Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning. This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets. It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics. Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
귀하가 습득할 기술
전문 자격증이란 무엇인가요?
기술을 쌓아서 실무에 대비
새로운 분야에서 커리어를 찾고 있거나 현재 커리어에 변화를 주고 싶다면, Coursera의 전문 자격증을 취득하여 준비된 인재로 거듭날 수 있습니다. 가장 편리한 시간과 장소에서 나에게 맞는 속도로 배워보세요. 지금 바로 등록하고 7일 무료 평가판을 통해 새로운 진로를 탐색해보세요. 언제든지 학습을 일시 중지하거나 구독을 종료할 수 있습니다.
실습 프로젝트
실습 프로젝트에서 기술을 적용해보고, 미래 고용주에게 실무적으로 준비된 인재임을 보여주는 포트폴리오를 만들어보세요. 자격증을 취득하려면 프로젝트를 성공적으로 완료해야 합니다.
경력 자격 증명 취득
프로그램의 모든 강좌를 완료하면 전문가 네트워크에서 공유할 수 있는 자격증을 얻게 되며, 새로운 커리어를 시작하는 데 도움이 되는 커리어 지원 리소스에 액세스할 수 있게 됩니다. 많은 전문 자격증은 해당 전문 자격증의 자격 증명을 인정해주는 채용 파트너가 있거나, 자격증 시험을 준비하는 데 도움이 됩니다. 해당하는 경우 개별 전문 자격증 페이지에서 자세한 내용을 알아볼 수 있습니다.
이 전문가 수료증에는 9개의 강좌가 있습니다.
What is Data Science?
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.
Open Source tools for Data Science
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.
Data Science Methodology
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.
Python for Data Science and AI
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.
강사
Joseph Santarcangelo
Ph.D., Data Scientist at IBM
Alex Aklson
Ph.D., Data Scientist
Rav Ahuja
AI and Data Science Program Director
SAEED AGHABOZORGI
Ph.D., Sr. Data Scientist
Polong Lin
Data ScientistIBM 정보
자주 묻는 질문
환불 규정은 어떻게 되나요?
하나의 강좌에만 등록할 수 있나요?
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 진행되나요? 직접 참석해야 하는 수업이 있나요?
이 강좌는 100% 온라인으로 진행되므로 강의실에 직접 참석할 필요가 없습니다. 웹 또는 모바일 장치를 통해 언제 어디서든 강의, 읽기 자료, 과제에 접근할 수 있습니다.
How long does it take to complete the Professional Certificate?
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.
What background knowledge is necessary?
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.
Do I need to take the courses in a specific order?
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.
Will I earn university credit for completing the Professional Certificate?
No, there is no University credits involved with taking these courses.
What will I be able to do upon completing the Professional Certificate?
Become job ready for a career in Data Science. Develop practical skills using hands-on labs in Cloud environments, projects and captsones.
I already completed some of the other courses in this Professional Certificate. Will I get "credit" for them?
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.
I have already completed the "Introduction to Data Science" Specialization. Can I still enroll for this Professional Certificate?
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.
Which should I enroll for - "Introduction to Data Science" Specialization, or this "Data Science Professional Certificate"?
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.
I have already completed the "Applied Data Science" Specialization. Can I still enroll for this Professional Certificate?
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.
What are my job opportunities on completion of this Data Science Professional Certificate
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.
How can I access job opportunities with IBM after completing this Certificate?
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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