Computer Aided Graphics notes
| Institution | Jomo Kenyatta University of Science and Technology |
| Course | Information Technol... |
| Year | 3rd Year |
| Semester | Unknown |
| Posted By | Jeff Odhiambo |
| File Type | pptx |
| Pages | |
| File Size | 64.94 KB |
| Views | 1347 |
| Downloads | 0 |
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Description
Computer-Aided Graphics (CAG) focuses on the use of computer software and tools to create, manipulate, and visualize graphic designs and models. These notes typically cover fundamental concepts like 2D and 3D modeling, transformations, rendering, and the mathematical basis for graphical operations such as geometric transformations and coordinate systems. Topics may include algorithms for line and curve drawing, shading, lighting, texture mapping, and the role of CAD (Computer-Aided Design) in engineering and architectural applications. The notes often explore software like AutoCAD or Blender, along with programming techniques for custom graphic applications, offering practical insights into design, visualization, and problem-solving in modern industries.
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BIT 2319: Artificial Intelligence
Institution: Jomo Kenyatta University of Science and Technology
Year: 2021/2022
Semester: 3rd Year, 1st Semester (3.1)
BIT 2319: Artificial Intelligence
Institution: Jomo Kenyatta University of Science and Technology
Year: 2021/2022
Semester: 3rd Year, 1st Semester (3.1)
BIT 2319: Artificial Intelligence
Institution: Jomo Kenyatta University of Science and Technology
Year: 2021/2022
Semester: 3rd Year, 1st Semester (3.1)
BIT 2319: Artificial Intelligence
Institution: Jomo Kenyatta University of Science and Technology
Year: 2021/2022
Semester: 3rd Year, 1st Semester (3.1)
BIT 2319: Artificial Intelligence
Institution: Jomo Kenyatta University of Science and Technology
Year: 2022/2023
Semester: 3rd Year, 1st Semester (3.1)
BIT 2319: Artificial Intelligence
Institution: Jomo Kenyatta University of Science and Technology
Year: 2022/2023
Semester: 3rd Year, 1st Semester (3.1)
BIT 2319: Artificial Intelligence
Institution: Jomo Kenyatta University of Science and Technology
Year: 2022/2023
Semester: 3rd Year, 1st Semester (3.1)
Review of Data Structures
A review of data structures involves examining various ways to organize, store, and manage data efficiently for different computational tasks. It covers fundamental structures like arrays, linked lists, stacks, and queues, as well as more complex ones like trees, graphs, and hash tables. Each data structure has unique characteristics, advantages, and use cases, influencing factors such as time complexity, memory usage, and ease of implementation. The review typically includes analyzing operations like insertion, deletion, searching, and sorting, as well as their efficiency in different scenarios. Understanding data structures is crucial for optimizing algorithms and improving software performance.
76 Pages
1399 Views
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2.02 MB
Introduction to Artificial Intelligence
Introduction to Artificial Intelligence (AI) explores the development of computer systems that can perform tasks requiring human-like intelligence, such as problem-solving, learning, reasoning, and decision-making. AI encompasses various subfields, including machine learning, natural language processing, computer vision, and robotics. It relies on algorithms and models that enable computers to analyze data, recognize patterns, and make predictions or decisions with minimal human intervention. AI is widely used in industries such as healthcare, finance, and automation, transforming how technology interacts with the world. Understanding AI principles is essential for leveraging its potential and addressing ethical and societal challenges.
174 Views
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3.61 MB
AI and the Design of Agents
"I and the Design of Agents" explores the relationship between human intelligence and the creation of artificial agents capable of autonomous decision-making. It examines how human cognition, reasoning, and problem-solving inspire the development of AI-driven agents that can perceive their environment, process information, and take actions to achieve specific goals. This topic delves into agent architectures, decision-making models, and learning mechanisms that enable adaptability and interaction with dynamic environments. Understanding this connection helps in designing intelligent systems that can collaborate with humans, solve complex tasks, and function effectively in real-world applications.
1504 Views
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4.34 MB