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

3.5
stars
50 ratings

Ilkay Altintas +1 more instructor

9,483 already enrolled

Offered By

Python Data Products for Predictive Analytics SpecializationUniversity of California San Diego

About this Course

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In this course we will learn about Recommender Systems (which we will study for the Capstone project), and also look at deployment issues for data products. By the end of this course, you should be able to implement a working recommender system (e.g. to predict ratings, or generate lists of related products), and you should understand the tools and techniques required to deploy such a working system on real-world, large-scale datasets.
This course is the final course in the Python Data Products for Predictive Analytics Specialization, building on the previous three courses (Basic Data Processing and Visualization, Design Thinking and Predictive Analytics for Data Products, and Meaningful Predictive Modeling). At each step in the specialization, you will gain hands-on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 4 of 4 in the

Python Data Products for Predictive Analytics Specialization

Approx. 10 hours to complete

English

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What you will learn

Project structure of interactive Python data applications
Python web server frameworks: (e.g.) Flask, Django, Dash
Best practices around deploying ML models and monitoring performance
Deployment scripts, serializing models, APIs

Skills you will gain

Python Programming
Big Data Products
Recommender Systems

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 4 of 4 in the

Python Data Products for Predictive Analytics Specialization

Approx. 10 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.4/5 (5 Ratings)

Ilkay Altintas

Chief Data Science Officer

San Diego Supercomputer Center

459,802 Learners

13 Courses

Julian McAuley

Offered by

University of California San Diego

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Syllabus - What you will learn from this course

Week1

Week 1

3 hours to complete

Introduction

3 hours to complete

5 videos (Total 54 min), 3 readings, 3 quizzes

5 videos

Introduction to Recommender Systems4mRecommender Systems versus Other Forms of Supervised Learning7mCollaborative Filtering-Based Recommendation19mLatent Factor Models (Part 1)11mLatent Factor Models (Part 2)11m

3 readings

Syllabus10mCourse Materials10mSetting Up Your System10m

3 practice exercises

Review: Recommender Systems30mReview: Introduction to Latent Factor Models30mRecommender Systems and Latent Factor Models20m

Week2

Week 2

1 hour to complete

Implementing Recommender Systems

1 hour to complete

4 videos (Total 36 min)

Week3

Week 3

1 hour to complete

Deploying Recommender Systems

1 hour to complete

3 videos (Total 17 min), 1 reading, 2 quizzes

Week4

Week 4

2 hours to complete

Project 4: Recommender System

2 hours to complete

2 readings

Reviews

3.5

16 reviews

5 stars
36%
4 stars
22%
3 stars
18%
2 stars
8%
1 star
16%

TOP REVIEWS FROM DEPLOYING MACHINE LEARNING MODELS

by MLDec 6, 2020

I Liked the Course in general especially the recommender component. I would seriously recommend making major improvements and clarification to the capstone project.

View all reviews

About the Python Data Products for Predictive Analytics Specialization

Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego.

This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy. You’ll also develop statistical models, devise data-driven workflows, and learn to make meaningful predictions for a wide-range of business and research purposes. Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills. Python Data Products for Predictive Analytics is taught by Professor Ilkay Altintas, Ph.D. and Julian McAuley. Dr. Alintas is a prominent figure in the data science community and the designer of the highly-popular Big Data Specialization on Coursera. She has helped educate hundreds of thousands of learners on how to unlock value from massive datasets.

Python Data Products for Predictive Analytics

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Deploying Machine Learning Models

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