Stevens Institute of Technology
Graduate Certificate in Application of ML to Pharma Development
How this program compares
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Admission Snapshot
Typical admitted student: A bachelor's degree in a STEM field such as computer science, data science, pharmaceutical sciences, or related discipline with a minimum GPA of 3.0 is required. Relevant programming experience in Python or R and coursework in statistics or machine learning is often preferred.
About This Program
This program provides professionals in the life sciences with the tools to implement machine learning solutions in pharmaceutical research.
Career Outcomes
Gain machine learning skills to advance as Data Analyst in Healthcare AI
- 1. ML Engineer in Drug Discovery
- 2. Data Scientist in Pharmaceuticals
- 3. AI Specialist in Clinical Development
- 4. Bioinformatics Analyst in Pharma R&D
What You'll Learn
- Apply ML algorithms to predict drug-target interactions and efficacy.
- Develop AI models for accelerating pharmaceutical discovery pipelines.
- Analyze pharma datasets for clinical trial design and optimization.
- Implement deep learning for molecular modeling and compound screening.
Curriculum Highlights
The structure includes courses on data mining, predictive analytics, and specialized modules for machine learning in drug development.
Top Employers
Top employers include pharmaceutical giants like Pfizer, Novartis, Roche, and biotech firms such as Moderna and Gilead.
Admissions
A bachelor's degree in a STEM field such as computer science, data science, pharmaceutical sciences, or related discipline with a minimum GPA of 3.0 is required. Relevant programming experience in Python or R and coursework in statistics or machine learning is often preferred.
Application Materials
- Statement of Purpose: Required
- Letters of Recommendation: 2β3
- Resume: Required
- Transcripts: Official transcripts required
Academic Requirements
- Degree Required: Bachelor's degree
- GRE/GMAT: Not Required
- TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)
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