이 전문 분야 정보

최근 조회 16,134

The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance.

The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include:

(1) mapping the problem on a general landscape of available ML methods,

(2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and

(3) successfully implementing a solution, and assessing its performance.

The specialization is designed for three categories of students:

· Practitioners working at financial institutions such as banks, asset management firms or hedge funds

· Individuals interested in applications of ML for personal day trading

· Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance.

The modules can also be taken individually to improve relevant skills in a particular area of applications of ML to finance.

학습자 경력 결과
50%
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.
중급 단계
완료하는 데 약 4개월 필요
매주 5시간 권장
영어
자막: 영어, 프랑스어
학습자 경력 결과
50%
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.
중급 단계
완료하는 데 약 4개월 필요
매주 5시간 권장
영어
자막: 영어, 프랑스어

이 전문 분야에는 4개의 강좌가 있습니다.

강좌1

강좌 1

Guided Tour of Machine Learning in Finance

3.8
별점
520개의 평가
161개의 리뷰
강좌2

강좌 2

Fundamentals of Machine Learning in Finance

3.8
별점
260개의 평가
53개의 리뷰
강좌3

강좌 3

Reinforcement Learning in Finance

3.5
별점
94개의 평가
24개의 리뷰
강좌4

강좌 4

Overview of Advanced Methods of Reinforcement Learning in Finance

3.8
별점
63개의 평가
11개의 리뷰

제공자:

New York University 로고

New York University

자주 묻는 질문

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • Prerequisites for the specialization are basic math including calculus and linear algebra, basic probability theory and statistics, and some programming skills in Python. For students that are not familiar with Python and IPython / Jupyter notebooks, reference to tutorials are provided as a part of further reading.

궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.