All programmesApplied AI & Engineering
Applied AI & Machine Learning Engineering
Prepare data, engineer features, train and evaluate models, and deliver practical AI applications with reproducible engineering habits.
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Capabilities to practise and demonstrate.
Computer Science, BCA/MCA, engineering, mathematics, statistics and quantitative science learners; developers and analysts transitioning toward AI/ML.
Learning focus
Python, Git and data foundationsStatistics and exploratory analysisSupervised and unsupervised MLModel validation and error analysisLLM application patterns and APIsFastAPI, testing and deployment
Portfolio and outcome evidence
Reproducible EDA project
Model comparison report
End-to-end ML project
Deployed demonstration or API with limitations register
Source document
TIFES_Applied_AI_Machine_Learning_Engineering_Brochure.html. The original supplied brochure/curriculum is preserved in the project at content/source-documents. Exact module sequencing and delivery details should be confirmed from that source before cohort launch.