课程信息

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第 3 门课程(共 6 门)
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中级
完成时间大约为8 小时
英语(English)
字幕:法语(French), 巴西葡萄牙语, 俄语(Russian), 英语(English), 西班牙语(Spanish)

您将获得的技能

Deep LearningArtificial Neural NetworkArtificial Intelligence (AI)Machine Learningkeras
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
第 3 门课程(共 6 门)
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为8 小时
英语(English)
字幕:法语(French), 巴西葡萄牙语, 俄语(Russian), 英语(English), 西班牙语(Spanish)

提供方

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IBM

教学大纲 - 您将从这门课程中学到什么

1

1

完成时间为 2 小时

Introduction to Neural Networks and Deep Learning

完成时间为 2 小时
4 个视频 (总计 17 分钟), 1 个阅读材料, 2 个测验
4 个视频
Welcome2分钟
Introduction to Deep Learning4分钟
Neurons and Neural Networks3分钟
Artificial Neural Networks5分钟
1 个阅读材料
Syllabus10分钟
1 个练习
Introduction to Neural Networks and Deep Learning30分钟
2

2

完成时间为 1 小时

Artificial Neural Networks

完成时间为 1 小时
4 个视频 (总计 22 分钟)
4 个视频
Backpropagation9分钟
Vanishing Gradient1分钟
Activation Functions5分钟
1 个练习
Artificial Neural Networks30分钟
3

3

完成时间为 3 小时

Keras and Deep Learning Libraries

完成时间为 3 小时
3 个视频 (总计 16 分钟)
3 个视频
Regression Models with Keras6分钟
Classification Models with Keras5分钟
1 个练习
Keras and Deep Learning Libraries30分钟
4

4

完成时间为 2 小时

Deep Learning Models

完成时间为 2 小时
4 个视频 (总计 17 分钟)
4 个视频
Convolutional Neural Networks8分钟
Recurrent Neural Networks2分钟
Autoencoders2分钟
1 个练习
Deep Learning Models30分钟

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关于 IBM AI Engineering 专业证书

Artificial intelligence (AI) is revolutionizing entire industries, changing the way companies across sectors leverage data to make decisions. To stay competitive, organizations need qualified AI engineers who use cutting-edge methods like machine learning algorithms and deep learning neural networks to provide data driven actionable intelligence for their businesses. This 6-course Professional Certificate is designed to equip you with the tools you need to succeed in your career as an AI or ML engineer. You’ll master fundamental concepts of machine learning and deep learning, including supervised and unsupervised learning, using programming languages like Python. You’ll apply popular machine learning and deep learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow to industry problems involving object recognition, computer vision, image and video processing, text analytics, natural language processing (NLP), recommender systems, and other types of classifiers. Through hands-on projects, you’ll gain essential data science skills scaling machine learning algorithms on big data using Apache Spark. You’ll build, train, and deploy different types of deep architectures, including convolutional neural networks, recurrent networks, and autoencoders. In addition to earning a Professional Certificate from Coursera, you will also receive a digital badge from IBM recognizing your proficiency in AI engineering....
IBM AI Engineering

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