Prerequisites
- Foundational Knowledge of Neural Networks: Understanding architecture, optimization, and their role in AI applications.
- Model Evaluation Skills: Ability to assess performance metrics for reliability and scalability.
- AI Deployment Awareness: Familiarity with infrastructure and processes for seamless integration of AI systems.
Exam Details
- Modules (10)
- Examination (1)
- 50 MCQs, 90 Minutes
- Passing Score (70% (35/50) )
Exam Blueprint
| Modules | Percentage |
|---|---|
| Fundamentals of Neural Networks | 10 |
| Neural Network Optimization | 10 |
| Neural Network Architectures for NLP | 10 |
| Neural Network Architectures for Computer Vision | 10 |
| Model Evaluation and Performance Metrics | 10 |
| AI Infrastructure and Deployment | 10 |
| AI Ethics and Responsible AI Design | 10 |
| Generative AI Models | 10 |
| Research-Based AI Design | 10 |
| Capstone Project and Course Review | 10 |
What you will get
High-Quality Videos, E-book (PDF & Audio), and Podcasts
AI Mentor for Personalized Guidance
Quizzes, Assessments, and Course Resources
Online Proctored Exam with One Free Retake
Comprehensive Exam Study Guide
Why This Certification Matters
Smarter Design Decisions
Learn to apply AI tools for optimized architectural planning, enhancing efficiency, accuracy, and scalability.Innovative AI Integration
Leverage AI to automate workflows and embed intelligent systems into architectural processes for cutting-edge outcomes.Future-Ready Expertise
Stay competitive in a rapidly evolving field by gaining expertise in AI-driven architectural innovation and automation.Data-Driven Strategy
Use AI models to analyze spatial and operational data, forecast trends, and guide design decisions with precision.Leadership in AI Architecture
Equip yourself to lead AI transformation in architecture, positioning yourself at the forefront of industry advancement.
Who Should Enroll?
Architecture Professionals
Upgrade your design capabilities by integrating AI to build intelligent, scalable, and future-ready architectural systems.Systems Architects & Engineers
Master AI techniques to design adaptive infrastructures, automate processes, and support enterprise-grade system evolution.IT Infrastructure Managers
Leverage AI to streamline deployment, optimize resources, and ensure agile integration across complex ecosystems.Business & Technology Leaders
Drive digital transformation by embedding AI into architectural planning, improving performance, scalability, and innovation outcomes.Students & Emerging Professionals
Build a strong foundation in AI architecture to stand out in today’s competitive job market and lead tomorrow’s innovations.
- AutoGluon
- ChatGPT
- SonarCube
- Vertex AI
Prerequisites
Basic Understanding of Neural Networks: Familiarity with core concepts, architecture, and how neural networks are optimized for real-world applications.
Model Evaluation Skills: Ability to assess AI models using key performance metrics to ensure precision and reliability.
Interest in AI Infrastructure: Openness to learning how AI systems are deployed and maintained in practical environments.
Exam Blueprint
- Fundamentals of Neural Networks – 10%
- Neural Network Optimization – 10%
- Neural Network Architectures for NLP – 10%
- Neural Network Architectures for Computer Vision – 10%
- Model Evaluation and Performance Metrics – 10%
- AI Infrastructure and Deployment – 10%
- AI Ethics and Responsible AI Design – 10%
- Generative AI Models – 10%
- Research-Based AI Design – 10%
- Capstone Project and Course Review – 10%
Frequently Asked Questions
What is the duration of the AI Plus Architect certification course
The course includes forty hours of instruction, available as a five-day intensive live program or a self-paced learning format with the same content.
What will I learn in the AI Plus Architect certification
You will gain expertise in neural network optimization, architecture design for natural language processing and computer vision, AI deployment infrastructure, generative AI, ethical AI practices, and performance evaluation. The course concludes with a capstone project focused on building and deploying a production-ready AI solution.
Who should enroll in this course
This program is designed for AI architects, engineers, developers, and professionals in technology roles who want to build and lead scalable AI systems.
Do I need prior experience to enroll in this course
While no formal experience is required, it is recommended that learners have a basic understanding of neural networks, AI concepts, and model evaluation techniques.
What is the outcome after completing the AI Plus Architect certification
After completing the course and successfully passing the final exam, participants will receive a globally recognized certification. The capstone project further demonstrates their ability to design and implement real-world AI solutions.
