About this Course
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100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 13 hours to complete

Suggested: 5 hours/week...

English

Subtitles: English
User
Learners taking this Course are
  • Data Scientists
  • Machine Learning Engineers
  • Data Analysts
  • Entrepreneurs
  • Data Engineers

What you will learn

  • Check

    Project structure of interactive Python data applications

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    Python web server frameworks: (e.g.) Flask, Django, Dash

  • Check

    Best practices around deploying ML models and monitoring performance

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    Deployment scripts, serializing models, APIs

Skills you will gain

Python ProgrammingBig Data ProductsRecommender Systems
User
Learners taking this Course are
  • Data Scientists
  • Machine Learning Engineers
  • Data Analysts
  • Entrepreneurs
  • Data Engineers

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 13 hours to complete

Suggested: 5 hours/week...

English

Subtitles: English

Course Highlight

featured

Real-world Project

Deploy data products

Use the tools and techniques required to deploy working recommender systems on real-world datasets.

Syllabus - What you will learn from this course

Week
1
2 hours to complete

Introduction

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
1 hour to complete

Implementing Recommender Systems

4 videos (Total 36 min), 3 quizzes
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
1 hour to complete

Deploying Recommender Systems

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
2 hours to complete

Project 4: Recommender System

2 readings, 1 quiz
2 readings
Project Description10m
How to Find a Dataset10m

Instructors

Avatar

Ilkay Altintas

Chief Data Science Officer
San Diego Supercomputer Center
Avatar

Julian McAuley

Assistant Professor
Computer Science

About University of California San Diego

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory....

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

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • 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.

More questions? Visit the Learner Help Center.