In the first course of Duke University's AI Product Management Specialization, you will gain a foundational understanding of machine learning. This non-coding course will cover the basics of machine learning technology, including its definition, working principles, and its applications. The course emphasizes the importance of this knowledge for effectively managing AI teams and products and collaborating with data scientists, software engineers, and customers.
Key topics covered in the course include developing machine learning models, evaluating and interpreting these models, and understanding the intuition behind common machine learning and deep learning algorithms. The course concludes with a machine learning-based project, where you will have the opportunity to train and optimize a machine learning model for a real-world problem.
By the end of the course, you will be able to:
- Explain the functioning of machine learning and understand its various types.
- Recognize the challenges involved in modeling and apply strategies to overcome them.
- Identify the main algorithms for different machine learning tasks and understand their specific use cases.
- Describe deep learning, its strengths, and the challenges it presents compared to other forms of machine learning.
- Implement best practices for evaluating and interpreting machine learning models.
🆓 Free to Audit
🕒 Approx. 15 Hours
✏️ Beginner Level
🧾 Paid Certificate Available Upon Completion
🎓 Offered by Duke University via Coursera
