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.
IBM 数据科学 专业证书
Kickstart your Career in Data Science & ML. Master data science, learn Python & SQL, analyze & visualize data, build machine learning models.
无论您是想开始新的职业生涯，还是改变目前职业，Coursera 专业证书都能帮您为开始工作做好准备。选择最适合的时间和地点，自行安排学习进度。立即注册，探索新的职业道路，可免费试用 7 天。您可以随时暂停学习或结束订阅。
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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.