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Google Cloud Training
이 과정에서는 예측 및 생성형 AI 프로젝트를 모두 빌드하는 Google Cloud 기반 AI 및 머신러닝(ML) 제품군을 소개합니다. AI 기반, 개발, 솔루션을 모두 포함하여 데이터에서 AI로 이어지는 수명 주기 전반에 걸쳐 사용할 수 있는 기술과 제품, 도구를 살펴봅니다. 이 과정의 목표는 흥미로운 학습 경험과 실제적인 실무형 실습을 통해 데이터 과학자, AI 개발자, ML 엔지니어의 기술 및 지식 역량 강화를 지원하는 것입니다.
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What's inside
Syllabus
소개
이 모듈에서 다루는 과정은 학습자가 Google Cloud의 AI 개발 도구를 살펴보도록 돕는 데 그 목적이 있습니다. 여기에서 제공되는 과정의 대략적인 구성은 AI 기반, 개발, 솔루션, 이 3가지 계층으로 이루어진 AI 프레임워크를 토대로 합니다.
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Syllabus
소개
이 모듈에서 다루는 과정은 학습자가 Google Cloud의 AI 개발 도구를 살펴보도록 돕는 데 그 목적이 있습니다. 여기에서 제공되는 과정의 대략적인 구성은 AI 기반, 개발, 솔루션, 이 3가지 계층으로 이루어진 AI 프레임워크를 토대로 합니다.
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Devised by Google Cloud Training, a leader in professional skill development for AI and machine learning
Structured with a clear hierarchy of AI fundamentals, development, and solutions, ensuring a systematic learning experience
Covers both predictive and generative AI, providing a comprehensive understanding of the full spectrum of AI applications
Offers hands-on practice with real-world datasets and tools, allowing learners to apply their knowledge immediately
Incorporates Google Cloud's latest AI products and services, ensuring that learners are up-to-date with industry advancements
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Reviews summary
Google cloud 기반 ai/ml 핵심 입문
학습자들은 Google Cloud 기반 AI 및 머신러닝의 포괄적인 입문 과정으로 이 강의를 높이 평가합니다. 특히 최신 생성형 AI 내용과 Vertex AI 및 BigQuery ML을 활용한 실습이 매우 유용하다고 언급합니다. 실무 적용 가능성이 높으며, 한국어로 제공되어 학습에 용이하다는 점도 큰 장점으로 꼽힙니다. 반면, 일부 학습자들은 각 주제의 깊이가 다소 아쉽다고 느끼거나, 내용이 방대하고 빠르게 진행되어 초급자에게는 부담이 될 수 있다고 지적합니다. 심화 학습을 위해서는 추가 자료가 필요할 수 있습니다.
초보자에게는 좋으나, 심화 학습을 원하는 경우 깊이가 아쉽습니다.
"초보자에게는 매우 적합하지만, 이미 어느 정도 지식이 있는 저에게는 다소 피상적일 수 있다고 느꼈습니다."
"강의가 너무 많고 빠르게 진행되는 경향이 있어서, 특히 복잡한 주제는 초급자에게 조금 버거울 수 있겠다고 생각했어요."
"특정 기술에 대한 심화 학습을 원한다면 이 강의만으로는 부족하고 추가 학습이 필요할 것 같아요."
"일부 고급 개념은 빠르게 넘어가서, 심화 학습을 위해서는 별도 자료를 찾아봐야 했습니다."
Vertex AI, BigQuery ML, 생성형 AI 등 실용적인 기술을 다룹니다.
"Vertex AI와 BigQuery ML에 대한 실습이 정말 유용했고, 개념 설명도 명확했습니다. 바로 업무에 적용할 수 있을 것 같아요."
"생성형 AI 부분 덕분에 이 강의를 선택했어요. 실무에 바로 적용할 수 있는 팁을 얻어서 만족합니다."
"이 과정은 실습 위주의 구성이 매우 마음에 들었습니다. 이론만 나열하지 않고 직접 해볼 수 있어서 이해가 빨랐어요."
"최신 생성형 AI 내용이 포함되어 있어 좋았습니다. 트렌드까지 다뤄줘서 매우 유익했어요."
Google Cloud AI/ML의 핵심 개념을 효과적으로 소개합니다.
"이 강의는 Google Cloud에서 AI/ML을 배우는 데 있어 최고의 시작점이었습니다."
"AI와 ML에 대한 전반적인 이해를 돕는 데는 충분히 좋은 과정입니다."
"Google Cloud 플랫폼에서 AI/ML 서비스를 어떻게 활용하는지 이해하는 데 큰 도움이 되었습니다."
"저는 AI/ML 입문자로서 이 강의를 통해 전반적인 흐름을 파악할 수 있었습니다. 저에게는 최적화된 강의였습니다."
일부 학습자는 자료와 문제 해결 지원이 불충분하다고 느꼈습니다.
"강의 자료가 충분하지 않다고 느꼈습니다. 실습에서 막히는 경우가 많았는데, troubleshooting 가이드가 부족해서 아쉬웠어요."
"초급자를 위한 과정이라면 좀 더 친절한 설명과 학습 지원이 필요하다고 생각합니다."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to AI and Machine Learning on GC - 한국어 with these
activities:
Review Python Basics
Show steps
Revisit the basics of Python to solidify fundamental concepts and prepare for advanced topics covered in this course.
Browse courses on
Python
Show steps
-
Re-read Python documentation or tutorials on data types, operators, and control flow.
-
Solve coding challenges or practice exercises on platforms like LeetCode or HackerRank.
Read 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow'
Show steps
Gain a comprehensive understanding of machine learning concepts and techniques through a hands-on approach using popular libraries like Scikit-Learn, Keras, and TensorFlow.
Show steps
-
Read chapters 1-3, focusing on supervised learning algorithms.
-
Implement the algorithms discussed in the book using Python code.
Follow Tutorials on Natural Language Processing (NLP)
Show steps
Enhance your understanding of NLP techniques by following guided tutorials, which will provide step-by-step instructions and hands-on practice.
Browse courses on
Natural Language Processing
Show steps
-
Find tutorials on topics like text preprocessing, tokenization, and sentiment analysis.
-
Follow the tutorials, implementing the code and experimenting with different parameters.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join Study Groups or Online Forums
Show steps
Engage with peers, discuss concepts, and learn from others' experiences by participating in study groups or online forums dedicated to AI and machine learning.
Show steps
-
Find study groups or forums related to the course topics.
-
Participate in discussions, ask questions, and share your knowledge.
Solve Competitive Programming Problems
Show steps
Develop your problem-solving skills and deepen your understanding of algorithms and data structures by solving competitive programming problems.
Browse courses on
Competitive Programming
Show steps
-
Join online platforms like LeetCode or HackerRank.
-
Solve problems of varying difficulty levels.
Build a Machine Learning Model for Image Classification
Show steps
Apply your knowledge by building a machine learning model that can classify images, reinforcing your understanding of model development and evaluation.
Browse courses on
Machine Learning
Show steps
-
Gather and prepare a dataset of images.
-
Train a convolutional neural network (CNN) model using TensorFlow or Keras.
-
Evaluate the model's performance using metrics like accuracy and F1 score.
Create a Blog Post or Article on AI Trends
Show steps
Stay up-to-date with the latest advancements in AI by researching and writing about emerging trends, reinforcing your understanding of the field's evolution.
Browse courses on
AI Trends
Show steps
-
Research and gather information on recent AI developments.
-
Write a well-structured blog post or article summarizing your findings.
Review Python Basics
Show steps
Revisit the basics of Python to solidify fundamental concepts and prepare for advanced topics covered in this course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Re-read Python documentation or tutorials on data types, operators, and control flow.
- Solve coding challenges or practice exercises on platforms like LeetCode or HackerRank.
Read 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow'
Show steps
Gain a comprehensive understanding of machine learning concepts and techniques through a hands-on approach using popular libraries like Scikit-Learn, Keras, and TensorFlow.
Show steps
Show steps
Show steps
- Read chapters 1-3, focusing on supervised learning algorithms.
- Implement the algorithms discussed in the book using Python code.
Follow Tutorials on Natural Language Processing (NLP)
Show steps
Enhance your understanding of NLP techniques by following guided tutorials, which will provide step-by-step instructions and hands-on practice.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Find tutorials on topics like text preprocessing, tokenization, and sentiment analysis.
- Follow the tutorials, implementing the code and experimenting with different parameters.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join Study Groups or Online Forums
Show steps
Engage with peers, discuss concepts, and learn from others' experiences by participating in study groups or online forums dedicated to AI and machine learning.
Show steps
Show steps
Show steps
- Find study groups or forums related to the course topics.
- Participate in discussions, ask questions, and share your knowledge.
Solve Competitive Programming Problems
Show steps
Develop your problem-solving skills and deepen your understanding of algorithms and data structures by solving competitive programming problems.
Browse courses on
Competitive Programming
Show steps
Show steps
Show steps
- Join online platforms like LeetCode or HackerRank.
- Solve problems of varying difficulty levels.
Build a Machine Learning Model for Image Classification
Show steps
Apply your knowledge by building a machine learning model that can classify images, reinforcing your understanding of model development and evaluation.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Gather and prepare a dataset of images.
- Train a convolutional neural network (CNN) model using TensorFlow or Keras.
- Evaluate the model's performance using metrics like accuracy and F1 score.
Create a Blog Post or Article on AI Trends
Show steps
Stay up-to-date with the latest advancements in AI by researching and writing about emerging trends, reinforcing your understanding of the field's evolution.
Browse courses on
AI Trends
Show steps
Show steps
Show steps
- Research and gather information on recent AI developments.
- Write a well-structured blog post or article summarizing your findings.
Career center
Learners who complete Introduction to AI and Machine Learning on GC - 한국어 will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/hw6trw/introduction
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Effort
10 hours to complete
Level
Introductory
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Google Cloud
Instructor
Google Cloud Training
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