About this 전문가 수료증
최근 조회 563,489

100% 온라인 강좌

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 일정

유연한 마감을 설정하고 유지 관리합니다.

초급 단계

완료하는 데 약 2개월 필요

매주 12시간 권장

영어

자막: 영어, 아랍어, 독일어, 한국어

귀하가 습득할 기술

Data ScienceMachine LearningPython ProgrammingData AnalysisData Visualization (DataViz)

100% 온라인 강좌

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 일정

유연한 마감을 설정하고 유지 관리합니다.

초급 단계

완료하는 데 약 2개월 필요

매주 12시간 권장

영어

자막: 영어, 아랍어, 독일어, 한국어

How the 전문가 수료증 Works

강좌 수강

A Professional Certificate program is a series of online courses that help you become job-ready. Some Professional Certificates prepare you to launch a career in a specific field like IT support, while others help you to pass an industry certification exam. To begin, enroll in the program or choose a single course you'd like to start with. When you subscribe to a course that is part of a Professional Certificate program, you’re automatically enrolled in the full program. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to manage your course enrollments and track your progress.

Earn the Certificate

When you finish all of your courses, you'll receive a shareable electronic Certificate that you can add to your resume and LinkedIn.

how it works

이 전문가 수료증에는 9개의 강좌가 있습니다.

강좌1

What is Data Science?

4.7
11,504개의 평가
1,809개의 리뷰

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. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

...
강좌2

Open Source tools for Data Science

4.6
6,586개의 평가
804개의 리뷰

What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

...
강좌3

Data Science Methodology

4.6
4,996개의 평가
468개의 리뷰

Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn: - The major steps involved in tackling a data science problem. - The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment. - How data scientists think! LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

...
강좌4

Python for Data Science

4.6
5,220개의 평가
719개의 리뷰

This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours. Module 1 - Python Basics o Your first program o Types o Expressions and Variables o String Operations Module 2 - Python Data Structures o Lists and Tuples o Sets o Dictionaries Module 3 - Python Programming Fundamentals o Conditions and Branching o Loops o Functions o Objects and Classes Module 4 - Working with Data in Python o Reading files with open o Writing files with open o Loading data with Pandas o Numpy Finally, you will create a project to test your skills. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

...

강사

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Joseph Santarcangelo

Ph.D., Data Scientist at IBM
IBM Developer Skills Network
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Alex Aklson

Ph.D., Data Scientist
IBM Developer Skills Network
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Rav Ahuja

Data Science Program Manager
IBM
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SAEED AGHABOZORGI

Ph.D., Sr. Data Scientist
IBM Developer Skills Network
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Polong Lin

Data Scientist
IBM Developer Skills Network

IBM 정보

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

  • 네! 시작하려면 관심 있는 강좌 카드를 클릭하여 등록합니다. 강좌를 등록하고 완료하면 공유할 수 있는 수료증을 얻거나 강좌를 청강하여 강좌 자료를 무료로 볼 수 있습니다. 수료 과정에 있는 강좌를 구독하면, 자동으로 전체 수료 과정을 구독하게 됩니다. 학습자 대시보드에서 진행 사항을 추적할 수 있습니다.

  • 이 강좌는 100% 온라인으로 진행되므로 강의실에 직접 참석할 필요가 없습니다. 웹 또는 모바일 장치를 통해 언제 어디서든 강의, 읽기 자료, 과제에 접근할 수 있습니다.

  • The certificate requires completion of 9 courses. Each course typically contains 3-6 modules with an average effort of 2 to 4 hours per module. If learning part-time (e.g. 1 module per week), it would take 6 to 12 months to complete the entire certificate. If learning full-time (e.g. 1 module per day) the certificate can be completed in 2 to 3 months.

  • This certificate is open for anyone with any job and academic background. No prior computer programming experience is necessary, but is an asset. Familiarity working with computers, high school math, communication and presentation skills. For the last few courses knowledge of Calculus and Linear Algebra is an asset but not an absolute requirement.

  • Yes, it is highly recommended to take the courses in the order they are listed, as they progressively build on concepts taught in previous courses. For example the Data Visualization, Python and Machine Learning courses require knowledge of Python.

  • No, there is no University credits involved with taking these courses.

  • Become job ready for a career in Data Science. Develop practical skills using hands-on labs in Cloud environments, projects and captsones.

  • If you have already completed some of the courses in this Professional Certificate, either individually or as part of another specialization, they will be marked as "Complete". So you do not have to take those courses again and will be able to finish the Professional Certificate faster. You will only need to complete the courses that you have not yet completed.

  • Yes, absolutely. Any courses that you have already completed as part of that Specialization will be marked as "Complete". So you do not have to take those courses again and will be able to finish the Professional Certificate faster.

  • This Professional Certificate consists of 9 courses. The "Introduction to Data Science" Specialization has 4 courses, all of which are also included in this Professional Certificate.

    If you are unsure about your ability to commit to the level of effort and time required to complete this Professional Certificate, we recommend starting with the Introduction to Data Science Specialization, which has fewer courses. And if after earning the specialization certificate you are still determined to continue building your Data Science skills, you can then enroll for this Professional Certificate and then just complete the courses that are not in the specialization.

  • Yes, absolutely. Any courses that you have already completed as part of that Specialization will be marked as "Complete". So you do not have to take those courses again and will be able to finish this Professional Certificate faster.

  • As a Coursera learner who completes the Data Science Professional certificate, you will have special access to join IBM’s Talent Network. Our Talent Network members receive all of the tools you need to land a dream job with IBM - sent directly to your inbox! You will get job opportunities as soon as they are posted, recommendations to apply matched directly to your skills and interests, and tips and tricks to help you stand apart from the crowd.

  • As a Coursera learner who completes this Professional Certificate, you will have special access to join IBM’s Talent Network. Our Talent Network members receive all of the tools you need to land a dream job with IBM - sent directly to your inbox! You will get job opportunities as soon as they are posted, recommendations to apply matched directly to your skills and interests, and tips and tricks to help you stand apart from the crowd.

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