Rochester, MN Artificial Intelligence [Feb 24-Mar 18, 2018] Training | AI | IT Training | Disruptive Technologies | Machine Learning | Deep Learning | Neural Networks | Data Science

Features & Benefits

• 8 sessions, each session of 2 hours spread over 4 weeks


• 16 hours of LIVE Instruction spread over 4 weeks


• Training material with lab exercises provided


• Each session is recorded and recordings are provided to students over Microsoft Cloud

Next class starting:

• February 24, 2018
  

Course dates:

February 24 - March 18, 2018

Weekly Schedule

• Saturday and Sunday, every week
• 9:30 AM - 11:30 AM (US Pacific Standard Time) each day

Please confirm your local time

Video Conference Link

Will be sent upon registration and payment

Training Provider:

Omni212

Omni212 IT Training

https://www.omni212.com/services/training/

Artificial Intelligence Training

Course Overview

In this course you will learn the fundamentals of Artificial Intelligence (AI), and apply them. Design intelligent agents to solve real-world problems including, search, games, machine learning, logic, and constraint satisfaction problems. 

About this course

What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common? They are all complex real world problems being solved with applications of intelligence (AI). This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems. 

What you will learn in this course? 

In this course, you’ll learn the basics of modern AI as well as some of the representative  applications of AI. Along the way, we also hope to excite you about the numerous applications and huge possibilities in the field of AI, which continues to expand human capability beyond our imagination. Learn the fundamentals of Artificial Intelligence (AI), and apply them.

What are the pre-requisites?

Linear Algebra, Probability and Statistics, Data Structures & Algorithms, Truth, deduction, and Computation, Database Systems, Logic Programming.

Course Outline

• Fundamentals of AI
• Statistics, Uncertainty, and Bayes networks.
• Principles and programming techniques of artificial intelligence - symbol manipulation, knowledge representation, logical and probabilistic reasoning, learning, language understanding, vision, expert systems
• Principal ideas and developments in artificial intelligence - Problem solving and search, game playing, knowledge representation and reasoning, uncertainty, machine learning, natural language processing
• Machine learning.
• Logic and planning.
• Applications of AI
• Image processing and computer vision.
• Natural language processing and information retrieval.
• Data aspect of AI, classification, clustering, normalization
• Intelligent agents, uninformed search
• Distance metrics (result set comparisons), grouping the results (K-means)
• Heuristic search, A* algorithm
• Adversarial search, games
• Constraint Satisfaction Problems
• Trained algorithms, e.g. random walk, hill climbing
• Machine Learning: Basic concepts, linear models, perceptron, K nearest neighbors
• Machine Learning: advanced models, neural networks, SVMs, decision trees and unsupervised learning
• Machine learning libraries in Python
• Markov decision processes and reinforcement learning
• Logical Agent, propositional logic and first order logic
• AI applications (NLP)
• NLP libraries, e.g. nltk
• AI applications (Vision/Robotics)
• Expert Systems
• Review and Conclusion

Refund Policy

1. There are no refunds.
2. If for any reason the course has not been taken, class is cancelled or rescheduled, the payment can be applied towards any future course by Omni212.