AI Apprentice to AI Architect

 Mode of delivery: 

Digital learning

  Subjects:
AI Architect Track 1: AI Apprentice
AI Architect Track 2: AI Developer
AI Architect Track 3: AI Practitioner
AI Architect Track 4: AI Architect

Subject breakdown
AI Architect Track 1: AI Apprentice
Artificial Intelligence: Basic AI Theory
Artificial Intelligence: Types of Artificial Intelligence
Artificial Intelligence: Human-computer Interaction Overview
Artificial Intelligence: Human-computer Interaction Methodologies
Python AI Development: Introduction
Python AI Development: Practice
Computer Vision: Introduction
Computer Vision: AI & Computer Vision
Cognitive Models: Overview of Cognitive Models
Cognitive Models: Approaches to Cognitive Learning
Final Exam: AI Apprentice

AI Architect Track 2: AI Developer
AI Framework Overview: AI Developer Role
AI Framework Overview: Development Frameworks
Working With Microsoft Cognitive Toolkit (CNTK)
Deep Learning Packages: Keras – a Neural Network Framework
Introducing Apache Spark for AI Development
Implementing AI With Amazon ML
Implementing AI Using Cognitive Modeling
Applying AI to Robotics
Working with Google BERT: Elements of BERT
Final Exam: AI Developer

AI Architect Track 3: AI Practitioner
The AI Practitioner: Role & Responsibilities
The AI Practitioner: Optimizing AI Solutions
The AI Practitioner: Tuning AI Solutions
Advanced Functionality of Microsoft Cognitive Toolkit (CNTK)
Working With the Keras Framework
Using Apache Spark for AI Development
Extending Amazon Machine Learning
Using Intelligent Information Systems in AI
Final Exam: AI Practitioner

AI Architect Track 4: AI Architect
Elements of an Artificial Intelligence Architect
AI Enterprise Planning
AI in Industry
Leveraging Reusable AI Architecture Patterns
Evaluating Current and Future AI Technologies and Frameworks
Explainable AI
Final Exam: AI Architect