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Quick Facts

Medium Of InstructionsMode Of LearningMode Of Delivery
EnglishSelf StudyVideo 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
  • 18 hours for completion
  • Course subtitle is English

Programme Offerings

  • Flexible Deadlines
  • Short Programme
  • Beginner level course

Courses and Certificate Fees

Certificate AvailabilityCertificate Providing Authority
yesDuke University, DurhamCoursera

Eligibility Criteria

Certification Qualifying Details
The Managing Machine Learning Projects certification by Coursera is offered after it is completed. 

What you will learn

Project managementMachine learningPredictive Modeling knowledge

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)

1: What’s the average rating for the Managing Machine Learning Projects online course?

The ML Projects course has been rated 4.6 stars.

2: Is prior machine learning knowledge a need for enrolling into the course?

No prior ML knowledge is needed.

3: Is English the only subtitle for this programme?

Yes only English subtitles can be played for this programme

4: Name the instructor for the Managing Machine Learning Projects programme?

The instructor’s name is Jon Reifschneider.

5: Who supports Coursera for designing this course?

Duke University is the partnering institution.

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