I can honestly say that Andrea's knowledge and guidance is top notch! He explains the principles well which helps you understand the concepts and structures within the Dart language.

This course is a great asset to anyone looking to improve their coding skills. Having Andrea by your side, you should feel privileged to have a mentor / coach of his caliber, who shares his knowledge in such an "easy to understand" manner. Thanks!

Clear explanations, a useful practical application that demonstrates all the core things essential to building an app ready for release into the wild.

Every step taken is clearly and thoroughly explained, plus downloadable code for every section of this course. A fantastic current course and is proving invaluable for strategies for building ideas for my own app.

Cannot praise this course and Andrea’s presentation highly enough.

Andrea is a great instructor! He packs a ton of great information into each lesson in a concise way.

For the latest release notes, Windows-specific bug fixes, and community support, refer to the official Vector Q documentation and GitHub issues labeled os:windows .

Vector Q (often stylized as VectorQ ) is a high-performance vector similarity search engine and vector database management system. While originally developed for Linux-based server environments, its Windows port has gained significant traction among data scientists, AI application developers, and Windows-based researchers who need to work with embeddings without switching operating systems. What Does Vector Q Do? At its core, Vector Q is designed to store, index, and query high-dimensional vectors. These vectors are numerical representations of unstructured data—such as text, images, audio, or user behavior—generated by machine learning models (e.g., BERT, CLIP, or ResNet). The primary operation is similarity search : given a query vector, Vector Q returns the most similar stored vectors based on distance metrics like cosine similarity or Euclidean distance.

vectorq-cli --version vectorq-cli status Once Vector Q is running on localhost:8080 , you can interact with it using the Python SDK:

The new Flutter in Production course is fantastic! It covers so many practical aspects of launching an app that I would have had to learn by trial and error.

I haven’t seen these topics covered in other courses, and the explanation is thorough. Andrea’s teaching style is clear and concise; I feel like I can learn the concepts quickly without getting bogged down in a lot of fluff.

Highly recommended if you want to become a pro Flutter developer!

This is by far the best Flutter course if you want to learn coding best practises while learning flutter, which I think everyone should.

I've taken two other top rated flutter courses in Udemy and speaking by experience.

Another impressive thing about this course is that most of the videos are around 5 minutes even to cover complex topics. I am pretty sure Andrea has put lot of work to make them as such.

Andrea’s Flutter content is amazing - it’s one of the few resources I consistently reference for advanced real-world solutions.

He clearly puts a huge amount of care and thought into every tutorial. Highly recommended!

I would like to thank you very much Andrea for all your effort in helping me and others to learn about Dart, Flutter, and Firebase.

It literally changed my life because I started a new job as Flutter Developer and you gave me all the fundamentals to make this journey possible.