This course is designed for business professionals that want to learn how to gather results from previous stages of the data science project and present them to stakeholders. Learners will communicate the results of a model to stakeholders, be shown how to build a basic web app to demonstrate machine learning models and implement and test pipelines that automate the model training, tuning and deployment processes.
Finalize a Data Science Project
Finalize a Data Science Project
This course is part of CertNexus Certified Data Science Practitioner Professional Certificate
Instructors: Sarah Haq
Sponsored by InternMart, Inc
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
12 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Communicate results of a model via web apps, and implement an d test pipelines that automate the model training, tuning and deployment process.
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
3 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your Data Analysis expertise
This course is part of the CertNexus Certified Data Science Practitioner Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from CertNexus
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 4 modules in this course
In the previous courses in this specialization, you put your data through the extract, transform, and load (ETL) process, conducted an analysis of the data, and developed statistical models from the data that cover the three major disciplines of machine learning: classification, regression, and clustering. But you're not done yet. Now it's time to gather your results and present them to stakeholders. After all, you undertook the data science project to achieve business goals, so you need to demonstrate that you were actually successful in doing so. In this first module, you'll report your findings to the project's stakeholders.
What's included
6 videos3 readings1 assignment1 peer review1 discussion prompt
One way to create a robust and interesting presentation is to show off your results in a web app. In this module, you'll focus on some of the major technologies that go into creating a web app that you might want to use in a demonstration.
What's included
7 videos2 readings1 assignment1 discussion prompt
Much of what you've done throughout the data science project can be automated in some way. The goal is to spend less time performing some of the more repetitive tasks, and more time on tasks that require your own judgment. This is where pipeline automation comes into play.
What's included
6 videos2 readings1 assignment1 discussion prompt1 ungraded lab
You'll work on a project in which you'll apply your knowledge of the material in this course to practical scenarios.
What's included
1 peer review1 ungraded lab
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