Certified Specialist Programme in Machine Learning for Pharma
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- Introduction to Machine Learning in Pharma
- Drug Discovery and Development using Machine Learning
- Pharmaceutical Data Handling and Preprocessing
- Machine Learning Algorithms for Drug Design (including deep learning)
- Regulatory Considerations and Ethical Implications of AI in Pharma
- Predictive Modeling for Clinical Trials
- Deployment and Validation of Machine Learning Models in a Pharma Setting
- Advanced Topics: Generative Models and Reinforcement Learning in Pharma
- Case Studies in Pharmaceutical Machine Learning
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Career Roles in Machine Learning (Pharma) - UK Description Machine Learning Engineer (Pharma) Develop and implement machine learning algorithms for drug discovery, clinical trials, and personalized medicine.
High demand for expertise in Python and TensorFlow.
AI/ML Scientist (Pharmaceuticals) Conduct research and development in advanced machine learning techniques, focusing on applications within the pharmaceutical industry.
Strong statistical modelling skills are crucial.
Data Scientist (Pharma) Extract actionable insights from large pharmaceutical datasets, leveraging machine learning for predictive modelling and business decision-making.
Requires experience with SQL and big data technologies.
Bioinformatics Scientist (ML Focus) Apply machine learning to analyze biological data, contributing to drug design and development.
Proficiency in bioinformatics tools and programming languages is essential.
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- BasicUnderstandingSubject
- ProficiencyEnglish
- ComputerInternetAccess
- BasicComputerSkills
- DedicationCompleteCourse
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- ThreeFourHoursPerWeek
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- TwoThreeHoursPerWeek
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