Duke University - Managing Machine Learning Projects
- Offered byCoursera
Managing Machine Learning Projects at Coursera Overview
Duration | 18 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Managing Machine Learning Projects at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 2 of 3 in the AI Product Management
Managing Machine Learning Projects at Coursera Course details
- The course walks through the keys steps of a ML project from how to identify good opportunities for ML through data collection, model building, deployment, and monitoring and maintenance of production systems.
- Participants will learn about the data science process and how to apply the process to organize ML efforts, as well as the key considerations and decisions in designing ML systems.
- At the conclusion of this course, you should be able to:
- 1) Identify opportunities to apply ML to solve problems for users
- 2) Apply the data science process to organize ML projects
- 3) Evaluate the key technology decisions to make in ML system design
- 4) Lead ML projects from ideation through production using best practices
Managing Machine Learning Projects at Coursera Curriculum
Identifying Opportunities for Machine Learning
Specialization Overview
Instructor Introduction
Course Overiew
Introduction & Objectives
Identifying Opportunities
Validating Product Ideas
Benefits of ML in Products
ML vs. Heuristics
Module Wrap-up
About the Course
Download Module Slides
Identifying Good Problems for ML
Module 1 Quiz
Organizing ML Projects
Introduction and Objectives
ML Projects vs. Software Projects
CRISP-DM Data Science Process
CRISP-DM Case Study
Team Organization
Organizing the Project
Measuring Performance
Module Wrap-up
Download Module Slides
Why are ML Projects so Hard to Manage
Module 2 Quiz
Data Considerations
Introduction and Objectives
Data Needs
Data Collection
Data Governence & Access
Data Cleaning
Preparing Data for Modeling
Reproducibility & Versioning
Module Wrap-up
Download Module Slides
How We Improved Data Discovery for Data Scientists at Spotify
Module 3 Quiz
ML System Design & Technology Selection
Introduction and Objectives
ML System Design Considerations
Cloud vs. Edge
Online Learning & Inference
ML on Big Data
ML Technology Selection
Common ML Tools
Module Wrap-up
Download Module Slides
Why Jupyter is Data Science's Computational Notebook of Choice
Module 4 Quiz
Model Lifecycle Management
Introduction and Objectives
ML System Failures
ML System Monitoring
Model Maintenance
Model Versioning
Organizational Considerations
Module Wrap-up
Course Wrap-up
Download Module Slides
Google's Medical AI was Super Accurate in a Lab. Real Life was a Different Story.
Module 5 Quiz
Managing Machine Learning Projects at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
Anything you would want to ask experts?
Data ScienceMachine LearningMachine Learning and Pattern RecognitionManaging Machine Learning Projects