关于此 专业证书

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The rapid pace of innovation in Artificial Intelligence (AI) is creating enormous opportunity for transforming entire industries and our very existence. After competing this comprehensive 6 course Professional Certificate, you will get a practical understanding of Machine Learning and Deep Learning. You will master fundamental concepts of Machine Learning and Deep Learning, including supervised and unsupervised learning. You will utilize popular Machine Learning and Deep Learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow applied to industry problems involving object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers. You will be able to scale Machine Learning on Big Data using Apache Spark. You will build, train, and deploy different types of Deep Architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders. By the end of this Professional Certificate, you will have completed several projects showcasing your proficiency in Machine Learning and Deep Learning, and become armed with skills for a career as an AI Engineer.
学生职业成果
38%
完成此 专项课程 后开始了新的职业。
18%
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。
中级
完成时间大约为8 个月
建议 3 小时/周
英语(English)
字幕:英语(English)
学生职业成果
38%
完成此 专项课程 后开始了新的职业。
18%
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。
中级
完成时间大约为8 个月
建议 3 小时/周
英语(English)
字幕:英语(English)

此专业证书包含 6 门课程

课程1

课程 1

使用 Python 进行机器学习

4.7
9,002 个评分
1,435 条评论
课程2

课程 2

Scalable Machine Learning on Big Data using Apache Spark

3.9
850 个评分
212 条评论
课程3

课程 3

Introduction to Deep Learning & Neural Networks with Keras

4.7
632 个评分
120 条评论
课程4

课程 4

Deep Neural Networks with PyTorch

4.4
580 个评分
126 条评论

提供方

IBM 徽标

IBM

常见问题

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  • 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 pre-requisties the following skills:

    • High School Mathematics or Math for Machine Learning

    It is highly recommended that you complete either or both of the following Professional Certificates before starting this one:

  • 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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