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$199.00 USD
$199.00 USD
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Note: This new course is coming soon and is currently available for pre-order.

The AI Professional Consulting course provides essential coverage of the most important and relevant topics associated with predictive AI, generative AI, as well as fundamental AI engineering and architecture. It also includes business case development techniques for AI projects and change management and AI adoption strategies.

Complete the AI Professional Consulting course and, optionally, get accredited as a Certified AI Consultant 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 Consultant certifications, upon passing the exam you will also receive official AI Professional and AI Consultant 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 Consultant track here.

Download Guide &
Course Outlines (PDF)

The AI Professional Consulting 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 7: Fundamental Predictive AI Engineering
  • Module 10: Fundamental Generative AI Engineering
  • Module 13: Fundamental AI Architecture & Design

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 7: Fundamental Predictive AI Engineering

This course module delves into a range of predictive AI engineering practices and techniques, and further provides a detailed introduction of neural network architecture components. The course module illustrates how and when different practices and components of AI systems with neural networks need to be defined and applied. Finally, the module provides a set of key principles and best practices for carrying out AI engineering techniques.


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 Model Selection and Hyperparameter Tuning
  • Predictive AI Model Deployment, Monitoring and Maintenance
  • Predictive AI Bias Detection and Mitigation
  • Predictive AI Model Explainability and Interpretability
  • Predictive AI Model Evaluation and Validation Techniques
  • Data Preprocessing Techniques, Overfitting and Regularization
  • Performance Optimization Techniques for Predictive AI Models

  • Understanding Predictive Neural Networks and Models
  • Neural Network Types, Neurons, Layers, Links, Weights
  • Loss, Hyperparameters, Learning Rate, Bias, Epoch
  • Activation Functions (Sigmoid, Tanh, ReLU, Leaky ReLU, Softmax,
    Softplus)
  • Neuron Cell Types (Input, Backfed, Noisy, Hidden, Probabilistic,
    Spiking, Recurrent, Memory, Kernel, Convolution, Pool, Output,
    Match Input, etc.)
  • Common Neural Network Architectures for Predictive AI Systems

Module 10: Fundamental Generative AI Engineering

This course module provides in-depth coverage of essential engineering practices for training and operating generative AI systems, including various data processing, filtering and management techniques specific to creative content generation. The module further covers commonly related topics, such as natural language processing (NLP), transfer learning and the use of pre-trained models.


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

  • Data Representation and Encoding
  • Latent Space and its Manipulation
  • Prompt Engineering
  • Metrics for Evaluating Generative Models
  • Generative AI Model Selection and Hyperparameter Tuning
  • Generative AI Model Deployment, Monitoring and Maintenance
  • Generative AI Bias Detection and Mitigation
  • Generative AI Model Explainability and Interpretability
  • Model Evaluation and Validation Techniques for Generative AI
  • Data Preprocessing Techniques, Overfitting and Regularization

  • Performance Optimization Techniques for Generative AI Models
  • Understanding Generative Neural Networks and Models
  • Neural Network Types, Neurons, Layers, Links, Weights in Generative AI
  • Loss, Hyperparameters, Learning Rate, Bias, Epoch in Generative AI
  • Activation Functions (Leaky ReLU, Tanh, ReLU, Softmax, Sigmoid, Softplus)
  • Neuron Cell Types (Input, Backfed, Noisy, Hidden, Probabilistic, Spiking, Recurrent, Memory, Kernel, Convolution, Pool, Output, Match Input, etc.)
  • Common Neural Network Architectures for Generative AI Systems

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)

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

 

Lifetime Access Guarantee

Access to the interactive eLearning platform (1) and the study kit platform (3) is dependent on third-party platform providers. As a result, Arcitura cannot make any guarantees or warranties regarding the behavior or availability of the platform, nor can Arcitura guarantee a specific duration for which these platforms will remain available. When your course is set up, your access will have no expiration date and will be provided for a minimum of one year and indefinitely thereafter, for as long as the platforms remain available under the conditions by which they were contracted by Arcitura. The PDF documents (3) that will be made available for you to download are yours to keep forever.

QUESTIONS?

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