Machine Learning with PySpark: Recommender System
$9.99
ENROLL NOWCourse Overview
What You'll Learn
- This Guided Project was created to help data analysts and AI enthusiasts learn how to build scalable recommendation systems to enhance customer experience and drive sales.
- To be successful in this project, you should have basic Python programming skills, familiarity with data processing libraries like Pandas, a basic understanding of machine learning concepts, and some experience with APIs and data manipulation using SQL or PySpark.
Did you know that personalized product recommendations can increase sales by up to 20%? As consumers, we all appreciate suggestions tailored to our tastes, and as AI engineers, we can harness data to deliver that experience. This Guided Project was created to help data analysts and AI enthusiasts learn how to build scalable recommendation systems to enhance customer experience and drive sales. This 2-hour project-based course will teach you how to construct a data processing pipeline using PySpark, implement K-means clustering with OpenAI text embeddings, and develop a recommendation system that suggests products based on user behavior. To achieve this, you will create a personalized product recommendation system by working through a real-world scenario where an e-commerce company needs to improve its recommendation capabilities. This project is unique because it combines powerful tools like PySpark and OpenAI's embeddings for hands-on experience in creating data-driven recommendations. To be successful in this project, you should have basic Python programming skills, familiarity with data processing libraries like Pandas, a basic understanding of machine learning concepts, and some experience with APIs and data manipulation using SQL or PySpark.
Course FAQs
Is this an accredited online course?
Accreditation for 'Machine Learning with PySpark: Recommender System' is determined by the provider, Coursera Project Network. For online college courses or degree programs, we strongly recommend you verify the accreditation status directly on the provider's website to ensure it meets your requirements.
Can this course be used for continuing education credits?
Many of the courses listed on our platform are suitable for professional continuing education. However, acceptance for credit varies by state and licensing board. Please confirm with your board and {course.provider} that this specific course qualifies.
How do I enroll in this online school program?
To enroll, click the 'ENROLL NOW' button on this page. You will be taken to the official page for 'Machine Learning with PySpark: Recommender System' on the Coursera Project Network online class platform, where you can complete your registration.
