关于此 专业证书
122,272 次近期查看

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。

中级

完成时间大约为2 个月

建议 12 小时/周

英语(English)

字幕:英语(English)

您将获得的技能

Data ScienceDeep LearningArtificial Intelligence (AI)Machine LearningApache Spark

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。

中级

完成时间大约为2 个月

建议 12 小时/周

英语(English)

字幕:英语(English)

专业证书是什么?

塑造技能,做好工作准备

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。

实践项目

将您的技能应用到实践项目,并丰富您的简历内容,进而向潜在雇主展示您已为开始工作做好准备。您需要成功完成项目以获得证书。

获得职业证书

当完后计划中的所有课程后,您将获得一张证书。您可以将其在专业网络上分享,并获得使用职业支持资源的权限,这能够为您开启职业生涯提供助力。许多招聘合作伙伴认可我们的许多专业证书,并且我们还有许多合作伙伴可以帮助您准备认证考试。您可以在适用的各个专业证书页面上找到更多信息。

how it works

此专业证书包含 6 门课程

课程1

使用 Python 进行机器学习

4.7
4,395 个评分
554 个审阅
课程2

Scalable Machine Learning on Big Data using Apache Spark

4.0
104 个评分
15 个审阅
课程3

Introduction to Deep Learning & Neural Networks with Keras

4.6
68 个评分
17 个审阅
课程4

Deep Neural Networks with PyTorch

4.7
16 个评分

讲师

Avatar

SAEED AGHABOZORGI

Ph.D., Sr. Data Scientist
IBM Developer Skills Network
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Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT
Avatar

Alex Aklson

Ph.D., Data Scientist
IBM Developer Skills Network
Avatar

Joseph Santarcangelo

Ph.D., Data Scientist at IBM
IBM Developer Skills Network

关于 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....

常见问题

  • 可以!点击您感兴趣的课程卡开始注册即可开始学习。注册并完成课程后,您可以获得可共享的证书,或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某证书的一部分,系统会自动为您订阅完整的证书。访问您的学生面板,跟踪您的进度。

  • 此课程完全在线学习,无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

  • This Professional Certificate consists of 6 self-paced courses. Effort required to complete each course is 4-5 weeks if spending 2-4 hours per week. At this rate the entire specialization can be completed in 3-6 months.

  • It is highly recommended to complete the courses in the suggested order.

  • At this time there is no university credit for completing courses in this specialization.

  • Upon completing this Professional Certificate you will be able to:

    • Describe what is Machine Learning (ML), Deep Learning (DL) & Neural Networks
    • Explain ML algorithms including Classification, Regression, Clustering, and Dimensional Reduction
    • Implement Supervised and Unsupervised ML models using scipy and scikitlearn
    • Express how Apache Spark works and how to perform Machine Learning on Big Data
    • Deploy ML Algorithms and Pipelines on Apache Spark
    • Demonstrate an understanding of Deep Learning models such as autoencoders, restricted Boltzmann machines,  convolutional networks, recursive neural networks, and recurrent networks
    • Build deep learning models and neural networks using the Keras library
    • Utilize the PyTorch library for Deep Learning applications and build Deep Neural Networks
    • Explain foundational TensorFlow concepts like main functions, operations & execution pipelines
    • Apply deep learning using TensorFlow and perform backpropagation to tune the weights and biases
    • Determine what kind of deep learning method to use in which situation and build a deep learning model to solve a real problem
    • Demonstrate ability to present and communicate outcomes of deep learning projects

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