Introduction to AI and Machine Learning on GC - 한국어

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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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

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Revisit the basics of Python to solidify fundamental concepts and prepare for advanced topics covered in this course.

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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'

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Gain a comprehensive understanding of machine learning concepts and techniques through a hands-on approach using popular libraries like Scikit-Learn, Keras, and TensorFlow.

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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)

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Enhance your understanding of NLP techniques by following guided tutorials, which will provide step-by-step instructions and hands-on practice.

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Find tutorials on topics like text preprocessing, tokenization, and sentiment analysis.
Follow the tutorials, implementing the code and experimenting with different parameters.

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Join Study Groups or Online Forums

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Engage with peers, discuss concepts, and learn from others' experiences by participating in study groups or online forums dedicated to AI and machine learning.

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Find study groups or forums related to the course topics.
Participate in discussions, ask questions, and share your knowledge.

Solve Competitive Programming Problems

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Develop your problem-solving skills and deepen your understanding of algorithms and data structures by solving competitive programming problems.

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Join online platforms like LeetCode or HackerRank.
Solve problems of varying difficulty levels.

Build a Machine Learning Model for Image Classification

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Apply your knowledge by building a machine learning model that can classify images, reinforcing your understanding of model development and evaluation.

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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

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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.

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