Artificial Intelligence Specialist

Artificial Intelligence Specialist
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USD $2,038.01 without Exam Voucher




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We are currently planning this course, please contact us for further details.

Overview

Whether it’s a chat bot that is indistinguishable from a human or a self-driving car, artificial intelligence is here. We have moved on from the days when machines would just follow algorithms, we now need them to make decisions to keep up with the pace of technology and the amount of information. In this course you’ll learn all about Artificial Intelligence.

In this course you’ll learn about types of AI, AI Techniques, Neural Networks, building AI, architectural models and design patterns.


Duration: 3-days


Intended for
Enterprise Architects, Data Scientists, BI Specialists, Data Architects, Solution Architects and other IT Professionals that are responsible for working with and analysing data.


 Pre-requisites
An understanding of Data Analytics or analytical mathematics as well as IT systems is recommended.


Learning Outcomes
A comprehensive understanding of Artificial Intelligence, its concepts, uses and techniques. The following topics are some of the ones that are covered during the course:

  • Key Principles of Artificial Intelligence
  • Modern AI and Cognitive AI
  • The Evolution of AI and Machine Learning
  • AI, Machine Learning and Deep Learning
  • Artificial Intelligence and Business Intelligence
  • Cybernetics and Brain Simulation
  • Language Understanding, Learning and Adaptive Systems and Problem Solving
  • Computer Visions, Pattern Recognition, Expert Systems and Robotics
  • Natural Language Processing (NLP) and Speech Recognition
  • Hybrid Intelligent Systems
  • Frictionless Integration and Fault Tolerance Model Integration
  • Types of AI
  • Artificial Intelligence Techniques
  • Heuristics and Support Vector Machines
  • Artificial Neural Networks and Markov Decision Process
  • Understanding Artificial Neural Networks
  • Neural Network Layers
  • Artificial Neural Network Components
  • Training Neural Networks and Neural Network Activation Functions
  • Understanding the Inter-relationships of AI, Machine Learning and Deep Learning
  • Building AI, General Intelligence, Reasoning and Knowledge Representation
  • Motion and Manipulation, Social Intelligence and Creativity
  • AI Architecture Models and Design Patterns
  • Understanding and Working with Neural Network Architectures
  • Fundamental Neural Network Architectures
  • Memory-Influenced Architectures
  • Parabolicity Cell-Driven Architectures

And more…


In the Details tab you can find more information about this workshop:

  • Topics Covered - High-level description of topics covered during the course
  • Agenda - The full course outlines are provided.
  • Schedule
  • Registration information regarding the cancellation policy.
  • Location Details regarding the planned location of the workshop.
  • Exams and Certification - An explanation of how to take exams and get certified upon completion of the workshop.

 

Note: All quoted pricing is excluding GST. For customers in Australia GST will be added during the check-out process.

Topics Covered 
The following topics are covered during the course 

Day 1 / Module 1 (9:00 AM - 4:30 PM)
Fundamental Artificial Intelligence
This course module covers foundational AI topics and concepts and provides an understanding of essential AI techniques, the basics of neural networks and fundamental neural network architectural layers. The following primary topics are covered:

  • A Brief History of AI and Synthetic Intelligence
  • AI in Different Forms and Shapes
  • Modern AI and Cognitive AI
  • The Evolution of AI and Machine Learning
  • AI, Machine Learning and Deep Learning
  • Artificial Intelligence and Business Intelligence
  • Cybernetics and Brain Simulation
  • Symbolic, Sub-Symbolic and Statistical
  • Language Understanding, Learning and Adaptive Systems and Problem solving
  • Computer Visions, Pattern recognition, Expert Systems and Robotics
  • Natural Language Processing (NLP) and Speech Recognition
  • Hybrid Intelligent systems
  • Key Principles of Artificial Intelligence
  • Frictionless Integration and Fault Tolerance Model Integration
  • Types of AI (Narrow AI, Artificial General Intelligence (AGI) and Superintelligence)
  • Artificial Intelligence Techniques
  • Heuristics and Support Vector Machines
  • Artificial Neural Networks and Markov Decision Process
  • Understanding Artificial Neural Networks
  • Neural Network Layers (Input, Output and Hidden)
  • Artificial Neural Network Components (Neurons, Connections, Weights, Propagation Functions and Learning Rules)
  • Training Neural Networks and Neural Network Activation Functions

Day 2 / Module 2 (9:00 AM - 4:30 PM)
Advanced Artificial Intelligence
This course module covers important areas of AI application that further delve into the relationships of AI with machine learning and deep learning, as well as the relationship between reinforcement learning and artificial learning. Also provided is comprehensive coverage of neural networks, including different neural network architectural models. The following primary topics are covered: 

  • Understanding the Inter-relationships of AI, Machine Learning and Deep Learning
  • Continuous Learning and Reinforcement learning
  • Building AI, General Intelligence, Reasoning and Knowledge representation
  • Motion and Manipulation, Social Intelligence and Creativity
  • AI Design (Value Creation, Value Realization and Defensibility)
  • AI Architecture Models and Design Patterns
  • AI Mechanisms (AI Complete, AI Box, Percept, Rule-based System, etc.)
  • Computational Humor, Soft Computing and Description Logic
  • Understanding and Working with Neural Network Architectures
  • Input/Output Cells, Key Cells and Architectural Layers
  • Fundamental Neural Network Architectures (P, FF, RBF, DFF, RBM, AE, SAE, etc.)
  • Recurrent Cell-based Architectures (RNN, ESN)
  • Influenced by Hidden Cells (VAE, DAE)
  • Memory-Influenced Architectures (LSTM, GRU)
  • Parabolicity Cell-Driven Architectures (MC, BM, DBN)
  • Backfed Cell-based Architecture (Hopfield Network)
  • Pool and Kernel influenced architectures (DCN, DN, DCIGN)
  • Influenced by Match Input (Generative Adversarial Networks)
  • Influenced by Spiking Hidden Cells (Liquid State machine)
  • Influenced by Hidden Cells (ELM, DRN, KN, SVM, NTM, etc.)

Day 3 / Module 3 (9:00 AM - 4:30 PM)
Artificial Intelligence Lab
This course module presents participants with a series of exercises and problems that are designed to test their ability to apply their knowledge of topics covered in previous courses. Completing this lab will help highlight areas that require further attention and will further prove proficiency in AI, machine learning and deep learning systems and neural network architectures, as they are applied and combined to solve real-world problems.

The Trainer works closely with participants to ensure that all exercises are carried out completely and accurately. Attendees can voluntarily have exercises reviewed. 


Workshop Materials
The following materials will be provided: 

  • Full-colour printed course modules
  • Mind-maps

Schedule

  • Training starts at 9:00AM and we aim to finish around 4:30PM each day.
  • Breaks are scheduled at 10:30AM, 12:00 noon and 2:30PM but the exact times will be determined by the trainer.
  • The course is fully catered for; Morning Tea, Lunch and Afternoon Tea are provided.

 Registration 

  • Please select your preferred location from the options and select whether you'd like Exam Vouchers, then follow the registration process.
  • Alternatively, you can e-mail info@silverplatypus.com and request a quote or an invoice
  • We do offer private workshops for companies that want to hold workshops specifically for their employees, please contact us directly for a discussion or quote.
  • Accepted payment methods include Invoice, Wire Transfer, Credit Card (Amex, Visa, Mastercard) and Paypal.

Cancellation
Please see our cancellation policy.


Location
Please select the relevant city from the choices presented. The exact address of the workshop will be provided closer to the workshop date.


 Exams & Certification

  • All workshop attendees are issued an official "Certificate of Completion" for this workshop.
  • There is one exam required to attain certification. The exam can be taken at any Pearson VUE testing center in the world or online via Pearson VUE Online Proctoring. 

 

Note: All quoted pricing is excluding GST. For customers with a billing address in Australia GST will be added during the check-out process.

Weight (kg): 0kg
Trainers are yet to be detailed.


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