Introduction to Machine Learning for Research Portfolio Analysis
Train your team on your schedule. Contact us to book your training.
Introduction to Machine Learning for Research Portfolio Analysis covers an introduction to machine learning, including an overview of types of machine learning relevant to research portfolio analysis. We cover topics including determining which software to use, training your algorithms using the “gold standard,” supervised and unsupervised machine learning, evaluating your machine learning model’s performance, overcoming common challenges, and addressing ethical considerations.
While no prerequisite is required for this class, we do recommend this course be taken following Research Portfolio Analysis: Framework & Design and Research Portfolio Analysis: Project Management.
Pricing:
Analytic teams are as diverse as the portfolios they manage. We customize our training to address the needs of your team and the projects they are working on.
Understand artificial intelligence (AI) and how machine learning (ML) is involved in AI
Understand the gold standard in AI and why it is so important
Determine which software to use for ML based on your inputs (data and training set)
Discuss ML confidently with peers and provide an assessment of the ethical concerns involved
Assess your ML outputs and the reliability of the product
The Analytics Research Institute Cancellation Policy
If a paid registrant cancels prior to an event, The ARI will issue a 100% registration credit that can be used within 12 months of the date of the event by anyone at the registering organization. Requests for cancellation must be emailed to info@the-ari.com at least one week prior to the start of the event.
At an in-person event, credits will not be issued for no-shows or for cancellations made within one week of the start of the event.
If The ARI cancels or postpones an event, The ARI will automatically issue a 100% registration credit that can be used within 12 months of the date of the event by anyone at the organization, and may be used toward any ARI event, service, or product.
Instructors
KIRK BAKER
Kirk is the founder and president of The Analytics Research Institute. Prior to his current work, he was an integral member of two successful health science startups in Maryland. He joined the founding members of The Zerhouni Group as a computational linguist, designing a pharma-based search and visualization tool that formed the basis of that company’s acquisition by i3 Analytics. As VP of Technical Development at i3 Analytics, he guided the development of the prototype into a full-fledged search and analytics platform used by many of the top organizations in the pharma industry.
Kirk received his Ph.D. from Ohio State, specializing in the application of statistical machine learning techniques to problems in natural language processing.
HEATHER ESHLEMAN
Heather joined the ARI in 2021 with extensive basic research experience in cell biology, microbiology, and infectious diseases. Heather is also a science analyst with Lexical Intelligence. Previously Heather was a postdoctoral research fellow at Massachusetts General Hospital and Harvard Medical School, where she studied the molecular mechanisms of bacterial pathogenesis. She is excited to use her experience in research and funding mechanisms to serve a broader role in supporting research in the life sciences.
Heather holds a Ph.D. in Biochemistry and Molecular Biology from the University of California, San Francisco, and a B.S. in Molecular Biology from the University of California, San Diego.