關於此 專業證書
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100% 在線課程

立即開始,按照自己的計劃學習。

靈活的計劃

設置並保持靈活的截止日期。

初級

完成時間大約為3 個月

建議 12 小時/週

英語(English)

字幕:英語(English), 韓語, 德語(German)

您將獲得的技能

Deep LearningArtificial Intelligence (AI)Machine LearningwatsonTensorflow

100% 在線課程

立即開始,按照自己的計劃學習。

靈活的計劃

設置並保持靈活的截止日期。

初級

完成時間大約為3 個月

建議 12 小時/週

英語(English)

字幕:英語(English), 韓語, 德語(German)

專業證書是什麼?

塑造技能,做好工作準備

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實踐項目

將您的技能應用到實踐項目,並豐富您的簡歷內容,進而向潛在雇主展示您已為開始工作做好準備。您需要成功完成項目以獲得證書。

Earn a Career Credential

當完後計劃中的所有課程後,您將獲得一張證書。您可以將其在專業網絡上分享,並獲得使用職業支持資源的權限,這能夠為您開啟職業生涯提供助力。許多招聘合作夥伴認可我們的許多專業證書,並且我們還有許多合作夥伴可以幫助您準備認證考試。您可以在適用的各個專業證書頁面上找到更多信息。

how it works

此專業證書包含 12 門課程

課程1

Introduction to Artificial Intelligence (AI)

4.7
364 個評分
82 個審閱
課程2

Getting Started with AI using IBM Watson

4.4
115 個評分
19 個審閱
課程3

Building AI Powered Chatbots Without Programming

4.8
283 個評分
74 個審閱
課程4

Python for Data Science and AI

4.6
6,884 個評分
920 個審閱

講師

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Joseph Santarcangelo

Ph.D., Data Scientist at IBM
IBM Developer Skills Network
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Yi Leng Yao

MSc., Data Scientist, Software Engineer
IBM Skills Network
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Alex Aklson

Ph.D., Data Scientist
IBM Developer Skills Network
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Sacchit Chadha

Software Engineer @ IBM | Rising Computer Science Senior @ UWaterloo
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Rav Ahuja

AI and Data Science Program Director
IBM
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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
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Tanmay Bakshi

AI Evangelist & Watson Developer
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Antonio Cangiano

Software Developer and Technical Evangelist
IBM Developer Skills Network

關於 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....

常見問題

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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 consists of 12 courses. Each course entails 6-12 hours of effort. If learning part-time (approx 4-6 hours per week), and completing each course within the recommended 4-6 weeks timeframe, this program can be completed within one year. However, if learninig full-time (approx 4 to 6 hours per day), the entire program can even be completed within 3 to 4 months.

  • No prior background in AI, computer science or programming is necessary. As a part of the program you will learn the Python programming language. High School level Mathematics is required for the second half of the certificate (i.e. for the Machine Learning and Deep Learning courses). Although not a strict requirement, knowledge of Calculus and entry level Linear Algebra is an asset for Deep Learning.

  • Many courses build upon skills learned in previous courses. Therefore it is highly recommended to take the courses in the suggested order.

  • At this stage university credit is not available for the courses in this Professional Certificate.

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

    • Describe what is AI, its applications & use cases, and how its transforming our lives
    • Explain terms like Machine Learning (ML), Deep Learning (DL) and Neural Networks
    • Identify various Watson AI services from IBM and what they can be used for
    • Describe how AI-powered chatbot technology works and its applications
    • Create a customer support chatbot and add it to a website
    • Practice basics of Python programming language using Jupyter notebooks on IBM Cloud
    • Apply Python programming concepts for data science and AI
    • Utilize multiple Watson AI services and APIs together to build smart applications
    • Deploy speech enabled virtual assistants with domain intelligence to Facebook, etc.
    • Explain what computer vision is and its applications
    • Build and train custom image classifiers using Watson, Python and OpenCV
    • Create an interactive computer vision web application and deploy it on IBM Cloud
    • 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
  • No specialized hardware and software is required to complete these courses. Learners only require a modern web browser (recent versions of Chrome or Firefox) to complete the courses. All hands-on labs and projects will be performed from web browsers using IBM Cloud based environments and Watson AI services, available at no charge to the learners.

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