AI+ Architect Course | Online Certification Training
Length
5 days / 5 weeks
Price
$3299
Days
Mon - Fri
Why Choose This Course
AI+ architect is a vendor-agnostic, exam-aligned training course that prepares architects and technical leaders to design, evaluate, and integrate AI systems at enterprise scale. The curriculum spans neural network foundations, optimisation, architectures for natural language and computer vision, model evaluation, deployment infrastructure, responsible AI practices, and generative AI, culminating in a capstone that consolidates skills for real-world delivery. The program aligns to the AI CERTs AI+ Architect certification and includes hands-on practice and an online proctored exam pathway.
This instructor-led course emphasises practical design patterns for building scalable AI solutions, covering end-to-end workflows from data preprocessing and model building to deployment and monitoring. Learners explore how to integrate models into existing systems, apply performance metrics, and prepare solutions for production with appropriate governance.
At training courses now, this training is designed for solution architects, systems architects, AI engineers, and technology managers who want a clear and structured path that also supports exam preparation. The learning approach combines theory with real examples to make complex topics easier to understand. A certificate of course attendance is included to recognise your completion and skills gained.
Prerequisites
- There are no formal prerequisites for this course. Recommended background includes foundational knowledge of artificial intelligence and computer science concepts, plus familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Exam
Candidates can achieve this certification by passing the following exam(s).
- AI+ Architect (AT-320) – online proctored certification exam from AI CERTs
- The exam duration is 90 minutes, giving you enough time to focus and answer comfortably.
- It includes 50 questions made up of multiple‑choice and multiple‑response types.
- You need to score 35 out of 50 (70%) to pass the exam.
- The exam is completed online through a secure AI‑based proctoring system.
The course covers basic to intermediate concepts in a clear and structured way Learning includes theory, hands‑on projects, and real‑world case studies to help you apply what you learn
Books
Flexible Delivery Options
- Live virtual online training attend in real-time from anywhere
Skills Gained
- Explain core neural network building blocks and training workflows.
- Tune models using optimisation strategies and hyperparameter techniques.
- Design architectures for NLP use cases and integrate them in applications.
- Design architectures for computer vision workloads and evaluate trade-offs.
- Apply model evaluation and performance metrics to compare and validate models.
- Plan AI infrastructure and deployment pipelines for scalable, reliable operations.
- Implement responsible AI practices, governance considerations, and risk mitigation.
- Use generative AI models appropriately in solution designs.
- Execute end-to-end solution workflows from data preprocessing to monitoring.
- Integrate models into existing enterprise systems with attention to reliability.
- Plan and deliver a capstone project that demonstrates applied AI architecture skills.
Who Should Attend?
- Solution and systems architects designing AI-enabled platforms and applications.
- AI engineers and developers moving into architecture and integration roles.
- Technical managers and IT leaders responsible for AI adoption and governance.
Course Schedule & Pricing
Choose the schedule that fits your life — all options include full course materials & certification support
Full-time immersion for rapid certification readiness.
Balance your career while you upgrade your skills.
Maximum flexibility for busy working professionals.
Outline
- Fundamentals of neural networks: neurons, layers, activations, backpropagation
- Optimisation strategies: gradient methods, regularisation concepts, tuning approaches
- NLP architectures: embeddings, attention mechanisms, transformer-based designs
- Computer vision architectures: convolutional networks and modern variants
- Model evaluation: accuracy, precision/recall, confusion analysis, calibration concepts
- Dataset preparation and preprocessing across varied data types
- Infrastructure patterns for AI deployment in cloud environments
- CI/CD considerations for AI systems and versioning of models and data
- Serving patterns, latency and throughput considerations, and monitoring signals
- MLOps and observability for drift, performance, and reliability
- Responsible AI: fairness, bias considerations, privacy, and governance practices
- Security considerations for AI systems and data handling
- Generative AI models and appropriate use in solutions
- Retrieval and orchestration patterns for integrating models into applications
- Integration approaches with existing enterprise systems
- Performance optimisation and cost-effectiveness trade-offs
- Testing strategies for AI components in production contexts
- Documentation and architecture decision records for AI solutions
- Capstone project planning, execution, and review
- Exam preparation focus areas and blueprint alignment
- Post-deployment operations: monitoring, improvement loops, and lifecycle management
Terms & Conditions
Frequently Asked Questions (FAQ's)
What certification does this course align to?
Is the exam included with the course?
Is this program vendor-agnostic?
What courses are needed to become an AI architect?
To become an AI architect, you need courses in AI fundamentals, machine learning, data handling, cloud platforms, and AI system design. Structured programs from training courses now combine these skills in one learning path.
What is an AI architect course?
An AI architect course teaches how to design, build, and manage AI solutions from start to deployment. It focuses on architecture, scalability, governance, and real‑world use cases.
How long is an AI architect course?
The length depends on depth, but most AI architect courses take a few weeks to a few months. Instructor‑led and exam‑ready programs usually follow a structured timeline.
Where can I get AI architect training online?
AI architect training is available online through professional training platforms. Training courses now offers structured, online learning designed for real‑world and certification readiness.
Our Partnership
Reliable certification testing is vital for validating professional skills in today’s tech-driven world. As a Pearson VUE Authorised Centre, we provide a secure environment for globally recognised IT exams. This partnership ensures convenient access to certifications with the highest standards of integrity and accuracy.
Our Accreditations
