AI Course Outline

Institution Jomo Kenyatta University of Science and Technology
Course Information Technol...
Year 3rd Year
Semester Unknown
Posted By Jeff Odhiambo
File Type pdf
Pages 2 Pages
File Size 85.83 KB
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Description

An AI course outline typically covers foundational concepts, machine learning techniques, and real-world applications. It begins with an introduction to AI, covering history, types, and ethical considerations. The course then explores machine learning (supervised, unsupervised, and reinforcement learning), deep learning (neural networks, CNNs, RNNs), and natural language processing (NLP). It includes hands-on projects using tools like Python, TensorFlow, or PyTorch. Advanced topics may include computer vision, robotics, and AI ethics. The course concludes with AI deployment, industry trends, and a capstone project to reinforce learning.
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SMA 2371: Partial Differential Equations (Complete Notes, Examples & Solutions) – JKUAT Biostatistics Year 2 Semester 2
These are comprehensive and well-organized lecture notes for SMA 2371: Partial Differential Equations (PDE) offered to BSc. Biostatistics Year 2 Semester 2 students at JKUAT. The notes are neatly arranged from lecture one to the final topics, making them ideal for class learning, revision, CAT preparation, and final examinations. The notes include detailed explanations, worked examples, step-by-step mathematical derivations, solved exercises, and applications of Partial Differential Equations. Topics covered include: • Review of basic concepts and partial derivatives • Jacobians, surfaces and curves in three dimensions • Simultaneous first-order differential equations • Methods of solving symmetric differential equations • Orthogonal trajectories • Pfaffian differential equations • Linear first-order partial differential equations • Formation of PDEs • Elimination of arbitrary constants and arbitrary functions • Heat, Wave, Laplace and Poisson equations • Separation of variables • Fourier and Laplace Transform methods • Numerous worked examples, tutorial questions and examination-style problems with solutions. These notes are suitable for JKUAT students and other university students studying Mathematics, Statistics, Biostatistics, Engineering, Applied Mathematics or related courses. They are an excellent revision resource for CATs and final examinations.
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