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Artificial Intelligence in Bioinformatics

Discover the future of bioinformatics and learn how AI models of bioinformatics data help us to understand biological processes.

2,101 enrolled on this course

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Study the use of AI, machine learning, and deep learning in bioinformatics

This course will teach you the fundamentals of how AI is applied in the field of bioinformatics.

You’ll explore how AI, machine learning, deep learning, and natural language processing (NPL) concepts are used in the design and discovery of drugs, as well as for modelling complex biological systems.

Learn about AI-based bioinformatics

Artificial intelligence (AI) is transforming the field of bioinformatics.

On this course, you’ll learn the basics of collecting, analysing, and modeling bioinformatics data using AI.

You’ll find out how to collect and explore bioinformatics data from public resources and then use AI to analyse and model this data in order to better understand key biological processes.

Discover AI applications in bioinformatics research, such as genome sequencing

As you develop your knowledge of both the bioinformatics and artificial intelligence industries, you’ll explore how different AI concepts are applied in bioinformatics to mathematically interpret biological data and provide statistical information. You’ll develop your understanding of different cases of AI-based bioinformatics research, including genome sequencing, protein function prediction, and gene expression examination.

Build your AI toolkit for working in bioinformatics

This course will provide you with the AI knowledge and skills you need to apply AI in practice.

You’ll build data analytics and visualisation techniques that you can apply to a range of bioinformatics datasets and explore the latest machine learning concepts like feature engineering and feature learning.

You’ll put your learning into practice at the end of the course when you’ll be asked to organise and summarise data results for an academic paper in bioinformatics that’s fit for publication.

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What topics will you cover?

  • Overview on bioinformatics
  • Artificial Intelligence and how to apply it to bioinformatics
  • Feature engineering
  • Feature learning
  • Deep learning in bioinformatics
  • Analyzing and visualizing data

Who is this accredited by?

The CPD Certification Service
The CPD Certification Service:

The CPD Certification Service: The CPD Certification Service was established in 1996 and is the leading independent CPD accreditation institution operating across industry sectors to complement the CPD policies of professional and academic bodies.

When would you like to start?

Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.

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Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Collect and explore bioinformatics data from public resources
  • Apply different AI models in bioinformatics data to understand a variety of biological processes
  • Develop a standard framework for AI-based bioinformatics study that can be applied to different datasets
  • Summarise and report the results to generate a bioinformatics paper for publication purpose

Who is the course for?

This course is designed for any student, biologist, or researcher who would like to learn the basics of using AI to study bioinformatics data.

You do not need any experience in AI, bioinformatics, or programming.

What software or tools do you need?

Waikato Environment for Knowledge Analysis (Weka).

Who will you learn with?

Dr. Khanh is an Assistant Professor with the Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taiwan.

Who developed the course?

Taipei Medical University

Taipei Medical University (TMU) has been a leader in Taiwan’s healthcare system for over half a century due to its research, teaching excellence, internationalization and outstanding medical service.

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