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AI+ Architect Practitioner™

AI+ Architect Practitioner™
  • 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
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Certificate Code

AT-320

Exam Format

AI-Driven Remote Exam Proctoring

Course Overview

Important details and certification information

Instructor-led OR Self-paced course + Official exam + Digital badge
Instructor-Led: 3 Days (live or virtual)
key concepts in both artificial intelligence, Fundamental understanding of computer science, Familiarity with cloud computing platforms like AWS, Azure, or GCP
50 questions, 70% passing, 90 minutes, online proctored exam

Certification Modules

  1. Course Introduction Preview

  1. 1.1 Introduction to Neural Networks
  2. 1.2 Neural Network Architecture
  3. 1.3 Hands-on: Implement a Basic Neural Network

  1. 2.1 Hyperparameter Tuning
  2. 2.2 Optimization Algorithms
  3. 2.3 Regularization Techniques
  4. 2.4 Hands-on: Hyperparameter Tuning and Optimization

  1. 3.1 Key NLP Concepts
  2. 3.2 NLP-Specific Architectures
  3. 3.3 Hands-on: Implementing an NLP Model

  1. 4.1 Key Computer Vision Concepts
  2. 4.2 Computer Vision-Specific Architectures
  3. 4.3 Hands-on: Building a Computer Vision Model

  1. 5.1 Model Evaluation Techniques
  2. 5.2 Improving Model Performance
  3. 5.3 Hands-on: Evaluating and Optimizing AI Models

  1. 6.1 Infrastructure for AI Development
  2. 6.2 Deployment Strategies
  3. 6.3 Hands-on: Deploying an AI Model

  1. 7.1 Ethical Considerations in AI
  2. 7.2 Best Practices for Responsible AI Design
  3. 7.3 Hands-on: Analyzing Ethical Considerations in AI

  1. 8.1 Overview of Generative AI Models
  2. 8.2 Generative AI Applications in Various Domains
  3. 8.3 Hands-on: Exploring Generative AI Models

  1. 9.1 AI Research Techniques
  2. 9.2 Cutting-Edge AI Design
  3. 9.3 Hands-on: Analyzing AI Research Papers

  1. 10.1 Capstone Project Presentation
  2. 10.2 Course Review and Future Directions
  3. 10.3 Hands-on: Capstone Project Development

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

AI Tools Covered

AutoGluon
ChatGPT
SonarCube
Vertex AI
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