artificial intelligence syllabus

Deep learning is a sub-field of machine learning that focuses on learning complex, hierarchical feature representations from raw data.

omscs.gatech.edu·422.1 KB

In this course, students will learn the fundamental principles, underlying mathematics, and implementation details of deep learning. This includes the concepts ...

dev-omscs.cc.gatech.edu·291.5 KB

Develop sophisticated problem-solving skills within the context of artificial intelligence. •. Understand how agent based application are designed and ...

inside.tamuc.edu·291.3 KB

Our aim is to familiarize graduate students with basic optimization methods for solving supervised machine learning problems, so that they can use these ...

myrbs.business.rutgers.edu·217.1 KB

An introduction to the field of deep learning, including basic machine learning, supervised learning, logistic regression, loss functions, neural networks ...

people.tamu.edu·214.3 KB

The toolkit offers a wide range of materials, including both tools and resources for the use of AI in education — such as software, guidelines, tutorials, and ...

aipioneers.org·208.5 KB

This course introduces modern techniques of neural networks and deep learning, which have revolutionized machine learning and artificial intelligence ...

myrbs.business.rutgers.edu·205.6 KB

Your machine learning algorithms will classify handwritten digits and photographs. The techniques you learn in this course apply to a wide variety of artificial.

tbp.studentorg.berkeley.edu·173.9 KB

This course introduces fundamental knowledge of deep learning algorithms, practical skills to build, train and tune a deep artificial neural network with ...

cse.tcu.edu·168.6 KB

Basic concepts and techniques of artificial intelligence: problem solving, search, deduction, intelligent agents, knowledge representation. Topics chosen from ...

www.sjsu.edu·166.0 KB

This course covers the basic building blocks and intuitions behind designing, training, tuning, and monitoring of deep networks.

utdirect.utexas.edu·152.4 KB

Day 1-3: Basics of Artificial Intelligence, Machine Learning, Deep Learning. ... Information contained in the course syllabus, other than the grade and absence ...

astec.arizona.edu·147.6 KB

CS6601: Artificial Intelligence is typically run as a 16-week class. All assignments are due at the end of the week, on Sunday at midnight ...

omscs.gatech.edu·137.5 KB

1.1 Define artificial intelligence and its key components: machine learning, natural language processing and computer vision. 1.2 Explain the.

www.cecil.edu·136.5 KB

Main topics to be covered: The main topics are Deep Learning, computational neuroscience, machine learning, deep-networks, artificial vision and auditory ...

engineering.purdue.edu·132.8 KB

LO-1.1: Define intelligence and artificial intelligence (AI). LO-1.2: Compare strong and weak AI. LO-1.3: Identify common AI applications ...

www.amu.apus.edu·117.6 KB

A broad range of algorithms will be covered, such as linear and logistic regression, neural networks, deep learning, support vector machines, tree-based methods ...

engineering.nyu.edu·114.2 KB

The class will cover three major topics including neural network and deep learning theory, implementation of deep learning algorithms, and applications of deep ...

www.fau.edu·92.1 KB

The course will cover topics including the foundation of deep learning, how to train a neural network (optimization), architecture designs for various tasks, ...

fec.seas.ucla.edu·88.4 KB

This course is an introduction to deep learning. Topics include convolution neural networks, recurrent neural networks, and deep reinforcement learning. The ...

courses.grainger.illinois.edu·87.8 KB