Managing Machine Learning Projects
Learn practical aspects of managing ML projects from Duke University
Perfect for: Product managers looking to lead ML initiatives and bridge the gap between business needs and ML implementation
Key outcome: Ability to manage ML projects from ideation through production using proven frameworks
Prerequisites: Basic understanding of product management principles
What Sets This Course Apart
This course provides a practical, end-to-end framework for managing machine learning projects specifically designed for product managers. Unlike technical ML courses, it focuses on the strategic and managerial aspects of implementing ML solutions, helping PMs make informed decisions without needing deep technical expertise.
Course Journey
- ML Opportunity Identification
- Evaluating problems suitable for ML solutions
- Assessing business value and feasibility
- Data Science Process Framework
- Structured approach to ML projects
- Key milestones and deliverables
- ML System Design
- Critical technology decisions
- Architecture considerations
- Production Implementation
- Deployment strategies
- Monitoring and maintenance
- Project Leadership
- Best practices for ML project management
- Stakeholder management in ML context
Learning Experience
- Format: Interactive lectures and practical assignments
- Assessments: 5 hands-on assignments
- Tools: Industry-standard ML project management frameworks
- Projects: Real-world ML project planning and execution
- Support: Peer discussion forums and instructor guidance
Is This Course Right For You?
✅ Consider this course if:
- You need to manage teams working on ML projects
- You want to understand ML project lifecycles without deep technical knowledge
- You're looking to transition into AI product management
- You need practical frameworks for ML project execution
⚠️ This might not be for you if:
- You're seeking hands-on coding or model building skills
- You need advanced technical ML knowledge
- You have no basic product management experience
- You're looking for general project management training
Time & Commitment
- Weekly pace: 6 hours/week recommended
- Flexibility: Complete at your own pace within course schedule
- Start date: February 9, 2024
- Duration: Designed for 3-week completion
Investment & Returns
- Cost structure:
- Included with Coursera Plus subscription
- 7-day free trial available
- Financial aid available for eligible students
- Career impact:
- Part of comprehensive AI Product Management Specialization
- LinkedIn-shareable certificate
- Practical ML project management skills
- Industry-recognized credential
Skills You'll Gain
- ML project lifecycle management
- Data science process application
- ML system design evaluation
- Project leadership in ML context
- Cross-functional team coordination
Part of AI Product Management Specialization
This course is the second module in a broader specialization, providing a foundation for AI product management. Enrolling gives you access to the complete specialization pathway.