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"Predicting Protein Structure with Meta AI: Practical Guide

Learn life sciences through practical, hands-on projects and real-world applications.

Online Course
Self-paced learning
Flexible Schedule
Learn at your pace
Expert Instructor
Industry professional
Certificate
Upon completion
What You'll Learn
Build real-world projects using life sciences
Apply theoretical knowledge to practical scenarios
Build practical projects to demonstrate your skills
Understand advanced concepts and techniques

Skills you'll gain:

Professional SkillsBest PracticesIndustry Standards
Prerequisites & Target Audience

Skill Level

IntermediateSome prior knowledge recommended

Requirements

Basic understanding of life sciences
Enthusiasm to learn
Access to necessary software/tools
Commitment to practice

Who This Course Is For

Professionals working in life sciences
Students and career changers
Freelancers and consultants
Anyone looking to improve their skills
Course Information

About This Course

Unlock the power of AI-driven bioinformatics by mastering Predicting Protein Structure using Meta AI. This comprehensive, beginner-friendly course will teach you how to predict, analyze, and visualize protein structures using Meta AI's ESMFold without requiring expensive lab equipment or heavy computational resources. Protein structure plays a critical role in understanding biological functions, designing drugs, and advancing research in biotechnology and healthcare.

Traditional methods like X-ray crystallography and NMR are time-consuming and costly. With AI breakthroughs from Meta AI, you can now predict protein structures quickly and accurately to accelerate your research and project workflows. In this course, you will start with the fundamentals of protein structure, learning about primary, secondary, tertiary, and quaternary structures and why they are important in biology and drug design.

You will then dive into the exciting world of AI-based protein structure prediction, understanding how tools like Meta AI's ESMFold are revolutionizing structural biology. Through hands-on tutorials using Google Colab, you will learn how to:Fetch protein sequences from databases like UniProt,Predict their structures using ESMFold,Visualize and interpret these structures using tools like PyMOL, Chimera, and Mol*. You will work on practical mini-projects, such as predicting the structure of a disease-related protein and comparing predicted structures with experimental data, gaining insights into drug discovery and protein engineering applications.

This course also covers the limitations of AI in structure prediction, best practices, and ethical considerations, equipping you to apply these skills responsibly in your research or professional projects. Whether you are a student, researcher, bioinformatics enthusiast, or a professional in biotech or pharma, this course will empower you with practical, job-ready skills in AI-driven protein forecasting. By the end of this course, you will confidently predict and analyze protein structures, understand their implications in real-world scenarios, and add cutting-edge AI bioinformatics skills to your toolkit to stay ahead in your academic or professional journey.

Provider
Udemy
Estimated Duration
10-20 hours
Language
English
Category
Science & Academia

Topics Covered

Life SciencesUiHands-On Learning

Course Details

Format
Online, Self-Paced
Access
Lifetime
Certificate
Upon Completion
Support
Q&A Forum
Course Details
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This course includes:

Lifetime access to course content
Access on mobile and desktop
Certificate of completion
Downloadable resources

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