Generative AI Leader
In this course, you will take a journey from a broad overview of gen AI to understanding how to leverage gen AI and Google Cloud for organizational transformation.
2 d
Fundamental
GCPSPARKSDRUGDISCOVERY
Drug Discovery Essentials on Google Cloud Training
This course provides learners with the essential skills to leverage Google Cloud AI and Machine Learning to transform the Drug Discovery (R&D) pipeline. It focuses on accelerating time-to-market and enhancing precision by overcoming the industry's challenges of high cost, long timelines, and low success rates through data and automation.
The course is structured around the practical application of key technologies. Learners will gain an understanding of: the AI paradigms (Deep Learning, GNNs, Generative AI); the unified MLOps platform of Vertex AI for building scalable, reproducible pipelines; the role of BigQuery and specialized Accelerators in handling petabyte-scale omics data; and the critical importance of ethical governance and XAI in highly regulated scientific research.
What you will learn
- Describe the value of leveraging AI and ML to enhance drug discovery processes
- Use Vertex AI to streamline drug discovery workflows
- Identify applications of generative AI in drug discovery
- Analyze omics and clinical trial data using Google Cloud tools
Prerequisites
- Google Cloud basics and familiarity with Machine Learning basics will be helpful but not essential
Target audience
- Pharmaceutical leaders, Biotech leaders, Scientists
Training Program
4 modules to master the fundamentals
Objectives
- Describe the value of leveraging AI and ML to enhance drug discovery processes
Topics covered
- →How AI impacts the drug discovery pipeline
- →Next-gen tools
- →Google Cloud for drug discovery
- →Security and compliance
Objectives
- Use Vertex AI to streamline drug discovery workflows
Topics covered
- →What is Vertex AI
- →The anatomy of a pipeline
- →End-to-end pipeline workflow
Activities
1 use case demos
Objectives
- Identify applications of generative AI in drug discovery
Topics covered
- →What is Generative AI?
- →Core applications in drug discovery
- →GCP AI toolkit
- →Challenges and best practices
Objectives
- Analyze omics and clinical trial data using Google Cloud tools
Topics covered
- →Harnessing genomics with BigQuery
- →AI for proteomics
- →Integrated clinical and real-world data
- →Looking ahead: The future of AI in drug discovery
Activities
1 use case demos
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1 d
Fundamental
Upcoming sessions
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We regularly organize new sessions. Contact us to find out about upcoming dates or to schedule a session at a date of your choice.
Register for a custom dateQuality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
Teaching Methods Used
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
- Group Discussion — Open exchange among peers and the instructor on a specific topic.
Evaluation and Monitoring System
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Frequently Asked Questions
This course is for data scientists, bioinformaticians, ML engineers, and R&D professionals in life sciences who want to accelerate the drug discovery pipeline with Google Cloud AI and ML.
A basic understanding of machine learning concepts and life sciences R&D is recommended, as this is an intermediate, level-200 course.
You will learn the value of AI and ML for drug discovery, how to use Vertex AI to streamline workflows, the applications of generative AI, and how to analyze omics and clinical trial data with Google Cloud tools.
A dedicated module covers building AI pipelines for drug discovery with Vertex AI, the unified MLOps platform for creating scalable, reproducible pipelines across the R&D process.
The course lasts 3 hours and is delivered in an instructor-led format, combining conceptual explanations with practical demonstrations.
Yes. This is an official Google Cloud Sparks course delivered by SFEIR Institute, a certified Google Cloud Training Partner.
Train multiple employees
- Volume discounts (multiple seats)
- Private or custom session
- On-site or remote
Cloud Sparks Program