AI+ Architect™ - eLearning (exam included)
448,00 EUR
- 40 hours
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.
Key Features
Language
Course and material in English
Level
Advanced level (Category: AI+ Technical)
1 year platform access
and Virtual Hands-on Lab included
40 hours of video lessons & multimedia
50 hours of study time recommendation
Material
Video, PDF Material, audio eBook, Podcasts, quizzes and assessments.
Exam
Online Proctored Exam with One Free Retake
Certificate
Certification of completion included. Valid for 1 year
Tools You’ll Master
AutoGluon, ChatGPT, SonarCube, Vertex AI
About the course
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.
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.
Why This Certification Matters
Apply AI tools to enhance design efficiency, scalability, and performance.
Learning Outcomes
At the end of this course, you will be able to:
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
Course timeline
Fundamentals of Neural Networks
Lesson 1
- 1.1 Introduction to Neural Networks
- 1.2 Neural Network Architecture
- 1.3 Hands-on: Implement a Basic Neural Network
Neural Network Optimization
Lesson 2
- 2.1 Hyperparameter Tuning
- 2.2 Optimization Algorithms
- 2.3 Regularization Techniques
- 2.4 Hands-on: Hyperparameter Tuning and Optimization
Neural Network Architectures for NLP
Lesson 3
- 3.1 Key NLP Concepts
- 3.2 NLP-Specific Architectures
- 3.3 Hands-on: Implementing an NLP Model
Neural Network Architectures for Computer Vision
Lesson 4
- 4.1 Key Computer Vision Concepts
- 4.2 Computer Vision-Specific Architectures
- 4.3 Hands-on: Building a Computer Vision Model
Model Evaluation and Performance Metrics
Lesson 5
- 5.1 Model Evaluation Techniques
- 5.2 Improving Model Performance
- 5.3 Hands-on: Evaluating and Optimizing AI Models
AI Infrastructure and Deployment
Lesson 6
- 6.1 Infrastructure for AI Development
- 6.2 Deployment Strategies
- 6.3 Hands-on: Deploying an AI Model
AI Ethics and Responsible AI Design
Lesson 7
- 7.1 Ethical Considerations in AI
- 7.2 Best Practices for Responsible AI Design
- 7.3 Hands-on: Analyzing Ethical Considerations in AI
Generative AI Models
Lesson 8
- 8.1 Overview of Generative AI Models
- 8.2 Generative AI Applications in Various Domains
- 8.3 Hands-on: Exploring Generative AI Models
Research-Based AI Design
Lesson 9
- 9.1 AI Research Techniques
- 9.2 Cutting-Edge AI Design
- 9.3 Hands-on: Analyzing AI Research Papers
Capstone Project and Course Review
Lesson 10
- 10.1 Capstone Project Presentation
- 10.2 Course Review and Future Directions
- 10.3 Hands-on: Capstone Project Development
AI Agents for Architect
Optional Module
- 1. Understanding AI Agents
- 2. Case Studies
- 3. Hands-On Practice with AI Agents
Who Should Enroll in this Program?
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.
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.
More Details
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
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.
Frequently Asked Questions
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