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The AI Architecture & Design course covers fundamental and advanced AI systems and technology architecture topics, including design principles, distributed AI computing and scalability and reliability infrastructure, decision-making logic, performance optimization, security and enterprise architecture integration.

Complete the AI Architecture & Design course and, optionally, get accredited as a Certified AI Architect by passing the certification exam. You can purchase the course now and get the exam later, or you can get them together at a discount as part of the Certification Bundle.

Upon completing the course you will receive a digital certificate of completion, as well as a digital training badge from Acclaim/Credly. Because this course encompasses both the AI Professional and AI Architect certifications, upon passing the exam you will also receive official AI Professional and AI Architect digital accreditation certificates and certification badges from Acclaim/Credly, along with an account that can be used to verify your certification status.

If you already completed the AI Professional course modules, you can purchase a partial course (or a partial bundle) with only the modules specific to the AI Architect track here.

The AI Architecture & Design course is comprised of the following 5 course modules, each of which has an estimated completion time of 10 hours:

  • Module 1: Fundamental Predictive AI
  • Module 4: Fundamental Generative AI
  • Module 13: Fundamental AI Architecture & Design
  • Module 14: Advanced AI Architecture & Design
  • Module 15: AI Architecture & Design Lab

Choose the Certification Bundle to receive the entire course together with the online-proctored certification exam and a set of practice exam questions, all at a bundle discount.

Exam Details

Upon purchasing this course, you will automatically receive access via the Online Interactive eLearning platform. To provide you with the greatest flexibility, you will also have the option to access the course materials via two additional eLearning formats, at no extra cost. All three eLearning formats are briefly described below. A more detailed comparison can be found here.
  1. For everyday learning: An online interactive eLearning platform with individual lessons, as well as interactive and automatically graded exercises and practice questions.
  2. For learning on-the-go: A study kit platform with access to full course documents that support online/offline synching, annotations, comments, custom bookmarks and cross-document searches.
  3. For your reference: A set of printable watermarked PDF documents that you can keep (for all course workbooks and posters).
All three forms of access are subject to Arcitura’s *. Upon purchase, access to the online interactive eLearning platform (1) is provided within one business day. Access to the study kits (2) and the PDF documents (3) is provided upon request.

The course is comprised of a set of modules. Each module has a set of lessons and is further supplemented with exercises to help reinforce your understanding of key topics. Shown below are the digital contents and the topic outline for each course module:


Module 1: Fundamental Predictive AI

This course module illustrates how predictive AI can be used and applied in a range of business applications, as well as essential coverage of predictive AI practices and systems. The module explores the most common learning approaches and functional areas that AI systems are used for. All of the content is authored in easy-to-understand, plain English.


Course Module Contents


  • Workbook Lessons (100+ pages)
  • Interactive Exercises
  • Mind Map Poster

  • Symbol Legend Poster
  • Practice Exam Questions
  • PDFs of Workbook and Posters (printable)

Topics Covered

  • Predictive AI Business and Technology Drivers
  • Predictive AI Benefits
  • Common Risks and Challenges of Using Predictive AI
  • Business Problem Categories Addressed by AI
  • Types of Predictive AI
  • Common Predictive AI Learning Approaches
  • Understanding Predictive AI Learning and Model Training
  • Step-by-Step Training Loop Process

  • Supervised Learning, Unsupervised Learning, Continuous Learning
  • Heuristic Learning, Semi-Supervised Learning, Reinforcement Learning
  • Common Predictive AI Functional Designs, Computer Vision, Pattern Recognition
  • Robotics, Natural Language Processing (NLP)
  • Speech Recognition, Natural Language Understanding (NLU)
  • Understanding AI Models and Neural Networks

Module 4: Fundamental Generative AI

This course module explores the application of generative AI within a range of business scenarios and provides fundamental coverage of generative AI concepts, models, best practices and neural networks, including Generative Adversarial Networks (GANs), Variational Encoders (VAEs) and Transformer models. All of the content is authored in easy-to-understand, plain English.


Course Module Contents


  • Workbook Lessons (100+ pages)
  • Interactive Exercises
  • Mind Map Poster

  • Symbol Legend Poster
  • Supplement
  • Practice Exam Questions
  • PDFs of Workbook and Posters (printable)

Topics Covered

  • Generative AI Business and Technology Drivers
  • Generative AI Benefits
  • Common Risks and Challenges of Using Generative AI
  • Business Problem Categories Addressed by Generative AI
  • Understanding Models, Algorithms and Neural Networks
  • Types of Generative AI

  • Training Generative Models and Understanding the Training Loop
  • Understanding Generative Adversarial Networks (GANs)
  • Understanding Variational Encoders (VAE)
  • Understanding Transformers
  • Steps to Building AI Systems
  • Generative AI Best Practices

Module 13: Fundamental AI Architecture & Design

This course module provides an essential understanding of AI system and solution architecture. It explains the different AI system architecture types, scopes and modes and provides detailed coverage of core AI system modules (including data ingestion, data preprocessing, feature engineering, inference engine and model repository) and monitors (including operations, data, model and ancillary monitors).


Course Module Contents


  • Workbook Lessons (100+ pages)
  • Interactive Exercises
  • Mind Map Poster
  • Core Monitors and Modules Poster

  • Symbol Legend Poster
  • Practice Exam Questions
  • PDFs of Workbook and Posters (printable)

Topics Covered

  • AI Architecture vs. AI Engineering Comparison
  • AI Product Architectures vs. Custom AI Architectures
  • AI Architecture Scopes (System and Solution)
  • AI Solution Operational Modes (Training and Production)
  • AI System Architecture Types (Monolithic, Modular, Hybrid)
  • AI Solution Data Storage (Internal, External, Hybrid)
  • AI System Core Modules
  • Data Ingestion for Common Predictive AI and Generative AI Data Sources

  • Data Preprocessing in Predictive AI and Generative AI Systems
  • Feature Engineering in Predictive AI and Generative AI Systems
  • Inference Engine in Predictive AI and Generative AI Systems
  • Model Repository in Predictive AI and Generative AI Systems
  • Operations Monitors (Performance, Resource)
  • Data Monitors (Input, Output)
  • Model Monitors (Weight and Gradient, Activation Distribution, Bias and Fairness)
  • Ancillary Monitors (Explainability, Robustness and Adversarial Attack, Data Quality, Data Labeling)

Module 14: Advanced AI Architecture & Design

This course explores a range of techniques and complex topics dedicated to AI system design and technology architecture, including scalability models, performance and optimization techniques and resiliency architectures.


Course Module Contents


  • Workbook Lessons (100+ pages)
  • Interactive Exercises
  • Mind Map Poster

  • Practice Exam Questions
  • PDFs of Workbook and Poster (printable)

Topics Covered

  • AI System Scalability Patterns
  • Distributed Data Processing and Data Caching
  • Data Partitioning and Sharding
  • Incremental Processing
  • Hardware Acceleration
  • Autoscaling and Load Balancing
  • Continuous Learning
  • AI System Performance Patterns

  • Parallelism and Concurrency
  • Edge Caching and Vectorization
  • Data Compression
  • Lazy Loading
  • AI System Resiliency Patterns
  • Fault Tolerance
  • Graceful Degradation
  • Chaos Engineering

Module 15: AI Architecture & Design Lab

This course module provides a series of case-study driven, lab-style exercises and problems that are designed to test your ability to apply your knowledge of topics covered in previous modules. Completing this lab helps reinforce understanding of preceding topics and further demonstrates how different practices and technologies can be applied together as part of greater solutions.


Course Module Contents


  • Lab Exercise Booklet
  • Mind Map Poster

  • Practice Exam Questions
  • PDFs of Exercise Booklet and Poster (printable)

Topics Covered

  • Reading Exercise 15.1: Case Study Background: IVA
  • Lab Exercise 15.2: Model Training for Realtime Predictions
  • Lab Exercise 15.3: Realtime Computations & Resource Exhaustion
  • Lab Exercise 15.4: System Scalability & Model Accuracy
  • Lab Exercise 15.5: Reliable Content Generation & System Errors

  • Reading Exercise 15.6: Case Study Background: HealthV
  • Lab Exercise 15.7: LLM Training for Personalized Content Generation          
  • Lab Exercise 15.8: Content Delivery Optimization & Remote Access
  • Lab Exercise 15.9: Data Volume & Resource Constraints
  • Lab Exercise 15.10: Realtime Monitoring & Fluctuating Workloads

Learn About Arcitura: Take the Video Tour

Watch these helpful informational videos to learn about Arcitura programs, courses and certifications.

About Arcitura

About Arcitura Courses

About Arcitura Certifications

What’s in an Arcitura Course

Comprehensive
Coverage

Each course provides a comprehensive curriculum with 2-3 modules and 20-40 hours of training.

More Than Just
Video Lessons

In addition to standard video lessons, courses include full-color workbooks and reference posters for all lessons.

Interactive & Graded
Challenges

Courses also include interactive and graded exercises, interactive and graded self-tests and other supplements.

The Arcitura Difference

EACH COURSE

  • is authored by a dedicated courseware development team
  • has a self-test, accreditation exam and professional certification
  • is available via two different eLearning platforms

ALL COURSES

  • undergo a common development process
  • are authored to be consistent in quality, structure and style
  • share a common vocabulary and symbol notation
  • are authored in collaboration with subject matter experts

Take Your Skills Anywhere

Regardless of whether you are an individual looking to boost your career or an organization looking to up-skill a team, Arcitura courses and certifications provide a sound investment.

Because both courses and accreditations are vendor-neutral, they empower you with skills and credentials that you can take to wherever you need to go.

Professional Instructor-Led Training & Coaching

 

QUESTIONS?

Contact info@arcitura.com or 604-904-4100 during PT working hours.