One Week of Data Science in Python - New 2026! (Udemy.com)

His talking English is easy to understand for me. it's very plain, and straight and simple words and sentences to explain his thought, that is better to learn for the beginner even Japanese learner like me.

Designed for busy people, this course delivers on what it says: It's light but thorough enough that by the end of the course, one is already able to apply the knowledge to good measure. The coding examples are easy to follow and are good templates to refer to for use in your own projects. Just be aware that there are some code that needs to be updated. It may not cover of all the Machine Learning models in-depth nor deal with imbalanced data, but for a course like this, it sets one up with a working knowledge that can already be applied.

This was a super match. I will look out for more courses from the creator.

This course has adequate breadth and depth for beginners, taught in an easy-to-learn and fun way. I appreciate the hands-on projects per section/lesson, unlike other courses where it's all lectures first then lumping all the case studies together at the very end. If there will be a follow-up course after this from the instructor (maybe a level higher), I'll be there too :)

It seems that the lecturer knows deeply what he is going to talk about and that is essential... I also think that the course will be well-structured to cover my needs and the presence of additional examples and projects to be solved on my own will definitely contribute to the overall understanding of key data science concepts. Thank you very much!

I managed to hold on to my review until I completed the course. After day 1, I already wanted to give it five stars. This course met my expectations. As a beginner, the content was challenging for me to get into data science. I had to watch at least two to three times to understand the concepts and do the exercises and practical projects, but it was well worth my time. The course covered many topics and taught me much about data science, theories, and practical approaches. Dr. Ryan organized the course content professionally, and I found it extremely easy to go back and forth to review each section. I highly recommend this course to everyone.

The instructor is very good and tries his best to explain all the complex terms in plain English. He has a great attitude and makes the lessons enjoyable. The content delivers on the promise and it has solid teachings and techniques. My only criticism is that the appendix is recycled from other trainings so it’s incomplete and since it explores the introduction to XGBoost it would have been better placed at the beginning of the curse instead that at the end, but since it’s recycled and incomplete it kind of works.

Very good course and an excellent instructor! Dr. Ahmed did an excellent job in providing a good introduction to data science. His lessons are well structured with a brief introduction of the concept, then a dive into code example, with useful exercises, and ends with a final capstone project to strengthen what was learned. My only issue was with the autogluon section (Day 5) which had several version issues that took a lot of time to figure out. In the end, I was only able to get it to work on PyCharm by lowering the Python version. I believe this should have been mentioned somewhere in the course. The theory lectures in the appendices were well explained and constituted a very good introduction. However, section 9 (Appendix A) seems to be an extract from another course, which was presented here in reverse order, with repeated slides in the last lecture. The previous comments do not take away anything from the quality of the course and the effort and excellence of the instructor.

Dr. Ryan is fantastic! He explains the intuition behind a concept (e.g. logistic regression) clearly, then he gives you great code to learn and practice what you've learned as you go. Amazing how much he covers in a short time. Thank you!

I am thankful to Dr. Ryan Ahmed. Wonderful person delivering wonderful content. I was able to grab the content, revise the concepts through practice problems, and was able to transform myself from zero to something in the field of Data Science.