Data SciencePython ProgrammingJupyter notebooksRstudioSQLCloud DatabasesIpythonRelational Database Management System (RDBMS)
数据科学导论 專項課程
在数据科学领域工作. Data Science skills to prepare for a career or further advanced learning in Data Science.
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数据科学导论 專項課程IBM您將學到的內容有
Create and access a database instance on cloud
Write basic SQL statements: CREATE, DROP, SELECT, INSERT, UPDATE, DELETE
Filter, sort, group results, use built-in functions, access multiple tables
Access databases from Jupyter using Python and work with real world datasets
您將獲得的技能
關於此 專項課程
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In this Specialization learners will develop foundational Data Science skills to prepare them for a career or further learning that involves more advanced topics in Data Science. The specialization entails understanding what is Data Science and the various kinds of activities that a Data Scientist performs. It will familiarize learners with various open source tools, like Jupyter notebooks, used by Data Scientists. It will teach you about methodology involved in tackling data science problems. The specialization also provides knowledge of relational database concepts and the use of SQL to query databases. Learners will complete hands-on labs and projects to apply their newly acquired skills and knowledge.
Upon receiving the certificate for completion of the specialization, you will also receive an IBM Badge as a Specialist in Data Science Foundations.
應用的學習項目
Learners will complete hands-on labs and projects to apply their newly acquired skills and knowledge. You will utilize tools like Jupyter, Zeppelin, R Studio and Watson Studio. You will also work with real-world data sets and query them using SQL from Jupyter notebooks.
學生職業成果
46%
完成此 專項課程 後開始了新的職業。
19%
加薪或升職。
可分享的證書
完成後獲得證書
100% 在線課程
立即開始，按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
初級
無需相關領域的預備知識無需相關經驗。
完成時間大約為4 個月
建議 3 小時/週
英語（English）
字幕：英語（English）, 俄語（Russian）, 波斯語, 韓語, 阿拉伯語（Arabic）
學生職業成果
46%
完成此 專項課程 後開始了新的職業。
19%
加薪或升職。
可分享的證書
完成後獲得證書
100% 在線課程
立即開始，按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
初級
無需相關領域的預備知識無需相關經驗。
完成時間大約為4 個月
建議 3 小時/週
英語（English）
字幕：英語（English）, 俄語（Russian）, 波斯語, 韓語, 阿拉伯語（Arabic）
此專項課程包含 4 門課程
什么是数据科学？
36,150 個評分
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
18,124 個評分
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.
Data Science Methodology
13,947 個評分
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.
Databases and SQL for Data Science
11,196 個評分
Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist.
提供方
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.
常見問題
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?
The specialization consists of 4 courses. Suggested time to complete each course is 3-4 weeks. If you follow recommended timelines it would take 3 to 4 months to complete the entire specialization.
What background knowledge is necessary?
This specialization is intended for learners wanting to build foundational skills in Data Science. No prior background in data science or programming is required.
Do I need to take the courses in a specific order?
In order to get the most out of this specialization, it is recommended to take the courses in the order they are listed.
Will I earn university credit for completing the Specialization?
No University credit will be earned.
What will I be able to do upon completing the Specialization?
In this Specialization learners will develop foundational Data Science skills to prepare them for a career or further learning that involves more advanced topics in Data Science.
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