Deep Learning and Computer Vision A-Z + AI & ChatGPT Prizes

📚 **Global Course Rating:** 4.71 ## Course Overview The course has received mixed reviews, with a significant number of students finding it valuable for theoretical understanding, particularly for beginners. The instructor's ability to explain concepts has been consistently praised. However, there are notable concerns regarding the practical exercises and the course's up-to-date nature, as some libraries and code examples are outdated. ### Pros: - **Theoretical Depth:** Many students have commended the comprehensive explanation of theories related to Deep Learning (DL) and Computer Vision (CV), which is beginner-friendly and covers concepts from a very basic form to advanced levels. - **Clear Instruction:** The instructors are noted for providing clear slides and explanations that are well-received by students. - **Engaging Content:** Some students have found the course content rich, well-delivered, and engaging, particularly for those who are new to the field. - **Community Support:** A few instances highlight the helpful nature of the community, with some Q&A interactions being positive. ### Cons: - **Outdated Material:** A significant concern is the outdated nature of the course material, with some students reporting that the libraries and code examples do not work with current software versions. - **Practical Application Issues:** Several students have expressed frustration with the practical part of the course, stating it doesn't help in implementing algorithms from scratch; instead, it shows how to run ready implementations, which can be misleading and redundant. - **Installation Problems:** There are multiple reports of difficulties in installation and execution of scripts, particularly on modern operating systems like macOS. - **Lack of Update Responsiveness:** Some students have indicated that the course has not been updated despite being reported as outdated, which raises concerns about its continued sale. ### Recommendations: - **Manual Dependency Management:** Students who are comfortable with manually updating dependencies and understanding underlying concepts are more likely to benefit from this course. - **PyTorch Knowledge:** Given that some topics like SSD (Single Shot MultiBox Detector) and GANs (Generative Adversarial Networks) are covered using PyTorch, having a basic understanding of PyTorch functions would be advantageous. - **Course Review by Udemy:** Some students suggest that Udemy should review the course to address issues related to outdated content and problematic installations. ### Conclusion: The course is generally well-regarded for its theoretical content but faces significant criticism for its practical application and up-to-date status. Prospective learners should be aware of these issues before enrolling and should consider their comfort level with potentially outdated material and manual dependency management. It is recommended that Udemy review the course to ensure it meets current educational standards and provides a practical learning experience.