About this Course

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Flexible deadlines
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Approx. 11 hours to complete
English
Subtitles: English

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 ProgrammingBig Data ProductsRecommender Systems
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 11 hours to complete
English
Subtitles: English

Offered by

University of California San Diego logo

University of California San Diego

Syllabus - What you will learn from this course

Week
1

Week 1

2 hours to complete

Introduction

2 hours to complete
5 videos (Total 54 min), 3 readings, 3 quizzes
5 videos
Recommender Systems versus Other Forms of Supervised Learning7m
Collaborative Filtering-Based Recommendation19m
Latent Factor Models (Part 1)11m
Latent Factor Models (Part 2)11m
3 readings
Syllabus10m
Course Materials10m
Setting Up Your System10m
3 practice exercises
Review: Recommender Systems4m
Review: Introduction to Latent Factor Models4m
Recommender Systems and Latent Factor Models20m
Week
2

Week 2

1 hour to complete

Implementing Recommender Systems

1 hour to complete
4 videos (Total 36 min)
4 videos
Similarity-Based Recommender for Rating Prediction7m
Implementing a Latent Factor Model (Part 1)11m
Implementing a Latent Factor Model (Part 2)6m
3 practice exercises
Review: Similarity-Based Recommenders5m
Review: Implementing Latent Factor Models4m
Implementing Recommender Systems10m
Week
3

Week 3

1 hour to complete

Deploying Recommender Systems

1 hour to complete
3 videos (Total 17 min), 1 reading, 2 quizzes
3 videos
Intro to Django5m
Flask7m
1 reading
Setting up Your Workspace with Docker: Django10m
2 practice exercises
Review: Flask and Django30m
Deploying Recommender Systems5m
Week
4

Week 4

2 hours to complete

Project 4: Recommender System

2 hours to complete
2 readings
2 readings
Project Description10m
How to Find a Dataset10m

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

  • 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.

  • 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.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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