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Data science is one of the hottest professions of the decade, and the demand for data scientists who can analyze data and communicate results to inform data driven decisions has never been greater. This Professional Certificate from IBM will help anyone interested in pursuing a career in data science or machine learning develop career-relevant skills and experience. It’s a myth that to become a data scientist you need a Ph.D. Anyone with a passion for learning can take this Professional Certificate – no prior knowledge of computer science or programming languages required – and develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry level data scientist. The program consists of 9 online courses that will provide you with the latest job-ready tools and skills, including open source tools and libraries, Python, databases, SQL, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning algorithms. You’ll learn data science through hands-on practice in the IBM Cloud using real data science tools and real-world data sets. Upon successfully completing these courses, you will have 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'll also receive a digital badge from IBM recognizing your proficiency in data science.
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灵活的计划
设置并保持灵活的截止日期。
初级
完成时间大约为10 个月
建议 4 小时/周
英语(English)
字幕:英语(English), 俄语(Russian), 韩语, 波斯语, 越南语, 德语(German), 阿拉伯语(Arabic), 土耳其语(Turkish)...
学生职业成果
46%
完成此 专项课程 后开始了新的职业。
19%
加薪或升职。
可分享的证书
完成后获得证书
100% 在线课程
立即开始,按照自己的计划学习。
灵活的计划
设置并保持灵活的截止日期。
初级
完成时间大约为10 个月
建议 4 小时/周
英语(English)
字幕:英语(English), 俄语(Russian), 韩语, 波斯语, 越南语, 德语(German), 阿拉伯语(Arabic), 土耳其语(Turkish)...

此专业证书包含 9 门课程

课程1

课程 1

什么是数据科学?

4.7
37,981 个评分
7,039 条评论
课程2

课程 2

Tools for Data Science

4.5
18,735 个评分
2,758 条评论
课程3

课程 3

Data Science Methodology

4.6
14,397 个评分
1,652 条评论
课程4

课程 4

Python for Data Science and AI

4.6
17,966 个评分
2,770 条评论

提供方

IBM 徽标

IBM

常见问题

  • 此专项课程不提供大学学分,但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校,了解详情。Coursera 上的在线学位Mastertrack™ 证书提供获得大学学分的机会。

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  • D​ata science is the process of collecting, storing, and analyzing data. Data scientists use data to tell compelling stories to inform business decisions. Learn more about what data science is and what data scientists do in the first course of this Professional Certificate, "What is Data Science?"

  • An understanding of data science and the ability to make data driven decisions is useful in any career, but some careers specifically require a data science background. Some examples of careers in data science include: 

    -​ Business Intelligence Analyst

    -​ Data Analyst

    -​ Data Architect

    -​ Data Engineer

    -​ Data Scientist

    -​ Machine Learning Engineer

    -​ Marketing Analyst

    -​ Operations Analyst

    -​ Quantitative Analyst

  • The Professional 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 Professional Certificate is open for anyone with any job and academic background. No prior computer programming experience is necessary, but is an asset, as are familiarity working with computers, high school math, and 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 Analysis, Data Visualization, and Machine Learning courses require knowledge of Python covered earlier in the program.

  • No, there is no university credit 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". You do not have to take those courses again, and will be able to finish the Professional Certificate more quickly. 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". You do not have to take those courses again and will be able to finish the Professional Certificate more quickly.

  • 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. If, after completing the Specialization, 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". You do not have to take those courses again and will be able to finish this Professional Certificate more quickly.

  • 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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