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

Ce cours n'est pas disponible en Français (France)

Nous sommes actuellement en train de le traduire dans plus de langues. Consultez les langues disponibles.

AI in Healthcare & Drug Discovery

Instructeur : AI CERTs Team

2 238 déjà inscrits

Inclus avec En savoir plus

9 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Débutant

Expérience recommandée

8 heures à compléter

Planning flexible

Apprenez à votre propre rythme

9 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Débutant

Expérience recommandée

8 heures à compléter

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

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.

Compétences que vous acquerrez

Catégorie : Medical Science and Research
Catégorie : Regulatory Compliance
Catégorie : Applied Machine Learning
Catégorie : Pre-Clinical Development

Outils que vous découvrirez

Catégorie : Generative AI
Catégorie : AI Workflows
Catégorie : Agentic Workflows

Détails à connaître

Certificat partageable

Ajouter à votre profil LinkedIn

Évaluations

8 devoirs

Enseigné en Anglais

Découvrez comment les employés des entreprises prestigieuses maîtrisent des compétences recherchées

En savoir plus sur Coursera pour les affaires

logos de Petrobras, TATA, Danone, Capgemini, P&G et L'Oreal

Il y a 9 modules dans ce cours

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.

Introduces the core concepts of Artificial Intelligence (AI) and its applications across the pharmaceutical industry. This module covers AI fundamentals, machine learning concepts, healthcare data ecosystems, and how AI is transforming drug development, research, operations, and decision-making in pharma.

Inclus

6 vidéos1 devoir1 plugin

6 vidéosTotal 25 minutes

Course Introduction4 minutes
1.1 AI Fundamentals and Hierarchy4 minutes
1.2 AI Models, Implementation, and Governance in Pharma5 minutes
1.3 Advanced AI Applications for Pharma Knowledge, Writing, and Drug Development4 minutes
1.4 AI Copilots and Prompt Engineering for Medical Writing and Regulatory Documents4 minutes
1.5 Case Studies4 minutes

1 devoirTotal 30 minutes

Quiz 130 minutes

1 pluginTotal 5 minutes

Activity: Accordion5 minutes

Explores how AI is accelerating drug discovery and development through computational approaches. Learners will understand AI applications in target identification, molecule generation, virtual screening, molecular modeling, and optimization of drug candidates to improve speed, efficiency, and success rates.

Inclus

6 vidéos1 devoir1 plugin

6 vidéosTotal 26 minutes

2.1 AI for Protein and Molecular Design5 minutes
2.2 AI-Driven Drug Screening and Multi-Target Design5 minutes
2.3 AI for ADMET Profiling4 minutes
2.4 AI-Powered Drug Repurposing and Target Identification5 minutes
2.5 AI for Natural Product and Peptide Discovery4 minutes
2.6 Case Studies4 minutes

1 devoirTotal 30 minutes

Quiz 230 minutes

1 pluginTotal 5 minutes

Activity: Drag and Drop5 minutes

Examines the role of AI in designing, managing, and optimizing clinical trials. This module covers patient recruitment, trial design, data analysis, real-world evidence generation, predictive analytics, and AI-powered solutions that enhance clinical trial efficiency and outcomes.

Inclus

6 vidéos1 devoir1 plugin

6 vidéosTotal 27 minutes

3.1 AI-Enhanced Patient Recruitment6 minutes
3.2 Decentralized and AI-Augmented Trial Operations6 minutes
3.3 Bayesian Adaptive Designs4 minutes
3.4 AI for Dose Optimization4 minutes
3.5 Digital Twins for Trial Simulation5 minutes
3.6 Case Study: Pfizer's AI and Digital Biomarkers in Oncology Trials (2024–2025)3 minutes

1 devoirTotal 30 minutes

Quiz 330 minutes

1 pluginTotal 5 minutes

Activity: Carousel5 minutes

Introduces the integration of AI with genomics, proteomics, and other multi-omics data to enable personalized healthcare approaches. Learners will explore how AI helps identify biomarkers, stratify patients, predict treatment responses, and support precision medicine strategies.

Inclus

5 vidéos1 devoir1 plugin

5 vidéosTotal 25 minutes

4.1 The Multi-Omics Landscape and Graph Neural Networks (GNNs) for Pathway Analysis5 minutes
4.2 Single-Cell Analysis5 minutes
4.3 AI-Driven Personalized Treatment and Companion Diagnostics6 minutes
4.4 AI for Rare Disease and Orphan Drug Development5 minutes
4.5 Real-World Evidence and Case Study4 minutes

1 devoirTotal 30 minutes

Quiz 430 minutes

1 pluginTotal 5 minutes

Activity: Problem Statement5 minutes

Explores AI applications in regulatory processes, scientific documentation, and drug safety monitoring. This module covers AI-assisted medical writing, regulatory submission support, literature analysis, adverse event detection, signal management, and automation of pharmacovigilance workflows.

Inclus

4 vidéos1 devoir1 plugin

Focuses on the responsible adoption of AI within pharmaceutical organizations. Learners will examine AI governance frameworks, data privacy, regulatory expectations, transparency, bias mitigation, validation requirements, and ethical considerations for safe and trustworthy AI implementation.

Inclus

4 vidéos1 devoir1 plugin

Explores emerging AI innovations shaping the future of the pharmaceutical industry. This module covers generative AI, digital twins, AI-powered automation, advanced analytics, and future trends that are expected to influence research, development, manufacturing, and healthcare delivery.

Inclus

4 vidéos1 devoir1 plugin

Provides an opportunity to apply AI concepts and industry knowledge to a practical pharmaceutical use case. Learners will develop a project involving AI strategy, problem identification, solution design, and evaluation while demonstrating how AI can address real-world challenges in pharma.

Inclus

1 vidéo1 devoir1 plugin

Inclus

7 vidéos

Instructeur

AI CERTs Team

AI CERTs

62 Cours64 661 apprenants

Offert par

AI CERTs

Pour quelles raisons les étudiants sur Coursera nous choisissent-ils pour leur carrière ?

Felipe M.

Étudiant(e) depuis 2018

’Pouvoir suivre des cours à mon rythme à été une expérience extraordinaire. Je peux apprendre chaque fois que mon emploi du temps me le permet et en fonction de mon humeur.’

Jennifer J.

Étudiant(e) depuis 2020

’J'ai directement appliqué les concepts et les compétences que j'ai appris de mes cours à un nouveau projet passionnant au travail.’

Larry W.

Étudiant(e) depuis 2021

’Lorsque j'ai besoin de cours sur des sujets que mon université ne propose pas, Coursera est l'un des meilleurs endroits où se rendre.’

Chaitanya A.

’Apprendre, ce n'est pas seulement s'améliorer dans son travail : c'est bien plus que cela. Coursera me permet d'apprendre sans limites.’

Débloquez l'accès à plus de 10 000 cours grâce à un abonnement
Faites progresser votre carrière avec un diplôme en ligne
Obtenez un diplôme auprès d’universités de renommée mondiale - 100 % en ligne
Rejoignez les 4 700 entreprises internationales qui ont choisi Coursera for Business.

Foire Aux 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 course materials, assignments, and earn a Certificate, you'll need to purchase the Certificate experience when you enroll in a course. Eligible learners may also have the option to start with a Free Trial. Some courses may also offer a Full Course, No Certificate option. This lets you access course materials, submit required assessments, and receive a final grade, but you won't be able to earn or purchase a Certificate.