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London Artificial Intelligence Training
Sat, Apr 15, 2017, 8:00 PM – Sat, May 20, 2017, 10:00 PM BST
Attend our Information Session
RSVP or Register for Information Session here - http://bit.ly/2mHXdvm
Why Artificial Intelligence Training from Omni212?
1. Omni212 provides Artificial Intelligence Product engineering services
2. Two of our most experienced, AI instructors teach this class.
3. Employees of Microsoft, Zulily, have been interested in taking our AI classes.
4. Class recordings, Training manual for this class will be made available.
5. Post class support
6. Appropriate software access
7. Career advancement and Job placement assistance
Next class starting
April 15, 2017
Video Conference link
Will be sent upon your registration and payment
Training Session Details
There will be 9 online sessions, each session being of 2 hours. Every session will have presentation about theory, concepts and technology, followed by Hands-on Lab practice exercises.
- Begins April 15, taught over 6 weeks ending on May 20
- April 15, 16 Sat/Sun
- April 22 Sat
- April 29, 30 Sat/Sun
- May 6 Sat
- May 13, 14 Sat/Sun
- May 20 Sat
- Times: 12:00 PM - 2:00 PM (US Pacific Time) every session
- Each session will be recorded and the recordings will be shared after each session with students.
Artificial Intelligence Technology
Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. Artificial Intelligence (AI) technology is increasingly prevalent in our everyday lives. It has uses in a variety of industries from gaming, journalism/media, to finance, as well as in the state-of-the-art research fields from robotics, medical diagnosis, and quantum science.
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.
- You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.
- Hands on experience will be gained by building a basic search agent. Adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.
What you will learn in this course?
- In this course you’ll learn the basics and applications of AI, including: machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.
- 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. Design intelligent agents to solve real-world problems including, search, games, machine learning, logic, and constraint satisfaction problems.
What are the pre-requisites?
Some of the topics in Introduction to Artificial Intelligence will build on probability theory and linear algebra. You should have understanding of probability theory comparable to that covered in our Intro to Statistics course.
Students are required to have some basic of Python programming and an understanding of probability. Homework assignments will have a programming component in Python. The course offers an excellent opportunity for students to dive into Python while solving AI problems and learning its applications.
Introduction to AI, history of AI, course logistics
Intelligent agents, uninformed search
Heuristic search, A* algorithm
Adversarial search, games
Constraint Satisfaction Problems
Machine Learning: Basic concepts, linear models, perceptron, K nearest neighbors
Machine Learning: advanced models, neural networks, SVMs, decision trees and unsupervised learning
Markov decision processes and reinforcement learning
Logical Agent, propositional logic and first order logic
AI applications (NLP)
AI applications (Vision/Robotics)
Review and Conclusion
Class Size: Maximum 22
1. Each student gets access to a login account on the cloud, Microsoft Azure, where they install Hadoop on a cloud virtual machine and perform hands-on lab exercises with instructor guidance. There will be 2 experienced big data, hadoop instructors supporting the students throughout the class.
ADVANTAGES OF TAKING THIS COURSE WITH OMNI212:
1. Class recordings will be made available.
2. Post class support
3. Course material available.
4. Cloud account on Microsoft Azure with Hands-on lab exercises under the guidance of two experienced big data, hadoop instructors.
5. Career advancement and Job placement assistance
1. 100% refund will be provided under the following circumstances:
- In case Omni212 cancels or reschedules the class.
- If the student cancels or raises a refund up to 48 hours before the start of course.
- No negative review is given without giving Omni212 the chance to remedy the situation within 15 days after the complaint was registered by the student.
2. 50% refund will be issued under the circumstance that:
- Student raises a refund request within 3 days after the first training session.
3. No refund will be provided under the following circumstances:
- Student raises a request more than 3 days after start of the course.
- Student registers for the course and does not attend the course for whatever reason.
4. Refunds will be issued within 15 days once the request has been approved.
Date and Time
Instructor led Online | Video Conference
Online - please disregard address & map locations.