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Intelligent Robot and Advanced Manufacturing
Multi-field cross-scale simulation
Critical Conservation and Revitalization of Architecture Heritage
Curating Contemporary Art: Museums, Galleries, Exhibitions and the Curator
Artificial Intelligence and Big Data
Introduction to Computer Science and Programming
Basics of Machine Learning and Data Analysis
Smart Earth
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Healthy China Initiative and International Health Cooperation
选课操作指南
The Outline of《Artificial Intelligence and Big Data》
Basic Teaching Information
Course Code：2333990011364 |
Course Title：Artificial Intelligence and Big Data |
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Faculty：School of Electronic Information |
Targeted Student：Freshman |
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Course Credit：1 |
Lecture Hours：16 （consisted of __16___ theoretical hours and __0___ practical hours） |
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Course Leader： |
Name：Marcello Pelillo |
E-mail：marcello.pelillo@gmail.com |
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Office： |
Mobile： |
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Course Staff： |
Name：Haijian Zhang |
E-mail：haijian.zhang@whu.edu.cn |
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Office：606 |
Mobile： |
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Course Type：（公共基础课程Public Basic Course/基础通识课程Basic General Course/核心通识课程Core General Course/一般通识课程General Course/大类平台课程Generic Platform Course/专业必修课Compulsory Specialty Course/专业选修课程Optional Specialty Course） |
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Related Preview Courses： |
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Course Introduction
Artificial intelligence (AI) requires a large amount of data as the basis for "thinking" and "decision-making". Big data also requires AI technology for data value operations. One of the main channels for data application is the artificial intelligence product, i.e., the agent. The greater the amount of data provided to the agent, the better the operation effect of the agent will be. The agent needs a lot of data for "training" and "validation", so as to ensure the reliability and stability of operation. This course introduces the basic theories, methods and applications of artificial intelligence and big data.
The Allocation of Content and Lecture Hours
Content |
Lecture Hours |
Introduction |
2 |
Artificial Intelligence |
2 |
Big Data and Intelligent Data Processing |
2 |
Neural Networks |
2 |
Deep Learning |
2 |
Computer Vision |
2 |
Implementations |
2 |
Applications |
2 |
Assessment Methods and Marking Criterion
2 regular homework (40%) + 1 course report (60%)
Textbooks and References
[1] Anand Deshpande, Manish Kumar, 《Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques》, Packt Publishing, 2018.
[2] Fernando Iafrate, 《Artificial Intelligence and Big Data: The Birth of a New Intelligence》, Wiley, 2018.
