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Part of the Data Intelligence Architect Pathway

Certified Data Intelligence Specialist

AI & Machine Learning

AI as an integrating capability applied to data intelligence -- the mandatory AI-capability pillar of the Data Intelligence Architect designation.

About 570 hours of real coursework

Enroll in this Pathway
The Credential

Certified Data Intelligence Specialist — AI & Machine Learning

Finishing every course is not what earns this credential. You earn it by demonstrating all 16 required competencies through real, assessed evidence, then bringing them together in the Project below — reviewed end to end, not graded on attendance.

Artificial Intelligence and Intelligent Systems

  • AI Fundamentals
  • AI System Architecture & Deployment
  • LLMOps & AI Infrastructure at Scale
  • Reinforcement Learning
  • Multimodal & Generative AI
  • Reinforcement Learning from Human Feedback
  • Generative AI Systems Design
  • Applied AI Research Methods
  • Computer Vision Engineering
  • Natural Language Processing
  • Data Engineering for AI/ML
  • Large Language Models
  • AI Application Integration & Deployment
  • AI Agent Systems
  • MLOps & Production ML Systems
  • AI Safety, Ethics & Governance
Term 1 of 3

Fundamentals

Build the essential knowledge and skills this specialisation is founded on.

"Build a rigorous foundation in how neural networks learn — from perceptrons through backpropagation and regularization."

Included Modules
Perceptrons & Activation Functions
Backpropagation & Gradient Descent
Loss Functions & Optimization
Overfitting & Regularization
Model Evaluation Metrics
TensorFlow/PyTorch Framework Depth
GPU Training Concepts
Batch Normalization
Dropout & Regularization Strategies
Hyperparameter Tuning Methods

"Engineer computer vision systems using convolutional neural networks, transfer learning, and object detection."

Included Modules
Convolutional Neural Networks (CNNs)
Image Preprocessing Techniques
Transfer Learning
Object Detection Concepts
Model Accuracy Optimization

"Process and understand text using embeddings and transformer architectures for real NLP tasks."

Included Modules
Text Preprocessing & Tokenization
Word Embeddings
Recurrent & Transformer Architectures
Sentiment Analysis
Sequence Classification

"Build the mathematical intuition behind machine learning so models are understood, not just invoked."

Included Modules
Linear Algebra for ML
Calculus & Gradients
Probability & Statistics for ML
Optimization Theory

"Engineer the data pipelines and feature workflows that determine whether AI systems succeed."

Included Modules
Data Pipelines for ML
Feature Engineering at Scale
Data Labeling & Annotation
Handling Imbalanced & Biased Data

"Master the classical machine learning methods that remain the right tool for most real-world problems."

Included Modules
Tree-Based Models & Ensembles
Support Vector Machines
Clustering & Dimensionality Reduction
Model Selection & Validation
When Classical Beats Deep Learning

Professional Competencies

Coming soon.

Industry Tools

Coming soon.

Term 2 of 3

Applied

Turn that knowledge into practical capability on realistic, guided work.

"Understand how LLMs work and how to extend them with Retrieval-Augmented Generation and fine-tuning."

Included Modules
Transformer Architecture Overview
Prompt Engineering Frameworks
Context Windows & Token Management
Retrieval-Augmented Generation (RAG)
Fine-Tuning Fundamentals
Vector Databases (Concept & Integration)
RAG Architecture Design Depth
Fine-Tuning vs Prompt Tuning Comparison
Enterprise AI Governance

"Integrate LLMs into real applications using the OpenAI API: embeddings, function calling, and safety guardrails."

Included Modules
API-Based Model Interaction
Embeddings & Semantic Search
Function Calling & Tool Integration
Structured Output Control
Guardrails & AI Safety Practices

"Design AI agents using LangChain: memory, multi-step reasoning, and tool use over private enterprise data."

Included Modules
Agent Architecture
Memory Systems
Multi-Step Reasoning Chains
Tool-Using Agents
Private Data Integration
Vector Database Concepts

"Build complete AI-powered applications, integrating models into reliable, user-facing production systems."

Included Modules
AI Application Architecture
Integrating Models into Products
Handling Latency & Reliability
Cost & Token Management
Evaluation & Quality Assurance for AI

Professional Competencies

Coming soon.

Industry Tools

Coming soon.

Term 3 of 3

Professional

Perform at the depth and independence expected of a working specialist.

"Apply MLOps discipline — versioning, CI/CD, and drift detection — to keep ML systems reliable in production."

Included Modules
Model Versioning
Experiment Tracking
Data Version Control
CI/CD for ML Pipelines
Reproducible Training Environments
Model Registry Management
Drift Detection & Retraining Automation

"Deploy ML models as containerized services and monitor their performance and drift in production."

Included Modules
Model Serialization & APIs
Containerized ML Services
Performance Monitoring
Drift Detection
Automated Retraining Strategies

"Architect scalable, secure AI systems with responsible governance and cost-aware infrastructure decisions."

Included Modules
Scalable Inference Systems
GPU/CPU Optimization Concepts
Security for AI Systems
Responsible AI & Governance
Cost Optimization Strategies

"Operationalize AI safety, fairness, and governance so deployed systems are trustworthy and accountable."

Included Modules
Fairness & Bias Mitigation
Model Explainability (XAI)
AI Governance Frameworks
Privacy-Preserving ML

"Optimize and scale AI systems through model compression, distributed training, and inference efficiency."

Included Modules
Model Compression & Quantization
Distributed Training
Inference Optimization
GPU & Accelerator Economics

"Operationalize large language model systems with the specialized infrastructure, evaluation, and monitoring they demand."

Included Modules
LLMOps Lifecycle
LLM Evaluation Frameworks
Prompt & Version Management
Monitoring LLMs in Production

Professional Competencies

Coming soon.

Industry Tools

Coming soon.

The Project

ML/AI Portfolio Project

Independent specialization capstone -- demonstrates the AIDI specialization's own competencies. Earned completely independently of any other DIA-Advance specialization.

  1. 1

    Execute

    ML/AI Portfolio Project

  2. 2

    Specialization Track 1

    Applied AI/ML Research & Advanced Generative Systems portfolio project

Ready to Start?

This program is part of the Data Intelligence Architect — Specialize Pathway. You'll pick your starting cohort for Certified Data Intelligence Specialist — AI & Machine Learning — the first program in the pathway — on the next step.

Reserve Your Spot