关于此 专业证书
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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。

初级

完成时间大约为3 个月

建议 12 小时/周

英语(English)

字幕:英语(English), 韩语, 德语(German)

您将获得的技能

Deep LearningArtificial Intelligence (AI)Machine LearningwatsonTensorflow

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。

初级

完成时间大约为3 个月

建议 12 小时/周

英语(English)

字幕:英语(English), 韩语, 德语(German)

专业证书 的运作方式

加入课程

专业证书课程是一系列能够帮助您做好工作准备的在线课程。一些专业证书助力您开启在 IT 支持等特定领域的职业生涯,而另一些证书则可以帮助您通过行业认证考试。若要开始学习,请注册该课程或选择首先开始学习的单一课程。当您订阅专业证书课程的部分课程时,您将自动注册整个专业证书课程。您可以只完成一门课程,可以随时暂停学习或结束订阅。访问您的学生控制面板,管理您的课程注册情况并跟踪进度。

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当完成所有课程后,您会收到一个可共享的电子证书,您可以将其添加到您简历和领英档案中。

how it works

此专业证书包含 12 门课程

课程1

Introduction to Artificial Intelligence (AI)

4.7
135 个评分
35 个审阅

In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. You will also demonstrate AI in action with a mini project. This course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.

...
课程2

Getting Started with AI using IBM Watson

4.5
8 个评分
1 个审阅

In this course you will learn how to quickly and easily get started with Artificial Intelligence using IBM Watson. You will understand how Watson works, become familiar with its use cases and real life client examples, and be introduced to several of Watson AI services from IBM that enable anyone to easily apply AI and build smart apps. You will also work with several Watson services to demonstrate AI in action. This course does not require any programming or computer science expertise and is designed for anyone whether you have a technical background or not.

...
课程3

Building AI Powered Chatbots Without Programming

4.7
191 个评分
49 个审阅

This course will teach you how to create useful chatbots without the need to write any code. Leveraging IBM Watson's Natural Language Processing capabilities, you'll learn how to plan, implement, test, and deploy chatbots that delight your users, rather than frustrate them. True to our promise of not requiring any code, you'll learn how to visually create chatbots with Watson Assistant (formerly Watson Conversation) and how to deploy them on your own website through a handy WordPress plugin. Don't have a website? No worries, one will be provided to you. Chatbots are a hot topic in our industry and are about to go big. New jobs requiring this specific skill are being added every day, consultants demand premium rates, and the interest in chatbots is quickly exploding. Gartner predicts that by 2020, 85% of customer interactions with the enterprise will be through automated means (that's chatbots and related technologies). Here is your chance to learn this highly in demand set of skills with a gentle introduction to the topic that leaves no stone unturned.

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课程4

Python for Data Science and AI

4.6
6,088 个评分
828 个审阅

This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours. Module 1 - Python Basics o Your first program o Types o Expressions and Variables o String Operations Module 2 - Python Data Structures o Lists and Tuples o Sets o Dictionaries Module 3 - Python Programming Fundamentals o Conditions and Branching o Loops o Functions o Objects and Classes Module 4 - Working with Data in Python o Reading files with open o Writing files with open o Loading data with Pandas o Numpy Finally, you will create a project to test your skills. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

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讲师

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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

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 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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