- Data Science
- Deep Learning
- Machine Learning
- Big Data
- Data Mining
- Github
- Python Programming
- Jupyter notebooks
- Rstudio
- Methodology
- Data Analysis
- Pandas
IBM 데이터 과학 전문 자격증
Kickstart your career in data science & ML. 데이터 과학 기술을 배우고, Python 및 SQL을 학습하며 데이터 분석 및 시각화를 해보고 기계 학습 모델을 구축하세요. 학위나 이전 경험은 필요하지 않습니다.
배울 내용
Learn what data science is, the various activities of a data scientist’s job, and methodology to think and work like a data scientist
Develop hands-on skills using the tools, languages, and libraries used by professional data scientists
Import and clean data sets, analyze and visualize data, and build and evaluate machine learning models and pipelines using Python
Apply various data science skills, techniques, and tools to complete a project and publish a report
귀하가 습득할 기술
이 전문 자격증 정보
응용 학습 프로젝트
This Professional Certificate has a strong emphasis on applied learning. Except for the first course, all other courses include a series of hands-on labs in the IBM Cloud that will give you practical skills with applicability to real jobs, including:
Tools: Jupyter / JupyterLab, GitHub, R Studio, and Watson Studio
Libraries: Pandas, NumPy, Matplotlib, Seaborn, Folium, ipython-sql, Scikit-learn, ScipPy, etc.
Projects: random album generator, predict housing prices, best classifier model, Predicting successful rocket landing, dashboa rd and interactive map
사전 경험이 필요하지 않습니다.
사전 경험이 필요하지 않습니다.
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 전문 자격증에는 10개의 강좌가 있습니다.
데이터 과학이란 무엇인가요?
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.
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, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. 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 Skills Network 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 Watson Studio and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
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.
Python for Data Science, AI & Development
Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries.
제공자:

IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
학위 취득을 위한 학점 얻기
자주 묻는 질문
환불 규정은 어떻게 되나요?
하나의 강좌에만 등록할 수 있나요?
이 강좌는 100% 온라인으로 진행되나요? 직접 참석해야 하는 수업이 있나요?
How can I earn my IBM Badge?
What is data science?
What are some examples of careers in data science?
How long does it take to complete the Professional Certificate?
What background knowledge do I need for this program?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Professional Certificate?
What will I be able to do upon completing the Professional Certificate?
I already completed some of the other courses in this Professional Certificate. Will I get "credit" for them?
I have already completed the Introduction to Data Science Specialization. Can I still enroll in this Professional Certificate?
Which program should I enroll in - the Introduction to Data Science Specialization, or this Professional Certificate?
I have already completed the Applied Data Science Specialization. Can I still enroll in this Professional Certificate?
How can I access job opportunities with IBM and other organizations after completing this Professional Certificate?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.