Will I get hands-on experience?

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

Is it suitable for R&D teams?

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.

Is this useful for regulatory or clinical operations teams?

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

What will I get if I purchase the Certificate?

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.

Is financial aid available?

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.

AI in Healthcare & Drug Discovery

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AI in Healthcare & Drug Discovery

Instructor: AI CERTs Team

Included with

Learn more

8 modules

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

8 modules

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.

Skills you'll gain

Tools you'll learn

Generative AI

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

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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 videosTotal 90 minutes

Navigation Video2 minutes
Audiobook: Module 01: Course Introduction6 minutes
Module 01: Course Introduction6 minutes
Audiobook: Module 01: AI Foundations for Pharma40 minutes
Podcast: Module 01: AI Foundations for Pharma13 minutes
1.1 AI and Machine Learning Basics)7 minutes
1.2 AI Applications Specific to Pharmaceutical Contexts5 minutes
1.3 AI Algorithms and Models6 minutes
1.4 Predictive Modeling for Pharmacokinetics and Drug Interactions3 minutes
1.5 Predictive Modeling for Adverse Drug and Drug-Drug Reactions3 minutes

1 readingTotal 10 minutes

Hands On10 minutes

1 assignmentTotal 30 minutes

Quiz 130 minutes

2 pluginsTotal 30 minutes

Ebook: Module 01: AI Foundations for Pharma15 minutes
Activity: Tab15 minutes

What's included

7 videos2 readings1 assignment2 plugins

7 videosTotal 126 minutes

Audiobook: Module 02: AI in Drug Discovery and Development82 minutes
Podcast: Module 02: AI in Drug Discovery and Development14 minutes
2.1 Analysis of Molecular Docking, QSAR, and Virtual Screening8 minutes
2.2 AI in Therapeutic Molecule Design9 minutes
2.3 AI Approaches to Drug Repurposing7 minutes
2.4 Case Analysis: Drug Repurposing During Pandemics3 minutes
2.5 AI-Driven Drug Repurposing for COVID-193 minutes

2 readingsTotal 20 minutes

Hands On 110 minutes
Hands On 210 minutes

1 assignmentTotal 30 minutes

Quiz 230 minutes

2 pluginsTotal 30 minutes

Ebook: Module 02: AI in Drug Discovery and Development15 minutes
Activity: Multiple choice15 minutes

What's included

7 videos2 readings1 assignment2 plugins

7 videosTotal 122 minutes

Audiobook: Module 03: Clinical Trials Optimization with AI94 minutes
Podcast: Module 03: Clinical Trials Optimization with AI11 minutes
3.1 Predictive Analytics for Patient Recruitment and Retention3 minutes
3.2 Strategies for Targeted Patient Outreach Using Machine Learning5 minutes
3.3 AI-Driven Clinical Data Collection, Quality Assurance, and Monitoring4 minutes
3.4 Real-Time Predictive Analytics to Improve Trial Outcomes4 minutes
3.5 Use Case: Pfizer’s AI-Driven Analytics for Optimizing Clinical Trials2 minutes

2 readingsTotal 20 minutes

Hands On 110 minutes
Hands On 210 minutes

1 assignmentTotal 30 minutes

Quiz 330 minutes

2 pluginsTotal 30 minutes

Ebook: Module 03: Clinical Trials Optimization with AI15 minutes
Activity: Accordion15 minutes

What's included

7 videos1 reading1 assignment2 plugins

7 videosTotal 114 minutes

Audiobook: Module 04: Precision Medicine and Genomics66 minutes
Podcast: Module 04: Precision Medicine and Genomics13 minutes
4.1 AI-Driven Personalization Through Genomic, Epigenetic, and Clinical Data8 minutes
4.2 AI in Personalized Treatment8 minutes
4.3 AI Methods for Identifying and Validating Biomarkers7 minutes
4.4 Real-World Applications of Biomarkers in Therapeutic Decisions7 minutes
4.5 Case Study: AI-Assisted Biomarker Discovery and Validation in Cancer Treatments5 minutes

1 readingTotal 10 minutes

Hands On 10 minutes

1 assignmentTotal 30 minutes

Quiz 430 minutes

2 pluginsTotal 30 minutes

Ebook: Module 04: Precision Medicine and Genomics15 minutes
Activity: Problem Statement15 minutes

What's included

7 videos2 readings1 assignment2 plugins

7 videosTotal 116 minutes

Audiobook: Module 05: Regulatory and Ethical AI in Pharma80 minutes
Podcast: Module 05: Regulatory and Ethical AI in Pharma15 minutes
5.1 Bias Mitigation, Transparency Practices, and Patient Privacy5 minutes
5.2 Development of Ethical Frameworks for AI Governance3 minutes
5.3 FDA, EMA, and WHO Regulatory Guidance for AI Applications4 minutes
5.4 Practical Approaches to Regulatory Submissions for AI-Enabled Pharma Products4 minutes
5.5 Case Study: Ethical and Regulatory Challenges in AI-Driven Pharma Initiatives4 minutes

2 readingsTotal 20 minutes

Hands On 110 minutes
Hands On 210 minutes

1 assignmentTotal 30 minutes

Quiz 530 minutes

2 pluginsTotal 30 minutes

Ebook: Module 05: Regulatory and Ethical AI in Pharma15 minutes
Activity: Multiple select15 minutes

What's included

5 videos1 reading1 assignment2 plugins

5 videosTotal 90 minutes

Audiobook: Module 06: Implementing AI in Pharma Projects61 minutes
Podcast: Module 06: Implementing AI in Pharma Projects14 minutes
6.1 From Initiation to Deployment: AI in Pharma5 minutes
6.2 Stakeholder Management, Project Timelines, and Deliverables6 minutes
6.3 Evaluating AI Tools and ROI5 minutes

1 readingTotal 10 minutes

Hands On 10 minutes

1 assignmentTotal 30 minutes

Quiz 630 minutes

2 pluginsTotal 30 minutes

Ebook: Module 06: Implementing AI in Pharma Projects15 minutes
Activity: Tab15 minutes

What's included

7 videos1 reading1 assignment2 plugins

7 videosTotal 108 minutes

Audiobook: Module 07: Future Trends and Sustainability in Pharma AI65 minutes
Podcast: Module 07: Future Trends and Sustainability in Pharma AI15 minutes
7.1 Quantum Computing and Blockchain in Pharma9 minutes
7.2 Emerging AI Trends Transforming Pharmaceuticals5 minutes
7.3 Sustainable Pharmaceutical Operations with AI6 minutes
7.4 Examples of AI-Driven Ethics and Optimization in Healthcare4 minutes
7.5 Sustainability Initiatives Driven by AI in Pharmaceutical Industry Leaders4 minutes

1 readingTotal 10 minutes

Hands On 710 minutes

1 assignmentTotal 30 minutes

Quiz 730 minutes

2 pluginsTotal 30 minutes

Ebook: Module 07: Future Trends and Sustainability in Pharma AI15 minutes
Activity: Case study15 minutes

What's included

4 videos1 assignment1 plugin

Instructor

AI CERTs Team

AI CERTs

58 Courses38,879 learners

Offered by

AI CERTs

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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.

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.

AI in Healthcare & Drug Discovery

AI in Healthcare & Drug Discovery

What you'll learn

Skills you'll gain

Tools you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

There are 8 modules in this course

Module 01: AI Foundations for Pharma

What's included

Module 02: AI in Drug Discovery and Development

What's included

Module 03: Clinical Trials Optimization with AI

What's included

Module 04: Precision Medicine and Genomics

What's included

Module 05: Regulatory and Ethical AI in Pharma

What's included

Module 06: Implementing AI in Pharma Projects

What's included

Module 07: Future Trends and Sustainability in Pharma AI

What's included

Module 08: Capstone Project

What's included

Instructor

Offered by

Explore more from Basic Science

Foundations of AI in Healthcare

AI Technologies in Healthcare

AI Innovation in Healthcare

AI for Healthcare

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Save on skills that make you shine with 40% off 3 months of Coursera Plus

Drive your business forward and empower your teams

Frequently asked questions

What will I be able to do after this course?

Do I need technical or coding experience?

How does this differ from general AI courses?

More questions