Introduction to Recommender Systems
Non-Personalized and Content-Based

I was in a similar situation like you, about a week ago. I googled most of the result, whose summary is as follows:

1. Courses:
2. Coursera: Recommendation Systems with TensorFlow on GCP
   1. Pros: This course gives you more hands-on experience with actual coding.
   2. Cons: Not much into theoretical, hence if you just want to learn the implementation, you are good to go.
3. Coursera: Introduction to Recommender Systems: Non-Personal
   1. Pros: It is a 5 courses specialization which covers almost every aspect of a basic recommender system. The theory part is great and guides you to write your own code.
   2. Cons: It is an outdated course with video lecture being as old as 2014, also the programming language they use is Java which is not compatible with today's python friendly environment.
4. Online Blogs/articles:
5. Medium articles: You will get tons of medium articles on recommender system topics. Here are a few. which I liked:
   1. How hacker news algorithm works
   2. Introduction to recommendation systems and How to design Recommendation system,that resembling the Amazon
   3. Recommender Systems — User-Based and Item-Based Collaborative Filtering
6. Also, you may find some good research paper like this one.
7. Python libraries and online repositories:
8. Lenskit
9. Grouplens
10. Kaggle
11. Github repo 1
12. Github repo 2
13. Github repo 3

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Any more help on this list will be extremely helpful.