves as a Senior Staff Scientist at Fred Hutchinson Cancer Center and holds an affiliated faculty position at Johns Hopkins Bloomberg School of Public Health, where she focuses on making data science and computational biology more accessible to diverse audiences. Her expertise spans multiple domains, teaching courses including "AI for Decision Makers," "AI for Efficient Programming," "Avoiding AI Harm," "Best Practices for Ethical Data Handling," "Data Management and Sharing for NIH Proposals," and "Write Smarter with Overleaf and LaTeX." Her distinguished career includes significant contributions as a former Assistant Scientist in Biostatistics at Johns Hopkins and postdoctoral research at the Lieber Institute for Brain Development, where she studied genetic mechanisms in psychiatric disease. As a member of the Open Case Studies team, the Genomic Data Science Community Network, and chair of the ITCR OPEN Group, she demonstrates her commitment to advancing science, medicine, and social justice through accessible data science education. Her innovative work includes co-founding the LIBD rstats club and teaching at various institutions, including the Baltimore Underground Science Space and Johns Hopkins Center for Talented Youth.

Computing for Cancer Informatics

This course includes

11 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

2,435

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.6 course rating

11 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.