Data ScienceArtificial Intelligence (AI)Information Technology (IT) ArchitectureData ArchitectureLeadershipDeep LearningJobsMachine LearningManagementAnalyticsInnovation
배울 내용
Understand what is AI, its applications and use cases and how it is transforming our lives
Explain terms like Machine Learning, Deep Learning and Neural Networks
Describe several issues and ethical concerns surrounding AI
Articulate advice from experts about learning and starting a career in AI
귀하가 습득할 기술
이 전문 분야 정보
최근 조회 38,707회
This specialization will explain and describe the overall focus areas for business leaders considering AI-based solutions for business challenges. The first course provides a business-oriented summary of technologies and basic concepts in AI. The second will introduce the technologies and concepts in data science. The third introduces the AI Ladder, which is a framework for understanding the work and processes that are necessary for the successful deployment of AI-based solutions.
응용 학습 프로젝트
Each of the courses in this specialization include Checks for Understanding, which are designed to assess each learner’s ability to understand the concepts presented as well as use those concepts in actual practice. Specifically, those concepts are related to introductory knowledge regarding 1) artificial intelligence; 2) data science, and; 3) the AI Ladder.
학습자 경력 결과
41%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
초급 단계
사전 경험이 필요하지 않습니다.
완료하는 데 약 2개월 필요
매주 3시간 권장
영어
자막: 영어, 러시아어
학습자 경력 결과
41%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
초급 단계
사전 경험이 필요하지 않습니다.
완료하는 데 약 2개월 필요
매주 3시간 권장
영어
자막: 영어, 러시아어
이 전문 분야에는 3개의 강좌가 있습니다.
Introduction to Artificial Intelligence (AI)
3,701개의 평가
In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. You will also demonstrate AI in action with a mini project.
데이터 과학이란 무엇인가요?
35,966개의 평가
The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. In this course, we will meet some data science practitioners and we will get an overview of what data science is today.
The AI Ladder: A Framework for Deploying AI in your Enterprise
50개의 평가
This course is intended for business and technical professionals involved in strategic decision-making focused on bringing AI into their enterprises. Through the use of a conceptual model called “The AI Ladder”, participants in this course will learn the requirements, terms and concepts associated with successfully developing and deploying AI solutions in their enterprises. After completing this course you will be able to explain and describe each of the steps required to ensure success when you build and deploy AI solutions in your business enterprise.
제공자:
IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
자주 묻는 질문
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Can I just enroll in a single course?
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
Can I take the course for free?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
Is this course really 100% online? Do I need to attend any classes in person?
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
How long does it take to complete the Specialization?
Total time to complete this Specialization is approximately 20 hours.
Introduction to AI - approximately 8 hours
What is Data Science? - approximately 9 hours
AI Ladder - approximately 3 hours
What background knowledge is necessary?
No prior knowledge of artificial intelligence, machine learning, or data science is needed.
Do I need to take the courses in a specific order?
It is strongly suggested that learners complete the courses in the order presented.
Will I earn university credit for completing the Specialization?
No.
What will I be able to do upon completing the Specialization?
This specialization is designed for business leaders who are considering AI-based solutions for business challenges in their enterprises. Learners who complete this specialization will be able to:
Explain a business-oriented summary of today’s technologies and basic concepts in AI
Describe and explain the basic technologies and concepts in the area of data science
Describe the AI Ladder and its use in understanding the work and processes that are necessary for the successful deployment of AI-based solutions in large enterprises.
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.
© 2020 Coursera Inc. All rights reserved.
