University of California San Diego
Design Thinking and Predictive Analytics for Data Products
University of California San Diego

Design Thinking and Predictive Analytics for Data Products

This course is part of Python Data Products for Predictive Analytics Specialization

Taught in English

Some content may not be translated

Julian McAuley
Ilkay Altintas

Instructors: Julian McAuley

9,467 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.5

(62 reviews)

Intermediate level
Some related experience required
8 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

12 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.5

(62 reviews)

Intermediate level
Some related experience required
8 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Python Data Products for Predictive Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • 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
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There are 5 modules in this course

Welcome to the second course in this specialization! This week, we will go over the syllabus, download all course materials, and get your system up and running for the course. We will also introduce the basics of supervised learning and regression.

What's included

5 videos4 readings3 quizzes2 discussion prompts

This week, we will learn what features are in a dataset and how we can work with them through cleaning, manipulation, and analysis in Jupyter notebooks.

What's included

4 videos1 reading3 quizzes

This week, we will learn about classification and several ways you can implement it, such as K-nearest neighbors, logistic regression, and support vector machines.

What's included

4 videos3 quizzes1 discussion prompt

This week, we will learn the importance of properly training and testing a model. We will also implement gradient descent in both Python and TensorFlow.

What's included

5 videos3 quizzes

In the final week of this course, you will continue building on the project from the first course of Python Data Products for Predictive Analytics with simple predictive machine learning algorithms. Find a dataset, clean it, and perform basic analyses on the data.

What's included

2 readings1 peer review1 discussion prompt

Instructors

Instructor ratings
4.4 (12 ratings)
Julian McAuley
University of California San Diego
5 Courses30,182 learners
Ilkay Altintas
University of California San Diego
14 Courses485,132 learners

Offered by

Recommended if you're interested in Data Analysis

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4.5

62 reviews

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AM
4

Reviewed on May 7, 2021

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