[Renewed] Introduction to Python Backend and Web Technologies for Beginners (Intermediate Python, Understanding Backend and Web Technology Basics with Flask) [Full Stack Part1-1]
Based on real-world experience developing web services in the field, this is a full-stack series course aimed at helping beginners develop web and app services at a level suitable for actual commercialization. As the first step (part1-1) toward this goal, this course provides detailed explanations of intermediate Python, backend implementation techniques using Flask, and essential web technologies (HTTP, REST API, MVC pattern, etc.) for full-scale development.
2,940 learners
Level Basic
Course period Unlimited
[Lecture Open] Python Machine Learning Bootcamp for Beginners
hello.
After much preparation, I am happy to share with you that my first Python Machine Learning Bootcamp course is now 100% open.
There was a delay in the opening of the course, so we have also offered maximum discounts during the opening period.
This lecture is one that I created by improving on the parts that I tried and failed at.
It was 7 years ago when I started learning machine learning/AI technology. At first, I tried learning AI technology, but I got tired of hearing only about AI principles, so I gave up. I also tried learning machine learning, but I only learned mathematical proofs and linear algebra, so I gave up.
Looking back now, I think it would have been much easier to learn artificial intelligence or machine learning technology if I had done it in the following order.
Python -> pandas -> Machine learning key concepts + various practical techniques for practical application of machine learning -> Artificial intelligence
Machine learning contains the most basic concepts that include artificial intelligence. It also contains special related thinking. Also, when applying concepts and actual machine learning to actual problems, there are various special techniques that are used. If you learn and apply the core concepts and techniques that are applied to actual problems, and become familiar with the application of machine learning, your understanding of related technologies will increase. If you learn artificial intelligence technology based on this, you can learn it more easily and learn and utilize it in general.
Machine learning is so vast, and when you get into the mathematical part, it has the characteristics of a collection of several disciplines, so this lecture was created after thinking about how to organize the necessary parts well, focus on them, and learn them along with techniques used in actual problems. Since it was a lecture that had not been done before, it took even more time.
Even for developers, machine learning/artificial intelligence seems like a somewhat ambiguous technology that can be overlooked. This lecture is not aimed at becoming the world's top 1% machine learning expert. There are stages. This lecture aims to be a stepping stone for data science careers by allowing developers to understand and utilize machine learning technology and quickly familiarizing themselves with related technologies for those considering a data science career.
In the future, we will prepare and open artificial intelligence lectures according to the data roadmap as follows.
I really hope that this will be helpful and that you will find the lecture very impressive.
thank you
Data Science Roadmap
1. Python and data collection (crawling) basics (Python and web, data understanding basics)
2. Conquering Scrapy and Selenium (Currently the most advanced crawling intermediate technology and related IT knowledge)
3. SQL and Data Storage/Analysis Basics (Data Storage/Analysis)
4. NoSQL(mongodb) Big Data Basics (Big Data Storage/Analysis)
5. First Python Data Analysis (Data Preprocessing and Pandas, Latest Visualization) [Data Science Part 1]
6. Python Machine Learning Bootcamp for Beginners (Easy! Learn concepts/applications with real problems) [Data Science Part 2]
7. AI Artificial Intelligence Bootcamp (Data Prediction Automation, First Half of 22') [Data Science Part 3]
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