Managing Machine Learning Projects
Learn to manage projects involved in machine learning with the Managing Machine Learning Projects certification course.
Beginner
Online
2 Weeks
1,699 INR Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The Managing Machine Learning Projects certification course is a lunch of Duke University’s Pratt School of Engineering, and Coursera. This is course number 2 of the main AI Product Management Specialization programme. The course has a main focus on the practical aspects related to the management of projects in machine learning.
The Managing Machine Learning Projects training will take around 18 hours to get completed. This Coursera programme will walk every participant through different processes like data collection, building of a model, data collection, deployment, and maintenance of the systems of production. Apart from the above the candidates will also be taught processes in data science so that decision making in ML systems can be easier.
The Highlights
- Online course
- Shareable Certificate
- 2 weeks for completion
- Course subtitle is English
Programme Offerings
- Flexible Deadlines
- Short Programme
- Beginner level course.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Duke University, DurhamCoursera |
Managing Machine Learning Projects Fee Details
Description | Total Fee in INR |
Course Fee, 1 month | Rs. 1,699 |
Course Fee, 3 months | Rs. 3,499 |
Course Fee, 6 months | Rs. 5,199 |
Eligibility Criteria
Certification Qualifying Details
The Managing Machine Learning Projects certification by Coursera is offered after it is completed.
What you will learn
Here are the learning from the Managing Machine Learning Projects certification syllabus:
- The candidates will be able toIdentify different kinds of opportunities where they will be able to make an application of machine learning concepts.
- Learning to apply different processes of data science for organization of ML projects.
- The students will also be evaluating the key technologies in the design of Machine Learning.
- Ultimately the participants will be leading ML projects with the help of ideation projects by making use of the best available practices.
Who it is for
ML Engineers can benefit from the Managing Machine Learning Projects certification course by becoming more knowledgeable.
Admission Details
To get admission to the Managing Machine Learning Projects classes, the students can follow these steps:
Step 1: Follow the official URL: https://www.coursera.org/learn/managing-machine-learning-projects
Step 2: Then scroll to the spot where one can locate the ‘Enrol Now’ button.
Step 3: Next, the final step towards the admission process will be making accounts, and making a choice of their schedule to submit the fee, and seek admission.
The Syllabus
Videos
- Specialization Overview
- Instructor Introduction
- Course Overiew
- Introduction & Objectives
- Identifying Opportunities
- Validating Product Ideas
- Benefits of ML in Products
- ML vs. Heuristics
- Module Wrap-up
Readings
- About the Course
- Download Module Slides
- Identifying Good Problems for ML
Practice Exercise
- Module 1 Quiz
Videos
- 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
Readings
- Download Module Slides
- Why are ML Projects so Hard to Manage
Practice Exercise
- Module 2 Quiz
Videos
- Introduction and Objectives
- Data Needs
- Data Collection
- Data Governence & Access
- Data Cleaning
- Preparing Data for Modeling
- Reproducibility & Versioning
- Module Wrap-up
Readings
- Download Module Slides
- How We Improved Data Discovery for Data Scientists at Spotify
Practice Exercise
- Module 3 Quiz
Videos
- 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
Readings
- Download Module Slides
- Why Jupyter is Data Science's Computational Notebook of Choice
Practice Exercise
- Module 4 Quiz
Videos
- Introduction and Objectives
- ML System Failures
- ML System Monitoring
- Model Maintenance
- Model Versioning
- Organizational Considerations
- Module Wrap-up
- Course Wrap-up
Readings
- Download Module Slides
- Google’s Medical AI was Super Accurate in a Lab. Real Life was a Different Story.
Practice Exercise
- Module 5 Quiz
Instructors
Duke University, Durham Frequently Asked Questions (FAQ's)
The ML Projects course has been rated 4.6 stars.
No prior ML knowledge is needed.
Yes only English subtitles can be played for this programme
The instructor’s name is Jon Reifschneider.
Duke University is the partnering institution.