You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.
242 learners
Level Basic
Course period Unlimited
Reviews from Early Learners
5.0
SPAGGY
Even Docker beginners can easily follow along.
5.0
심심한 펭귄
I searched for Docker lectures necessary for data analysis and ended up taking the lecture. It was a field I was originally interested in, but I couldn't find any suitable lectures. This is a great lecture for mlops! The lecture covers not only Docker, but also the Linux system and the cloud! I haven't finished listening to it yet, but it's a bit difficult, but I think I can follow it well and apply it to my work.
5.0
Sung Cheol Kim
First of all, thank you for making a great lecture. I am a researcher and practitioner in the ML/AI field, and I was looking for a good lecture related to MLOps and came across this lecture. There are easier lectures on Docker, but this lecture explains it in a more advanced setting, so I was able to gain good insight for fundamental problem solving as well as simple knowledge while listening to the lecture. At the same time, each lecture is broken down into simple contents, so I was able to naturally move on to more difficult contents and learn them. Above all, based on the know-how gained from working in the actual industry, the key points are well organized, so I learned how to keep the focus in situations where it is easy to get confused by too many functions. I am looking forward to the lectures that will come out after this one. Thank you.
Build the same data analysis environment as Kaggle using Docker
Various ways to connect your local to a cloud with powerful computing power
How to Minimize Costs When Using the Cloud
Linux for Understanding Docker
Using the container feature of IDE (VSCode, RStudio, Jupyter Notebook)
Docker for Python
Building and deploying Docker images
Setting up a file sharing system
True virtualization implementation
Who is this course right for?
Data engineers, scientists, and analysts who want to learn Docker in a practical way
Developers and engineers who want to learn Docker through practical experience
Those who need a practical portfolio for the cloud
644
Learners
68
Reviews
74
Answers
4.9
Rating
7
Courses
Working as a Pod Lead at an LLM-based AI company
Seoul National University Graduated from the Department of Mechanical and Aerospace Engineering
Master's degree in Mechanical and Aerospace Engineering from a graduate school in Europe
Conducting doctoral research at an engineering research institute in Germany
Senior Data Scientist experience at a major European energy company
Active as a Senior Consultant at a UK-based energy consulting firm
Performed Databricks-based data engineering projects
Achieved Top 3% in Kaggle Stock Trading AI Competition
Currently serving as the AI Agent Development Team Lead
All
66 lectures ∙ (10hr 27min)
Course Materials:
All
15 reviews
4.7
15 reviews
Reviews 4
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Average Rating 5.0
5
This is a lecture that feels like a real-life situation. It provides practical examples and tips on how to use Docker in a real work environment, so I was able to listen to it all weekend even though there were many lectures. I will listen to it again when another lecture is uploaded.
I am so glad that the lecture was helpful. I tried to make the lecture as similar to the actual situation as possible. I will see you in the next lecture. If you need anything, please contact me by email and I will do my best to help you if I can provide any additional support.
Reviews 1
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Average Rating 5.0
5
I searched for Docker lectures necessary for data analysis and ended up taking the lecture. It was a field I was originally interested in, but I couldn't find any suitable lectures. This is a great lecture for mlops! The lecture covers not only Docker, but also the Linux system and the cloud! I haven't finished listening to it yet, but it's a bit difficult, but I think I can follow it well and apply it to my work.
Bored penguin! Your ID is full of sense. What's so special about mlops? If you can do a little bit of cloud, docker containers, and if possible, git, you are already an mlops expert^^; I hope that the learning content will be connected to your future work and that you will have good results.
Reviews 155
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Average Rating 5.0
Reviews 9
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Average Rating 4.6
5
Even Docker beginners can easily follow along.
Thank you for your review, SPAGGY. I will continue to come back with good lectures 😀 And if you have any questions about the class content at any time, I will answer them as easily and sincerely as possible.
Reviews 1
∙
Average Rating 5.0
5
First of all, thank you for making a great lecture. I am a researcher and practitioner in the ML/AI field, and I was looking for a good lecture related to MLOps and came across this lecture. There are easier lectures on Docker, but this lecture explains it in a more advanced setting, so I was able to gain good insight for fundamental problem solving as well as simple knowledge while listening to the lecture. At the same time, each lecture is broken down into simple contents, so I was able to naturally move on to more difficult contents and learn them. Above all, based on the know-how gained from working in the actual industry, the key points are well organized, so I learned how to keep the focus in situations where it is easy to get confused by too many functions. I am looking forward to the lectures that will come out after this one. Thank you.
You are doing a leading job. I am grateful that the lecture was helpful. It would be great if you could apply the lecture content directly in the field. If you could share a successful case of applying it in the field, it would be a virtuous cycle of knowledge. Thank you.
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