AI+ Architect™

AI+ Architect™ - eLearning (exam included)

The AI+ Architect Certification is an advanced program designed for cloud architects, providing a deep dive into Artificial Intelligence (AI) and its practical implementations. The curriculum begins with core neural network principles and progresses to advanced topics such as optimization, hyperparameter tuning, and regularization. Learners work with AI architectures including Recurrent Neural Networks (RNNs), Long Short-Term Memory networks (LSTMs), Transformers, and Convolutional Neural Networks (CNNs), applying them in Natural Language Processing (NLP) and computer vision projects.

The program also addresses AI infrastructure, deployment strategies, and ethical considerations to ensure responsible AI development. Through a capstone project, participants showcase their ability to tackle architectural challenges using AI, equipping them to lead in technology-driven environments with greater precision, efficiency, and innovation.

Envision the Future: Neural Networks for Vision

• Advanced AI Mastery: Explore neural networks, NLP, and computer vision frameworks.
• Enterprise-Scale AI: Learn to develop scalable AI systems with real-world applications.
• Capstone Experience: Design, test, and deploy sophisticated AI architectures.
• Career-Ready Skills: Prepare for in-demand roles in AI system design and implementation.

Why This Certification Matters

• Optimize Architectural Design with AI: Apply AI tools to enhance design efficiency, scalability, and performance.

• Integrate AI into Projects: Embed innovative AI solutions and automate workflows within architectural projects.

• Lead in AI-Driven Innovation: Stay ahead as AI transforms architecture, gaining cutting-edge expertise.

• Data-Driven Decision Making: Use AI models to analyze architectural data, forecast trends, and guide strategic choices.

• Advance Your Career: Acquire skills to lead AI initiatives in the evolving field of architecture.

Industry Growth: Driving scalable, intelligent architectural solutions

• The global AI in architecture market is expected to grow at a CAGR of 38.6% from 2021 to 2028.
• AI-powered design and automation are transforming construction, real estate, and urban planning, improving sustainability.
• Increasing adoption of AI for predictive design, virtual simulations, and smart building management.
• AI innovations are reshaping construction and smart city planning, enhancing energy efficiency and urban development.
• Rising demand for AI-enhanced architecture across commercial real estate, infrastructure, and urban projects.

Key Features

• Course and material in English 
• Advanced level  (Category: AI+ Technical)
• 1 year access to the platform 24/7
• 40 hours of video lessons & multimedia resources

• 50 hours of study time recommendation 
• Quizzes, Assessments, and Course Resources
• Online Proctored Exam with One Free Retake

• Certification of completion included valid for 1 year

• Virtual Hands-on Lab included
• Tools You’ll Master: AutoGluon, ChatGPT, SonarCube, Vertex AI

Learning Outcomes

• End-to-End AI Development: Design complete AI pipelines, from data preprocessing and model building to deployment, ensuring integration with infrastructure and scalability.
• Advanced Neural Networks: Implement complex neural network architectures using frameworks like TensorFlow and PyTorch for NLP and computer vision applications.
• AI Research & Innovation: Apply cutting-edge AI research and design strategies to address gaps and stay ahead in the evolving AI landscape.
• Generative AI Techniques: Explore generative AI models and their applications in creative industries, research, and automated system design.

Target Audience

• Architecture Professionals: Integrate AI for smarter, scalable designs.
• Systems Architects & Engineers: Use AI to build advanced, automated infrastructures.
• IT Infrastructure Managers: Optimize planning and deployment with AI.
• Business Leaders: Drive transformation with AI-powered solutions.
• Students & Graduates: Gain an edge with AI architecture skills.

Prerequisites

• Basic understanding of neural networks, including their structure and optimization for practical applications.
• Ability to assess model performance using different metrics to ensure accuracy and reliability.
• Interest in learning about AI infrastructure and deployment to effectively implement and maintain AI systems.

Exam Details

• Duration: 90 minutes
• Passing :70% (35/50)
• Format: 50 multiple-choice/multiple-response questions
• Delivery Method: Online via proctored exam platform (flexible scheduling)
• Language: English

Course Content

Module 1: Fundamentals of Neural Networks

1.1 Introduction to Neural Networks

1.2 Neural Network Architecture

1.3 Hands-on: Implement a Basic Neural Network

Module 2: Neural Network Optimization

2.1 Hyperparameter Tuning

2.2 Optimization Algorithms

2.3 Regularization Techniques

2.4 Hands-on: Hyperparameter Tuning and Optimization

Module 3: Neural Network Architectures for NLP

3.1 Key NLP Concepts

3.2 NLP-Specific Architectures

3.3 Hands-on: Implementing an NLP Model

Module 4: Neural Network Architectures for Computer Vision

4.1 Key Computer Vision Concepts

4.2 Computer Vision-Specific Architectures

4.3 Hands-on: Building a Computer Vision Model

Module 5: Model Evaluation and Performance Metrics

5.1 Model Evaluation Techniques

5.2 Improving Model Performance

5.3 Hands-on: Evaluating and Optimizing AI Models

Module 6: AI Infrastructure and Deployment

6.1 Infrastructure for AI Development

6.2 Deployment Strategies

6.3 Hands-on: Deploying an AI Model

Module 7: AI Ethics and Responsible AI Design

7.1 Ethical Considerations in AI

7.2 Best Practices for Responsible AI Design

7.3 Hands-on: Analyzing Ethical Considerations in AI

Module 8: Generative AI Models

8.1 Overview of Generative AI Models

8.2 Generative AI Applications in Various Domains

8.3 Hands-on: Exploring Generative AI Models

Module 9: Research-Based AI Design

9.1 AI Research Techniques

9.2 Cutting-Edge AI Design

9.3 Hands-on: Analyzing AI Research Papers

Module 10: Capstone Project and Course Review

10.1 Capstone Project Presentation

10.2 Course Review and Future Directions

10.3 Hands-on: Capstone Project Development

Optional Module: AI Agents for Architect

1. Understanding AI Agents
2. Case Studies
3. Hands-On Practice with AI Agents

Licensing and accreditation

This course is offered by AVC according to Partner Program Agreement and complies with the License Agreement requirements. 

Equity Policy

AVC does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.

FAQ

What will I learn in the AI+ Architect certification?
You will gain expertise in advanced neural network techniques, model optimization, NLP and computer vision architectures, AI deployment, and ethical AI design principles.

Who should enroll in this course?
Ideal for AI architects, engineers, software developers, and professionals aiming to master AI architectures and neural network applications.

Do I need prior experience to enroll in the AI+ Architect course?
A basic understanding of AI and neural networks is recommended but not mandatory, as the course begins with core concepts.

What is the outcome after completing the AI+ Architect certification?
Participants will acquire both theoretical and practical skills to design, optimize, and deploy AI architectures effectively.

Recertification Requirements
AI+ Technical courses require recertification every year to keep your certification valid. Notifications will be sent three months before the due date

How Can AVC Help Foster an AI-Ready Culture?
While AI offers significant advantages, many organizations struggle with challenges like talent gaps, complex data environments, and system integration barriers. At AVC, we understand these obstacles and have tailored our certification programs to help businesses overcome them effectively.

Our strategic approach focuses on building a culture that embraces AI adoption and innovation. Through our industry-recognized certifications and in-depth training, we equip your workforce with the skills and knowledge needed to lead your organization confidently into an AI-powered future.

Customized for Impact: Our programs aren't one-size-fits-all. We offer specialized training designed by industry experts to equip your workforce with the specific skills and knowledge needed for critical AI roles.

Practical, Real-World Learning: We prioritize hands-on experience over theory, using real-world projects and case studies. This approach ensures your team gains the confidence and capability to implement AI solutions effectively, driving innovation and measurable business outcomes.