What experience level is required for Model Deployment and Maintenance for Data Scientists?

This course is aimed at the Intermediate level. Having some basic understanding of the topic will help you get the most out of the curriculum.

How long does it take to complete Model Deployment and Maintenance for Data Scientists?

The total duration of the course is approximately 37 minutes. Since it is generally self-paced, completion time depends entirely on your learning schedule and availability.

Is this course more theory-focused or project-focused?

This course provides a strong mix of conceptual theory and practical application to ensure a comprehensive understanding of the subject matter.

Information Technology

Model Deployment and Maintenance for Data Scientists

Name: Model Deployment and Maintenance for Data Scientists
Availability: InStock

The machine learning pipeline doesn't end at just building the model. This course will teach you how to deploy your machine learning models as application programming interface (API) endpoints, and the maintenance required to support the model.

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Security+

₹6,164/yr

₹12,327SAVE 50%

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Security+

₹734/mo

Core TechBilled Yearly

₹5,282

Core TechStart your learning journey with a strong foundation in the basics and access to over 3,900 courses

₹627/mo

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Course Insight

Suitable for intermediate learners. Works well as a continuation after mastering Information Technology fundamentals. It bridges the gap toward advanced, production-level engineering.

Intermediate FriendlySelf-Paced Learning

SKILLS TO
MASTER

Information Technology Basics

Fundamental principles and concepts

Practical Application

Real-world project implementation

Best Practices

Industry standard workflows and guidelines

Problem Solving

Core Concepts

Implementation

Workflow Integration

Optimization

Careers:Relevant for professionals pursuing roles within Information Technology.

Quick Facts

37 minutes

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What You’ll Learn

Machine learning models only become useful once they begin to support the business through a deployed application.

In this course, Model Deployment and Maintenance for Data Scientists, you'll gain the ability to run, monitor, and optimize machine learning models in production.

First, you'll explore options for deploying machine learning models as an API endpoint.

Next, you'll discover metrics and KPIs for the model you will need to monitor.

Finally, you'll learn how to iterate and improve on your model as time goes on.

When you're finished with this course, you'll have the skills and knowledge of deploying and maintaining machine learning models needed to productionalize your machine learning pipeline.

See how this course curriculum compares with alternatives