Intro to machine learning
Course summary
In this course, you'll discover how machine learning is revolutionising the way medicines are produced. We'll cover the basics of machine learning, explore its applications in the pharmaceutical industry, and provide practical insights to help you understand and implement these technologies. Whether you're new to the field or looking to expand your knowledge, this course will guide you through the exciting intersection of technology and medicines manufacturing.
During this course, you’ll gain:
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An introduction to machine learning, emphasising its transformative role in medicine manufacturing.
A comprehensive glossary of machine learning terminology to navigate the field effectively.
An overview of the various types of machine learning, alongside the most utilised algorithms.
Insights into data preparation and the intricacies of training machine learning models.
Strategies for selecting the most effective algorithm and evaluating its performance.
An exploration of the challenges faced when implementing machine learning.
Guidance on optimising processes and making informed decisions with machine learning models.
The course culminates in a series of specific case studies, showcasing real-world examples of machine learning within CMAC. These case studies are designed to provide you with practical insights and understanding of how machine learning can be used to innovate and improve outcomes in the medicines manufacturing industry.
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Professionals in medicines manufacturing - Engineers, scientists, and technicians working in pharmaceutical and biopharmaceutical manufacturing who want to understand and implement machine learning in production processes.
Research and academics - Those involved in pharmaceutical research, process development, and computational modelling who seek to integrate machine learning into their work.
Students and early career professionals - Those studying machine learning, artificial intelligence, or pharmaceutical sciences and looking to explore real-world applications in medicine manufacturing.
Available now
Format: E-learning
Duration: 1 hour (approx)
Cost: Free
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