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. 17 hours to complete

Suggested: 9 hours/week...

English

Subtitles: English

What you will learn

  • Check

    Project structure of interactive Python data applications

  • Check

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

  • Check

    Best practices around deploying ML models and monitoring performance

  • Check

    Deployment scripts, serializing models, APIs

Skills you will gain

Python ProgrammingBig Data ProductsRecommender Systems

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 17 hours to complete

Suggested: 9 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
2 hours to complete

Introduction

Welcome to the first week of Deploying Machine Learning Models! 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 recommender systems and differentiate it from other types of machine learning

...
3 videos (Total 31 min), 3 readings, 3 quizzes
3 videos
Recommender Systems versus Other Forms of Supervised Learning7m
Collaborative Filtering-Based Recommendation19m
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
19 minutes to complete

Implementing Recommender Systems

This week, we will learn how to implement a similarity-based recommender, returning predictions similar to an user's given item. We will cover how to optimize these models based on gradient descent and Jaccard similarity.

...
3 quizzes
3 practice exercises
Review: Similarity-Based Recommenders5m
Review: Implementing Latent Factor Models4m
Implementing Recommender Systems10m
Week
3
5 minutes to complete

Deploying Recommender Systems

This week, we will learn about Python web server frameworks and the overall structure of interactive Python data applications. We will also cover some tips for best practices on deploying and monitoring your applications.

...
1 quiz
1 practice exercise
Deploying Recommender Systems5m
Week
4
2 hours to complete

Project 4: Recommender System

For this final project, you will build a recommender system of your own. Find a dataset, clean it, and create a predictive system from the dataset. This will help prepare you for the upcoming capstone, where you will harness your skills from all courses of this specialization into one single project!

...
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
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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.