Learn Artificial intelligence in Los Angeles, California

Training courses, certificates, diplomas or degree programs of Artificial intelligence for students in Los Angeles, CA

Total 10 training courses and degree programs available.

Intelligent Robotics (Master Degree)

Course Format: Public Course / Instructor-Led / Open Enrollment
School/Trainer: USC Viterbi School of Engineering
Training Center(s)/Venue(s): Los Angeles, United States

Master of Science in Computer Science with Specialization in Intelligent Robotics.

Artificial Intelligence

Course Format: Online / Virtual Classroom / Webinar
School/Trainer: Regis University

Introduces the concepts and techniques of Artificial Intelligence (AI) including use of the Prolog language, knowledge representation, machine learning, expert systems, uncertainty, neural networks, and real world application of AI techniques.


Course Format: Online / Virtual Classroom / Webinar
School/Trainer: Franklin University

This course focuses on the use of artificial intelligence tools and techniques in industry. Topics include cognitive psychology topics, foundation material (e.g., search algorithms, knowledge representation and AI languages) and tools (e.g., expert systems, natural language interfaces and neural networks).

Artificial Intelligence for Games and Simulations

Course Format: Online / Virtual Classroom / Webinar
School/Trainer: DeVry University Online

Looking at artificial intelligence methods and techniques, this course explores autonomous movement, path finding, decision making, genre considerations and learning with dynamic programming.

Introduction to Artificial Intelligence

Course Format: Online / Virtual Classroom / Webinar
School/Trainer: Park University School For Online Learning

The student will learn the terminology and methods used in a variety of artificial intelligence (AI) areas. These topics will be covered: history of artificial intelligence, search techniques, knowledge representation. In addition, one or more of these topics will be covered: expert systems, uncertainty, case-based reasoning, neural networks, vision, robotics. The student may use various AI tools, Lisp, and/or Prolog for AI projects.

Artificial Intelligence

Course Format: Online / Virtual Classroom / Webinar
School/Trainer: Stevens Institute of Technology

An introduction to the large and diverse field of artificial intelligence. Topics include: problem-solving by search and constraint satisfaction; alpha-beta search for two-player games; and logic and knowledge representation, planning, learning, decision theory, statistical learning, and computer vision.

Pattern Recognition and Classification

Course Format: Online / Virtual Classroom / Webinar
School/Trainer: Stevens Institute of Technology

Introduction and general pattern recognition concerns and statistical pattern recognition: introduction to statistical pattern recognition, supervised learning (training) using parametric and nonparametric approaches, parametric estimation and supervised learning, maximum likelihood (ML) estimation, the Bayesian parameter estimation approach, supervised learning using nonparametric approaches, Parzen windows, nonparametric estimation, unsupervised learning and clustering, and formulation of unsupervised learning problems; syntactic pattern recognition: quantifying structure in pattern description and recognition, grammar-based approach and applications, elements of formal grammars, syntactic recognition via parsing and other grammars, graphical approaches, and learning via grammatical inference; neural pattern recognition: the artificial neural network model, introduction to neural pattern associators and matrix approaches, multilayer, feed-forward network structure, and content addressable memory approaches. The Hopfield approach to pattern recognition, unsupervised learning, and self-organizing networks.

Computer Vision

Course Format: Online / Virtual Classroom / Webinar
School/Trainer: Stevens Institute of Technology

An introduction to the field of Computer Vision, focusing on the underlying algorithmic, geometric and optic issues. The course starts with a brief overview of basic image processing topics (convolution, smoothing, edge detection). It then proceeds on various image analysis topics: binary images, moments-based shape analysis, Hough transform, image formation, depth and shape recovery, photometry, motion, classification, special topics.

Artificial Intelligence Overview Workshop

Course Format: Online / Virtual Classroom / Webinar
School/Trainer: NobleProg Ltd

Artificial Intelligence History
Intelligent Agents

Problem Solving
Solving Problems by Searching
Beyond Classical Search
Adversarial Search
Constraint Satisfaction Problems

Knowledge and Reasoning
Logical Agents
First-Order Logic
Inference in First-Order Logic
Classical Planning
Planning and Acting in the Real World
Knowledge Representation

Uncertain Knowledge and Reasoning
Quantifying Uncertainty
Probabilistic Reasoning
Probabilistic Reasoning over Time
Making Simple Decisions
Making Complex Decisions

Learning from Examples
Knowledge in Learning
Learning Probabilistic Models
Reinforcement Learning

Communicating, Perceiving, and Acting
Natural Language Processing
Natural Language for Communication

Philosophical Foundations
AI: The Present and Future

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