The framework helps you capture and categorize your customer’s wants and needs. Once you’re able to understand your customer’s needs, you can understand what needs aren’t being met and what solutions should be built to respond to those needs. In summary, it helps you drive value for your customers.
Module 1 : What Is AI Engineering?
After this lesson, learners will be able to:
Identify where AI adds real business value
Apply Jobs-To-Be-Done (JTBD) for problem discovery
Score AI ideas using Pain Ă— Frequency Ă— Cost Ă— Urgency
Prioritize high-ROI AI opportunities
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Module 2 :Data Foundations
Data is the backbone of any AI or Machine Learning system. High-quality, well-structured, and relevant data dramatically improves model performance, accuracy, and reliability. Understanding how data is collected, processed, and prepared is essential for building robust AI solutions.
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Module 3: ML Fundamentals for Engineers
Machine Learning (ML) enables systems to automatically learn patterns from data and make predictions or decisions. Engineers must understand the core types of ML problems, how to evaluate models, and how to manage errors and generalization to build reliable AI systems.
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