As a graduate, you will be prepared to reliably demonstrate the ability to:
- Develop an optimized Machine Learning model based on the selection and hyperparameter tuning of different algorithms.
- Justify the use of conventional, auto, and real-time Machine Learning algorithms, their trade-offs, and their utility with different datasets toward business solutions for actionable decision making.
- Generate prescriptions and predictions from trained deep learning models that use data to drive optimized business solutions.
- Build high performing, scalable supervised and unsupervised models to understand the underlying patterns of data in different contexts.
- Curate and construct training data sets to reduce machine and human bias for monitoring and mitigating adverse predictions while complying with regulatory frameworks and ethical standards.
- Propose and implement creative AI based business solutions drawing from academic and applied research in related subfields.
- Extract valuable insights from complex datasets through storytelling, visualization methods, wrangling, and preparation, to make data-driven decisions that contribute to business support and success.
- Leverage statistical, mathematical, and computational methodologies in the field of artificial intelligence to extract valuable insights and generate knowledge from data sets.
- Foster and maintain a collaborative environment that highlights teamwork, engages professional communication and constructive criticism, and shares creative solutions.