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⇱ AI in Healthcare & Drug Discovery | Coursera

AI in Healthcare & Drug Discovery

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AI in Healthcare & Drug Discovery

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Accelerate Drug Discovery with AI: Use AI for target identification, molecule design, virtual screening, and early-stage research decisions.

  • Improve Clinical Research Workflows: Apply predictive models to support trial planning, patient selection, safety monitoring, and endpoint analysis.

  • Automate Research Tasks: Use AI to streamline data cleaning, literature review, research analysis, and high-throughput biomedical tasks.

  • Strengthen Evidence-Based Decisions: Interpret clinical and biomedical data more effectively to support faster, well-informed healthcare decisions.

Details to know

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Recently updated!

March 2026

Assessments

8 assignments

Taught in English

There are 8 modules in this course

AI is transforming how healthcare, pharmaceutical research, and drug discovery teams work, from early-stage research to clinical decision-making.

The AI in Healthcare & Drug Discovery Certification is a beginner-friendly, hands-on program designed for professionals in pharma, biotech, clinical research, healthcare analytics, and medical innovation. Learn how AI supports drug discovery, clinical trials, biomedical analysis, and evidence-based decisions without coding experience. The course covers practical AI applications across the drug development lifecycle, including target identification, molecule screening, biomarker evaluation, trial planning, clinical data analysis, and research automation. Through guided exercises and real-world scenarios, you’ll learn how to use machine learning, generative AI, predictive analytics, and automation to review scientific information faster, analyze data more efficiently, and support safer, smarter research outcomes. By the end of the course, you’ll confidently apply AI tools to improve productivity, research quality, and decision-making across healthcare and drug development workflows. Enroll now to gain practical AI skills for healthcare research and innovation.

This module introduces the overall certification structure and explains how the learning experience is organized throughout the course. To support different learning preferences, the content is offered in multiple formats, including Videos, eBooks, Audiobooks, and Podcasts. Each format covers the same key concepts, giving you the flexibility to learn in the way that works best for you. You can choose any format based on your preferred learning style and move through the course at your own pace.

What's included

10 videos1 reading1 assignment2 plugins

10 videos•Total 90 minutes
  • Navigation Video•2 minutes
  • Audiobook: Module 01: Course Introduction•6 minutes
  • Module 01: Course Introduction•6 minutes
  • Audiobook: Module 01: AI Foundations for Pharma•40 minutes
  • Podcast: Module 01: AI Foundations for Pharma•13 minutes
  • 1.1 AI and Machine Learning Basics•7 minutes
  • 1.2 AI Applications Specific to Pharmaceutical Contexts•5 minutes
  • 1.3 AI Algorithms and Models•6 minutes
  • 1.4 Predictive Modeling for Pharmacokinetics and Drug Interactions•3 minutes
  • 1.5 Predictive Modeling for Adverse Drug and Drug-Drug Reactions•3 minutes
1 reading•Total 10 minutes
  • Hands On•10 minutes
1 assignment•Total 30 minutes
  • Quiz 1•30 minutes
2 plugins•Total 30 minutes
  • Ebook: Module 01: AI Foundations for Pharma•15 minutes
  • Activity: Tab•15 minutes

What's included

7 videos2 readings1 assignment2 plugins

7 videos•Total 126 minutes
  • Audiobook: Module 02: AI in Drug Discovery and Development•82 minutes
  • Podcast: Module 02: AI in Drug Discovery and Development•14 minutes
  • 2.1 Analysis of Molecular Docking, QSAR, and Virtual Screening•8 minutes
  • 2.2 AI in Therapeutic Molecule Design•9 minutes
  • 2.3 AI Approaches to Drug Repurposing•7 minutes
  • 2.4 Case Analysis: Drug Repurposing During Pandemics•3 minutes
  • 2.5 AI-Driven Drug Repurposing for COVID-19•3 minutes
2 readings•Total 20 minutes
  • Hands On 1•10 minutes
  • Hands On 2•10 minutes
1 assignment•Total 30 minutes
  • Quiz 2•30 minutes
2 plugins•Total 30 minutes
  • Ebook: Module 02: AI in Drug Discovery and Development•15 minutes
  • Activity: Multiple choice•15 minutes

What's included

7 videos2 readings1 assignment2 plugins

7 videos•Total 122 minutes
  • Audiobook: Module 03: Clinical Trials Optimization with AI•94 minutes
  • Podcast: Module 03: Clinical Trials Optimization with AI•11 minutes
  • 3.1 Predictive Analytics for Patient Recruitment and Retention•3 minutes
  • 3.2 Strategies for Targeted Patient Outreach Using Machine Learning•5 minutes
  • 3.3 AI-Driven Clinical Data Collection, Quality Assurance, and Monitoring•4 minutes
  • 3.4 Real-Time Predictive Analytics to Improve Trial Outcomes•4 minutes
  • 3.5 Use Case: Pfizer’s AI-Driven Analytics for Optimizing Clinical Trials•2 minutes
2 readings•Total 20 minutes
  • Hands On 1•10 minutes
  • Hands On 2•10 minutes
1 assignment•Total 30 minutes
  • Quiz 3•30 minutes
2 plugins•Total 30 minutes
  • Ebook: Module 03: Clinical Trials Optimization with AI•15 minutes
  • Activity: Accordion•15 minutes

What's included

7 videos1 reading1 assignment2 plugins

7 videos•Total 114 minutes
  • Audiobook: Module 04: Precision Medicine and Genomics•66 minutes
  • Podcast: Module 04: Precision Medicine and Genomics•13 minutes
  • 4.1 AI-Driven Personalization Through Genomic, Epigenetic, and Clinical Data•8 minutes
  • 4.2 AI in Personalized Treatment•8 minutes
  • 4.3 AI Methods for Identifying and Validating Biomarkers•7 minutes
  • 4.4 Real-World Applications of Biomarkers in Therapeutic Decisions•7 minutes
  • 4.5 Case Study: AI-Assisted Biomarker Discovery and Validation in Cancer Treatments•5 minutes
1 reading•Total 10 minutes
  • Hands On •10 minutes
1 assignment•Total 30 minutes
  • Quiz 4•30 minutes
2 plugins•Total 30 minutes
  • Ebook: Module 04: Precision Medicine and Genomics•15 minutes
  • Activity: Problem Statement•15 minutes

What's included

7 videos2 readings1 assignment2 plugins

7 videos•Total 116 minutes
  • Audiobook: Module 05: Regulatory and Ethical AI in Pharma•80 minutes
  • Podcast: Module 05: Regulatory and Ethical AI in Pharma•15 minutes
  • 5.1 Bias Mitigation, Transparency Practices, and Patient Privacy•5 minutes
  • 5.2 Development of Ethical Frameworks for AI Governance•3 minutes
  • 5.3 FDA, EMA, and WHO Regulatory Guidance for AI Applications•4 minutes
  • 5.4 Practical Approaches to Regulatory Submissions for AI-Enabled Pharma Products•4 minutes
  • 5.5 Case Study: Ethical and Regulatory Challenges in AI-Driven Pharma Initiatives•4 minutes
2 readings•Total 20 minutes
  • Hands On 1•10 minutes
  • Hands On 2•10 minutes
1 assignment•Total 30 minutes
  • Quiz 5•30 minutes
2 plugins•Total 30 minutes
  • Ebook: Module 05: Regulatory and Ethical AI in Pharma•15 minutes
  • Activity: Multiple select•15 minutes

What's included

5 videos1 reading1 assignment2 plugins

5 videos•Total 90 minutes
  • Audiobook: Module 06: Implementing AI in Pharma Projects•61 minutes
  • Podcast: Module 06: Implementing AI in Pharma Projects•14 minutes
  • 6.1 From Initiation to Deployment: AI in Pharma•5 minutes
  • 6.2 Stakeholder Management, Project Timelines, and Deliverables•6 minutes
  • 6.3 Evaluating AI Tools and ROI•5 minutes
1 reading•Total 10 minutes
  • Hands On •10 minutes
1 assignment•Total 30 minutes
  • Quiz 6•30 minutes
2 plugins•Total 30 minutes
  • Ebook: Module 06: Implementing AI in Pharma Projects•15 minutes
  • Activity: Tab•15 minutes

What's included

7 videos1 reading1 assignment2 plugins

7 videos•Total 108 minutes
  • Audiobook: Module 07: Future Trends and Sustainability in Pharma AI•65 minutes
  • Podcast: Module 07: Future Trends and Sustainability in Pharma AI•15 minutes
  • 7.1 Quantum Computing and Blockchain in Pharma•9 minutes
  • 7.2 Emerging AI Trends Transforming Pharmaceuticals•5 minutes
  • 7.3 Sustainable Pharmaceutical Operations with AI•6 minutes
  • 7.4 Examples of AI-Driven Ethics and Optimization in Healthcare•4 minutes
  • 7.5 Sustainability Initiatives Driven by AI in Pharmaceutical Industry Leaders•4 minutes
1 reading•Total 10 minutes
  • Hands On 7•10 minutes
1 assignment•Total 30 minutes
  • Quiz 7•30 minutes
2 plugins•Total 30 minutes
  • Ebook: Module 07: Future Trends and Sustainability in Pharma AI•15 minutes
  • Activity: Case study•15 minutes

What's included

4 videos1 assignment1 plugin

4 videos•Total 54 minutes
  • Audiobook: Module 08: Capstone Project•26 minutes
  • Podcast: Module 08: Capstone Project•18 minutes
  • 8.1 Introduction to Capstone Project•5 minutes
  • Module 08: Course Summary •6 minutes
1 assignment•Total 30 minutes
  • Quiz 8•30 minutes
1 plugin•Total 15 minutes
  • Ebook: Module 08: Capstone Project•15 minutes

Instructor

AI CERTs
58 Courses•43,878 learners

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Frequently asked questions

After this course, you’ll be able to identify where AI fits into drug discovery, use AI tools for research analysis, evaluate clinical data more effectively, and support better decision-making across healthcare and pharmaceutical workflows.

No. This course is designed for non-technical healthcare, pharma, research, and clinical professionals. No programming skills are required.

Unlike general AI programs, this course focuses specifically on AI use cases in pharma, biotech, clinical research, drug development, and healthcare. Every lesson is designed around real-world industry applications.

Yes. You’ll learn through guided exercises, case studies, and practical scenarios based on real healthcare and research challenges.

Yes. The program is ideal for R&D researchers, analysts, clinical teams, and healthcare innovators who want to use AI to improve research productivity and outcomes.

Yes. Regulatory and clinical operations teams can use the course to understand how AI supports data review, trial workflows, documentation, and research decision-making.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,