CompTIA DataAI

The CompTIA DataAI course is designed for experienced data professionals who want to develop advanced skills in artificial intelligence, machine learning and data science.

As organisations increasingly adopt AI technologies, demand is growing for professionals who can work with complex data, develop reliable models, and turn analytical results into meaningful business insights.

This course provides the practical knowledge and techniques required to bridge the gap between traditional data analysis and modern AI-driven solutions. It covers the complete data science lifecycle, including defining business problems, collecting and preparing data, exploratory analysis, model selection, machine learning, deep learning, model evaluation, deployment and communicating results.

Delegates will learn how to apply mathematical and statistical methods, select appropriate analysis and modelling techniques, develop machine learning solutions and make justified model recommendations.

The course also explores specialised applications of data science, including natural language processing, computer vision, anomaly detection, fraud detection, reinforcement learning and multimodal machine learning.

CompTIA DataAI is a vendor-neutral certification that validates the advanced knowledge and practical skills required to design, develop, evaluate and manage data-driven solutions throughout the complete data lifecycle.

Please note: the CompTIA DataAI syllabus includes additional content and laboratory exercises beyond those that can be completed during the instructor-led course. Delegates should be prepared to undertake independent study and complete additional laboratory work in their own time.

Target Audience

• Experienced Data Scientists
• Senior Data Analysts
• Machine Learning Engineers
• AI and Machine Learning Specialists
• Data Science Consultants
• Data Modellers
• Statistical Modellers
• Analytics Professionals
• Data Engineers moving into advanced modelling roles
• MLOps Professionals
• Technical Professionals responsible for deploying and monitoring data models
• Professionals who design, develop or manage AI-driven data solutions
• Experienced data professionals seeking a vendor-neutral certification

By the End of This Course, You Will Be Able To:

• Understand and apply the complete data science lifecycle
• Translate business problems into appropriate data science activities
• Collect data from suitable internal and external sources
• Clean, prepare, transform and enrich complex datasets
• Apply appropriate mathematical and statistical methods
• Understand probability, statistical modelling, linear algebra and calculus concepts
• Perform exploratory data analysis to identify patterns, relationships and anomalies
• Recognise and address common data quality and modelling issues
• Select appropriate analysis and modelling techniques
• Design and iterate data models based on business and technical requirements
• Apply supervised and unsupervised machine learning methods
• Understand and apply foundational deep learning concepts
• Evaluate models using appropriate statistical and performance measures
• Identify and address overfitting, underfitting, bias and variance
• Refine models through feature selection and hyperparameter tuning
• Make justified model recommendations based on experimental results
• Communicate analytical findings to technical and non-technical stakeholders
• Produce effective, accessible and accurate data visualisations and reports
• Deploy models within cloud, cluster, hybrid, edge and on-premises environments
• Monitor model performance and recognise model or data drift
• Understand specialised applications such as natural language processing and computer vision
• Support informed, data-driven business decisions
• Prepare confidently for the CompTIA DataAI DY0-001 examination

The CompTIA DataAI course is designed for experienced data professionals who want to develop advanced skills in artificial intelligence, machine learning and data science.

As organisations increasingly adopt AI technologies, demand is growing for professionals who can work with complex data, develop reliable models, and turn analytical results into meaningful business insights.

This course provides the practical knowledge and techniques required to bridge the gap between traditional data analysis and modern AI-driven solutions. It covers the complete data science lifecycle, including defining business problems, collecting and preparing data, exploratory analysis, model selection, machine learning, deep learning, model evaluation, deployment and communicating results.

Delegates will learn how to apply mathematical and statistical methods, select appropriate analysis and modelling techniques, develop machine learning solutions and make justified model recommendations.

The course also explores specialised applications of data science, including natural language processing, computer vision, anomaly detection, fraud detection, reinforcement learning and multimodal machine learning.

CompTIA DataAI is a vendor-neutral certification that validates the advanced knowledge and practical skills required to design, develop, evaluate and manage data-driven solutions throughout the complete data lifecycle.

Please note: the CompTIA DataAI syllabus includes additional content and laboratory exercises beyond those that can be completed during the instructor-led course. Delegates should be prepared to undertake independent study and complete additional laboratory work in their own time.

Target Audience

• Experienced Data Scientists
• Senior Data Analysts
• Machine Learning Engineers
• AI and Machine Learning Specialists
• Data Science Consultants
• Data Modellers
• Statistical Modellers
• Analytics Professionals
• Data Engineers moving into advanced modelling roles
• MLOps Professionals
• Technical Professionals responsible for deploying and monitoring data models
• Professionals who design, develop or manage AI-driven data solutions
• Experienced data professionals seeking a vendor-neutral certification

By the End of This Course, You Will Be Able To:

• Understand and apply the complete data science lifecycle
• Translate business problems into appropriate data science activities
• Collect data from suitable internal and external sources
• Clean, prepare, transform and enrich complex datasets
• Apply appropriate mathematical and statistical methods
• Understand probability, statistical modelling, linear algebra and calculus concepts
• Perform exploratory data analysis to identify patterns, relationships and anomalies
• Recognise and address common data quality and modelling issues
• Select appropriate analysis and modelling techniques
• Design and iterate data models based on business and technical requirements
• Apply supervised and unsupervised machine learning methods
• Understand and apply foundational deep learning concepts
• Evaluate models using appropriate statistical and performance measures
• Identify and address overfitting, underfitting, bias and variance
• Refine models through feature selection and hyperparameter tuning
• Make justified model recommendations based on experimental results
• Communicate analytical findings to technical and non-technical stakeholders
• Produce effective, accessible and accurate data visualisations and reports
• Deploy models within cloud, cluster, hybrid, edge and on-premises environments
• Monitor model performance and recognise model or data drift
• Understand specialised applications such as natural language processing and computer vision
• Support informed, data-driven business decisions
• Prepare confidently for the CompTIA DataAI DY0-001 examination