Engineer AI Models: Explain, Tune & Experiment prepares program and project managers to guide AI projects beyond “just working” toward being trusted, explainable, and reproducible. You’ll learn how feature engineering and hyperparameter tuning improve model performance, how explainability methods like SHAP and LIME build stakeholder confidence, and how structured experimentation ensures reliable results. Through real-world scenarios — from boosting fraud detection F1 scores, to presenting credit approval models to risk committees, to planning experiments in Jupyter — you’ll gain the skills to ask the right questions, guide technical teams, and translate complex model outputs into business impact. By the end, you’ll know how to move AI projects from black box to business-ready.
Erwerben Sie mit Coursera Plus für 199 $ (regulär 399 $) das nächste Level. Jetzt sparen.
Empfohlene Erfahrung
Kompetenzen, die Sie erwerben
- Kategorie: Performance Metric
- Kategorie: Fraud detection
- Kategorie: Business Analytics
- Kategorie: Feature Engineering
- Kategorie: Model Evaluation
- Kategorie: Jupyter
- Kategorie: Research Design
- Kategorie: Performance Improvement
- Kategorie: Responsible AI
- Kategorie: Technical Communication
- Kategorie: Performance Analysis
- Kategorie: Project Management
- Kategorie: Risk Modeling
- Kategorie: Credit Risk
- Kategorie: Applied Machine Learning
- Kategorie: Test Engineering
- Kategorie: Test Planning
- Kategorie: Performance Tuning
Wichtige Details
Zu Ihrem LinkedIn-Profil hinzufügen
Dezember 2025
Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.
In diesem Kurs gibt es 1 Modul
Engineer AI Models: Explain, Tune & Experiment prepares program and project managers to guide AI projects beyond “just working” toward being trusted, explainable, and reproducible. You’ll learn how feature engineering and hyperparameter tuning improve model performance, how explainability methods like SHAP and LIME build stakeholder confidence, and how structured experimentation ensures reliable results. Through real-world scenarios — from boosting fraud detection F1 scores, to presenting credit approval models to risk committees, to planning experiments in Jupyter — you’ll gain the skills to ask the right questions, guide technical teams, and translate complex model outputs into business impact. By the end, you’ll know how to move AI projects from black box to business-ready.
Das ist alles enthalten
5 Videos3 Lektüren4 Aufgaben
Dozent
von
Mehr von Machine Learning entdecken
Status: Kostenloser Testzeitraum
Status: Kostenloser TestzeitraumScrimba
Status: Kostenloser Testzeitraum
Warum entscheiden sich Menschen für Coursera für ihre Karriere?
Häufig gestellte Fragen
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Weitere Fragen
Finanzielle Unterstützung verfügbar,
¹ Einige Aufgaben in diesem Kurs werden mit AI bewertet. Für diese Aufgaben werden Ihre Daten in Übereinstimmung mit Datenschutzhinweis von Courseraverwendet.