AI+ Architect™

Visualize Tomorrow: Neural Networks in Vision

Certificate Code: AT-320

About This Course

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

Certificate Overview

Included

Instructor-led OR Self-paced course + Official exam + Digital badge

Duration

Instructor-Led: 5 days (live or virtual)
Self-Paced: 40 hours of content

Prerequisites

key concepts in both artificial intelligence, Fundamental understanding of computer science, Familiarity with cloud computing platforms like AWS, Azure, or GCP

Exam Format

50 questions, 70% passing, 90 minutes, online proctored exam

Course Modules

Certification Overview

Course Introduction Preview

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

Course