AI+ Architect™
AT-320
Visualize Tomorrow: Neural Networks in Vision- Deep AI Expertise: Covers neural networks, NLP, and computer vision frameworks
- Enterprise AI: Learn to design scalable AI systems for real-world impact
- Capstone Integration: Build, test, and deploy advanced AI architectures
- Industry Preparedness: Equips you for roles in high-demand AI design domains
Why This Certification Matters
At a Glance: Course + Exam Overview
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 30 hours of content
Who Should Enroll?
Architecture Professionals: Enhance your architectural design skills by integrating AI to create scalable, efficient, and intelligent systems for modern solutions.
Systems Architects & Engineers: Learn to leverage AI to design and build sophisticated, scalable infrastructures while automating key processes.
IT Infrastructure Managers: Use AI to optimize architecture planning, streamline infrastructure deployment, and ensure seamless system integration.
Business Leaders: Drive transformation within your organization by adopting AI-driven architectural solutions to enhance scalability, reduce costs.
Students & New Graduates: Gain a competitive edge in the tech industry by mastering AI architectural techniques and tools.
Job Roles & Industry Outlook
AI Architect
Specializes in designing AI models, neural networks, and intelligent systems for diverse applications, including NLP and computer vision.
AI Solutions Architect
Leads the integration of AI into complex systems, ensuring the deployment of scalable and efficient AI solutions across various platforms.
Cloud AI Architect
Designs and implements AI-powered cloud infrastructures, focusing on the seamless integration of AI models.
AI Research Scientist
Engages in the development of new AI models and architectures, conducting cutting-edge research.
AI System Integrator
Focuses on the implementation and integration of AI components into existing systems, ensuring that AI-driven solutions.
Industry Growth: Empowering Tech Leaders to Build Scalable, Smart Architectures
- The global AI in architecture market is projected to grow at a CAGR of 38.6% from 2021 to 2028 (Source: Grand View Research).
- AI-driven design and building automation are transforming industries like construction, real estate, and urban planning, enhancing sustainability.
- The adoption of AI in architecture is increasing, with professionals using AI for predictive design, virtual simulations, and smart building management.
- AI-powered technologies in architecture are revolutionizing construction and smart city planning, driving innovations in energy-efficient buildings, urban development.
- The demand for AI-enhanced architecture is rising across sectors like commercial real estate, urban development, and infrastructure.
Skills You’ll Gain
- Advanced Neural Network Design
- AI Model Evaluation & Performance Metrics
- Generative AI for Architecture
- AI Deployment & Infrastructure
- Machine Learning Optimization Shape
What You'll Learn
- Course Introduction
- 1.1 Introduction to Neural Networks
- 1.2 Neural Network Architecture
- 1.3 Hands-on: Implement a Basic Neural Network
- 2.1 Hyperparameter Tuning
- 2.2 Optimization Algorithms
- 2.3 Regularization Techniques
- 2.4 Hands-on: Hyperparameter Tuning and Optimization
- 3.1 Key NLP Concepts
- 3.2 NLP-Specific Architectures
- 3.3 Hands-on: Implementing an NLP Model
- 4.1 Key Computer Vision Concepts
- 4.2 Computer Vision-Specific Architectures
- 4.3 Hands-on: Building a Computer Vision Model
- 5.1 Model Evaluation Techniques
- 5.2 Improving Model Performance
- 5.3 Hands-on: Evaluating and Optimizing AI Models
- 6.1 Infrastructure for AI Development
- 6.2 Deployment Strategies
- 6.3 Hands-on: Deploying an AI Model
- 7.1 Ethical Considerations in AI
- 7.2 Best Practices for Responsible AI Design
- 7.3 Hands-on: Analyzing Ethical Considerations in AI
- 8.1 Overview of Generative AI Models
- 8.2 Generative AI Applications in Various Domains
- 8.3 Hands-on: Exploring Generative AI Models
- 9.1 AI Research Techniques
- 9.2 Cutting-Edge AI Design
- 9.3 Hands-on: Analyzing AI Research Papers
- 10.1 Capstone Project Presentation
- 10.2 Course Review and Future Directions
- 10.3 Hands-on: Capstone Project Development
Tools You’ll Master
AutoGluon
ChatGPT
SonarCube
Vertex AI
Prerequisites
- A foundational knowledge on neural networks, including their optimization 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.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via proctored exam platform (flexible scheduling)
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%
Choose the Format That Fits Your Schedule
What’s Included (One-Year Subscription + All Updates):
- 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
Instructor-Led (Live Virtual/Classroom)
- 5 days of intensive training with live demos
- Real-time Q&A, peer collaboration, and hands-on labs
- Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
- ~30 hours of on-demand video lessons, e-book, podcasts, and interactive labs
- Learn anywhere, anytime, with modular quizzes to track progress
Trusted LinkedIn Reviews Posted by Our Learners
Isi Idemudia
Global Responsible AI Advisor |Ex-Accenture|Adjunct Professor | Published AuthorI am officially an AI+ Architect™ ! Equipped to lead in the era of innovation and technology! Russell Sarder https://lnkd.in/gaEj5iTU
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Get CertifiedFrequently Asked Questions
The certification lasts 40 hours, typically completed over 5 days, providing an intensive learning experience.
You will learn advanced neural network techniques, model optimization, NLP and computer vision architectures, AI deployment infrastructure, and ethical AI design.
This course is ideal for AI architects, engineers, software developers, and professionals seeking to master AI architectures and neural networks.
A foundational understanding of AI and neural networks is recommended but not required, as the course starts with core concepts.
Participants will be equipped with both theoretical and practical knowledge to design, optimize, and implement AI architectures.
