Computer and Information science
Computer Science and Information (CIS) is a field that makes a point in both computing and informatics, which promotes a strong connection between the fields of information science and computer science and computer management as a tool rather than a field.
Information science is one that has a great history, unlike the very small field of computer science. Information science is concerned with the compilation, storage, distribution, distribution and protection of any form of all information. It is a wide field, covering many different areas but is often overlooked in computer science because it is incredibly useful for computers and computer programs in assisting students and researchers in the field especially in helping to analyze data and pattern patterns. While information science is sometimes confused with theory, the two have very different topics. Information theory focuses on a particular concept of knowledge while scientific data focuses on all processes and processes of knowledge.
- Business Information Systems
- Computational Science
- Computer Networks
- Computer Security
- Database and Informatics
- Foundations
- Software Development
Related Conference of Computer and Information science
10th International Conference and Expo on Computer Graphics & Animation
11th International Conference on Data Science and Machine Learning Applications
3rd World Summit on Big Data, Machine Learning and Artificial Intelligence
Computer and Information science Conference Speakers
Recommended Sessions
- AI and ML in Cloud Computing and Mobile Computing
- Artificial Intelligence in Computer Vision
- Artificial Intelligence in LAW
- Automation
- Automation Tools and Its Applications
- Autonomous Technology
- Computer and Information science
- Electrical Engineering
- Human Robot Interaction
- Information and Communications Technology
- Machine Vision System
- Mechatronics
- Microcontroller
- Opt Mechatronics
- Robotics
- Role of AI & Robotics in Industry
- System Engineering
- Types of Artificial Intelligence Learning Models
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