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AI 알고리즘 모델과 한계점
Brent Summers
Brent Summers
알고리즘의 영향력은 점차 커지고 있습니다. 머신 러닝은 방대한 데이터 세트를 기반으로 주요 의사결정을 내리기 시작함에 따라, 인간인 우리는 실제 생활에서의 한계점을 충분히 알고 있어야 합니다. 대출 승인, 교통 경로 재설정을 막론하고, 머신 러닝 모델에는 인간의 공유가치가 정확히 반영되어야 합니다. 본 강좌에서는 가장 기본적인 알고리즘부터 완전 자율 알고리즘에 이르기까지 알고리즘의 발전을 살펴보고, 보다 윤리적으로 건전한 알고리즘을 만드는 방법을 논의합니다.
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What's inside
Syllabus
시작: 알고리즘
수강생 여러분 환영합니다! 강좌 구조에 대한 개요를 소개한 뒤, 본격적으로 알고리즘의 세계를 살펴봅니다.
AI 및 모델 결과
이번 주 강좌에서는 이론과 실제의 핵심 차이점인 예측 모델링을 자세히 알아봅니다.
Read more
Syllabus
시작: 알고리즘
수강생 여러분 환영합니다! 강좌 구조에 대한 개요를 소개한 뒤, 본격적으로 알고리즘의 세계를 살펴봅니다.
AI 및 모델 결과
이번 주 강좌에서는 이론과 실제의 핵심 차이점인 예측 모델링을 자세히 알아봅니다.
Read more
AI 규칙: 학습 및 제약 조건
이번 주 강좌에서는 보다 정확하고 윤리적인 모델을 모색하기 위해 머신 러닝 정확도와 학습 가이드라인을 집중적으로 살펴봅니다.
윤리적인 AI: 원인 및 영향
마지막 주 강좌에서는 이 모든 예측 지능이 어디로 향하는지 이에 대한 몇 가지 중요한 화두를 던져 봅니다. AI가 지나온 길과 사회에 미치는 광범위한 영향에 대해 논의합니다.
Good to know
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Know what's good ,
what to watch for , and
possible dealbreakers
Investigates fairness and bias in algorithmic decision-making, a critical topic in data science and machine learning
Taught by Brent Summers, a recognized expert in the field, providing learners with direct access to industry knowledge
Examines the ethical implications of algorithmic decision-making, addressing a crucial aspect for responsible and transparent AI
Covers the evolution of algorithms from simple to autonomous, providing a comprehensive understanding of their development
Suitable for learners with some understanding of machine learning or data analysis, making it accessible to those already familiar with the field
Requires a solid background in statistics and programming, which may be a barrier to those without prior knowledge
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AI 알고리즘 모델과 한계점.
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Career center
Learners who complete AI 알고리즘 모델과 한계점 will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models for various applications. This course can empower Machine Learning Engineers with a comprehensive understanding of the ethical considerations and potential pitfalls associated with AI algorithms. Additionally, the course's focus on building more ethical and accountable algorithms can equip Machine Learning Engineers with the necessary knowledge and skills to create AI solutions that align with human values and social responsibility.
Ethics Officer
Ethics Officer
Ethics Officers are responsible for ensuring that an organization's activities are conducted in an ethical manner. This course can provide Ethics Officers with a deeper understanding of the ethical implications of AI algorithms and the importance of building and maintaining an ethical culture within organizations. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Ethics Officers with the knowledge and skills to effectively address the ethical challenges associated with AI.
Privacy Officer
Privacy Officer
Privacy Officers are responsible for protecting an organization's data and ensuring compliance with privacy laws and regulations. This course can provide Privacy Officers with a valuable foundation in the ethical implications of AI algorithms and the importance of building and maintaining data privacy in AI systems. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Privacy Officers with the knowledge and skills to effectively address the ethical and privacy-related challenges associated with AI.
Data Analyst
Data Analyst
Data Analysts gather, analyze, and interpret data to provide insights and inform decision-making. This course can provide Data Analysts with a deeper understanding of the ethical implications and potential biases of AI algorithms, which is becoming increasingly important in the field of data analysis. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Data Analysts with the knowledge and skills to navigate the ethical challenges associated with AI and data analysis.
Auditor
Auditor
Auditors evaluate an organization's financial and operational activities to ensure accuracy and compliance. This course can provide Auditors with a deeper understanding of the ethical implications of AI algorithms and the importance of auditing AI systems to ensure they are operating in an ethical and responsible manner. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Auditors with the knowledge and skills to effectively address the ethical and audit-related challenges associated with AI.
Consultant
Consultant
Consultants provide expert advice and guidance to organizations on various business and management issues. This course can provide Consultants with a deeper understanding of the ethical implications of AI algorithms and the importance of advising clients on ethical AI adoption and implementation. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Consultants with the knowledge and skills to effectively address the ethical challenges associated with AI and provide informed guidance to clients.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course can provide Quantitative Analysts with a deeper understanding of the ethical implications and potential biases of AI algorithms in the financial sector. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Quantitative Analysts with the knowledge and skills to navigate the ethical challenges associated with AI and financial modeling.
Data Scientist
Data Scientist
Data Scientists analyze and interpret data to extract meaningful insights and help businesses make informed decisions. This course, which delves into the ethical and practical implications of AI algorithms, can provide Data Scientists with a deeper understanding of the limitations and biases inherent in machine learning models. Furthermore, the course's exploration of the historical development of algorithms and the discussion on building more ethical algorithms can enable Data Scientists to create more responsible and equitable AI solutions.
Risk Manager
Risk Manager
Risk Managers identify, assess, and mitigate risks to an organization. This course can provide Risk Managers with a deeper understanding of the ethical implications of AI algorithms and the importance of managing the risks associated with AI systems. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Risk Managers with the knowledge and skills to effectively address the ethical and risk-related challenges associated with AI.
User Experience Researcher
User Experience Researcher
User Experience Researchers study how users interact with products and services to improve their usability and effectiveness. This course can provide User Experience Researchers with a deeper understanding of the ethical implications of AI algorithms and the importance of designing user experiences that are fair and inclusive. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips User Experience Researchers with the knowledge and skills to contribute to the creation of more ethical and socially responsible user experiences.
Compliance Officer
Compliance Officer
Compliance Officers ensure that an organization complies with applicable laws and regulations. This course can provide Compliance Officers with a valuable foundation in the ethical implications of AI algorithms and the importance of ensuring that AI systems comply with legal and ethical standards. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Compliance Officers with the knowledge and skills to effectively address the legal and ethical challenges associated with AI.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data to provide insights and inform decision-making. This course can provide Statisticians with a valuable foundation in the ethical implications of AI algorithms and the importance of building responsible and accountable statistical models. The course's exploration of the historical development of algorithms and its discussion on building more ethical algorithms can equip Statisticians with the necessary knowledge and skills to contribute to the creation of more ethical and socially responsible statistical solutions.
Policy Analyst
Policy Analyst
Policy Analysts research and analyze policy issues to inform policy-making. This course can provide Policy Analysts with a valuable foundation in the ethical implications of AI algorithms and the importance of developing policies that are fair and equitable. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Policy Analysts with the knowledge and skills to contribute to the creation of more ethical and socially responsible policies.
Product Manager
Product Manager
Product Managers oversee the development and launch of new products and features. This course can provide Product Managers with a valuable foundation in the ethical implications of AI algorithms and the importance of building responsible and accountable products. By exploring the historical development of algorithms and discussing methods for building more ethical algorithms, the course equips Product Managers with the knowledge and skills to contribute to the creation of more ethical and socially responsible products.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can provide Software Engineers with a valuable foundation in the ethical implications of AI algorithms and help them understand the importance of building responsible and accountable software systems. The course's exploration of the historical development of algorithms and its discussion on building more ethical algorithms can equip Software Engineers with the necessary knowledge and skills to contribute to the creation of more ethical and socially responsible software solutions.
For more career information including salaries, visit:
OpenCourser.com/course/0dv36q/ai
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
AI 알고리즘 모델과 한계점.
Save
딥러닝의 이론과 모델의 수학적 기반에 대해 포괄적으로 다룹니다.
이 책은 AI 시스템이 인간 가치와 일치하도록 설계하는 데 따른 과제를 탐구합니다. 본 과정에서 다루는 윤리적 함의에 대해 더 깊은 통찰력을 제공합니다.
파이썬 라이브러리를 사용하여 머신 러닝 모델을 구축하고 평가하는 실습적 가이드입니다.
이 책은 AI 시스템이 불평등을 심화하는 데 어떻게 사용되는지 조사합니다. 본 과정에서 다루는 AI의 윤리적 함의를 이해하는 데 도움이 될 수 있습니다.
이 책은 알고리즘이 사회적 불평등과 민주주의에 미치는 해로운 영향을 조사합니다. 본 과정에서 다루는 AI의 윤리적 함의를 이해하는 데 도움이 될 수 있습니다.
Save
이 책은 머신러닝의 원리와 응용에 대한 포괄적인 소개를 제공합니다. 본 과정에서 다루는 머신러닝 기법을 보완하는 데 도움이 될 수 있습니다.
Save
이 책은 AI와 다른 새롭게 부상하는 기술이 미래에 인류에 미칠 영향을 탐구합니다. 본 과정에서 다루는 AI의 사회적 영향을 이해하는 데 도움이 될 수 있습니다.
머신 러닝의 수학적 기반과 패턴 인식의 개념에 대해 자세히 다룹니다.
머신 러닝을 확률론적 관점에서 다루며, 그래프 모델, 베이지안 추론, 심층 학습과 같은 주제를 다룹니다.
Save
이 책은 알고리즘이 사회에 미치는 영향을 조사합니다. 본 과정에서 다루는 AI의 사회적 영향을 이해하는 데 도움이 될 수 있습니다.
Save
이 책은 AI 시스템의 한계와 잘못된 판단을 조사합니다. 본 과정에서 다루는 AI의 한계를 이해하는 데 도움이 될 수 있습니다.
강화 학습의 기본 원리와 알고리즘을 소개합니다.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/0dv36q/ai
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Level
Introductory
Via
Coursera
Institution
LearnQuest
Instructor
Brent Summers
Language
한국어
Transcripts
English
Español
Français
Português
Deutsch
Italiano
العربية
Pусский
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Good to know
Investigates fairness and bias in algorithmic decision-making, a critical topic in data science and machine learning
Taught by Brent Summers, a recognized expert in the field, providing learners with direct access to industry knowledge
Examines the ethical implications of algorithmic decision-making, addressing a crucial aspect for responsible and transparent AI
Covers the evolution of algorithms from simple to autonomous, providing a comprehensive understanding of their development
Suitable for learners with some understanding of machine learning or data analysis, making it accessible to those already familiar with the field
Requires a solid background in statistics and programming, which may be a barrier to those without prior knowledge
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