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AI+ Architect

Length 5 days
Price NZD 4350 exc GST
Inclusions Exam Voucher

Course overview

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Why study this course

The AI+ Architect course offers comprehensive training in advanced neural network techniques and architectures. It covers the fundamentals of neural networks, optimisation strategies, and specialised architectures for natural language processing (NLP) and computer vision. Participants will learn about model evaluation, performance metrics, and the infrastructure required for AI deployment. The course emphasises ethical considerations and responsible AI design, alongside exploring cutting-edge generative AI models and research-based AI design methodologies. A capstone project and course review consolidate learning, ensuring participants can apply their skills effectively in real-world scenarios. This certification equips learners with the knowledge and practical experience to excel in AI architecture and development.

Exam and certification

This course also prepares students for the AI+ Architect certification, and an exam voucher is included with the course.

The exam is:

90 minutes
50 multiple choice / multiple response questions
Pass mark is 35 out of 50 (i.e. 70%)
Online via AI Proctoring platform

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What you’ll learn

This course is designed to teach participants how to:

Develop end-to-end AI solutions, encompassing the entire workflow from data preprocessing and model building to deployment and monitoring. This includes integrating AI models into larger systems and applications, ensuring they work seamlessly within existing infrastructures.
Implement various neural network architectures from scratch using programming frameworks like TensorFlow or PyTorch. This includes creating, training, and debugging models for different applications.
Conduct AI research, enabling them to stay at the forefront of AI developments. This includes identifying research gaps, proposing novel solutions, and critically evaluating current AI methodologies to drive innovation in the field.
Explore advanced concepts in generative AI models and engage in research-based AI design. This includes developing innovative AI solutions and understanding the latest advancements in AI research, preparing them for cutting-edge applications and further research opportunities.

AI CERTs at Lumify Work

AI CERTs™ stands at the forefront of AI and blockchain certification, offering world-class programs that prepare individuals to lead in these rapidly growing fields. AI CERTs courses and certifications are vendor agnostic and designed to bridge the gap between theoretical knowledge and practical application, ensuring learners are equipped to make an immediate impact in their careers.
Lumify Work is an Authorized Training Partner for AI CERTs in Australia, New Zealand, and the Philippines.

View all AI CERTs at Lumify Work courses

Who is the course for?

This course is intended for:

Cloud Architects
AI Specialists
IT Professionals
Data Scientists and Analysts
Software Developers
Tech Managers and Leaders

Course subjects

Module 1: Fundamentals of Neural Networks

Introduction to Neural Networks
Neural Network Architecture
Hands-on: Implement a Basic Neural Network

Module 2: Neural Network Optimisation

Hyperparameter Tuning
Optimisation Algorithms
Regularisation Techniques
Hands-on: Hyperparameter Tuning and Optimisation

Module 3: Neural Network Architectures for NLP

Key NLP Concepts
NLP-Specific Architectures
Hands-on: Implementing an NLP Model

Module 4: Neural Network Architectures for Computer Vision

Key Computer Vision Concepts
Computer Vision-Specific Architectures
Hands-on: Building a Computer Vision Model

Module 5: Model Evaluation and Performance Metrics

Model Evaluation Techniques
Improving Model Performance
Hands-on: Evaluating and Optimising AI Models

Module 6: AI Infrastructure and Deployment

Infrastructure for AI Development
Deployment Strategies
Hands-on: Deploying an AI Model

Module 7: AI Ethics and Responsible AI Design

Ethical Considerations in AI
Best Practices for Responsible AI Design
Hands-on: Analysing Ethical Considerations in AI

Module 8: Generative AI Models

Overview of Generative AI Models
Generative AI Applications in Various Domains
Hands-on: Exploring Generative AI Models

Module 9: Research-Based AI Design

AI Research Techniques
Cutting-Edge AI Design
Hands-on: Analysing AI Research Papers

Module 10: Capstone Project and Course Review

Capstone Project Presentation
Course Review and Future Directions
Hands-on: Capstone Project Development

Prerequisites

A foundational knowledge on neural networks, including their optimisation and architecture for applications
Ability to evaluate models using various performance metrics to ensure accuracy and reliability
Willingness to know about AI infrastructure and deployment processes to implement and maintain AI systems effectively

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.