Learning OpenAI Codex through Projects - From Basics to Advanced Vibe Coding Using AI
AISchool
Non-Majors Welcome: Real-World Vibe Coding Projects Created Through Conversations with AI
Beginner
Business Productivity, openai, codex
Learn the basics of machine learning step by step through various Kaggle examples, and learn vivid project experiences and practical tips from hard-to-access field machine learning engineers all at once.
323 learners
Level Basic
Course period Unlimited
Reviews from Early Learners
5.0
도전적인 기린
It was a great help in learning the basics of handling various machine learning algorithms.
5.0
조종호
Thank you for the great lecture. It was great to learn about the basics of header files!
5.0
tjsduq8836
It seems to be excellent for understanding the overall flow of machine learning. I've gotten a feel for it, so I'm going to buy the book and study it in earnest. I think it'll make studying easier. Thank you.
Concept of machine learning
How to improve machine learning model performance
How to use Google Colab
Machine learning libraries - scikit-learn, xgboost
Machine Learning/Data Analysis Library - Numpy, Pandas
Data visualization library - matplotlib, seaborn
How to proceed with a machine learning practical project
Learn the basics of machine learning with various Kaggle examples.
Practical tips from working engineers, all in one place! 😀
0. What is Machine Learning (ML)?
1. A simple practice environment that does not require complex installation.
2. Introduction to scikit-learn & My First Machine Learning Model
3. Introduction to Kaggle and Kaggle Competition
4. Linear Regression Algorithm (Ridge, Lasso, ElasticNet) & How Much is My House Worth?
5. Random Forest, a popular and powerful predictor
6. XGBoost, the algorithm favored by Kaggle winners
7. Practical Stories from a Machine Learning Engineer
8. Practical DS/ML Tips from Professionals
Who is this course right for?
For those who are new to machine learning
Anyone who wants to learn data analysis techniques
Anyone who wants to get a job as a machine learning engineer
Anyone curious about the work process after getting a job as a machine learning engineer
Anyone who wants to get practical tips from machine learning engineers working at large IT companies
Need to know before starting?
Basic Python experience
9,778
Learners
761
Reviews
357
Answers
4.6
Rating
32
Courses
All
60 lectures ∙ (7hr 19min)
All
24 reviews
4.6
24 reviews
Reviews 1
∙
Average Rating 5.0
5
I was able to build a good foundation. I'm satisfied.
Hello. Thank you for taking the time to take the class~!. Thank you for the detailed course review~. I will try my best to create a more satisfactory course. Have a nice day!
Reviews 1
∙
Average Rating 5.0
5
It was a great help in learning the basics of handling various machine learning algorithms.
Hello. Thank you for taking the time to take the class~!. Thank you for the detailed course review~. I will try my best to create a more satisfactory course. Have a nice day!
Reviews 2
∙
Average Rating 5.0
5
Thank you for the great lecture. It was great to learn about the basics of header files!
Hello. Thank you for taking the time to take the class~!. Thank you for the detailed course review~. I will try my best to create a more satisfactory course. Have a nice day!
Reviews 2
∙
Average Rating 5.0
5
It seems to be excellent for understanding the overall flow of machine learning. I've gotten a feel for it, so I'm going to buy the book and study it in earnest. I think it'll make studying easier. Thank you.
Hello. Thank you for taking the time to take the class~!. Thank you for the detailed course review~. I will try my best to create a more satisfactory course. Have a nice day!
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