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Programme Detail

CompTIA DataX / DataAI

This programme develops advanced data-science and AI capabilities spanning business problem analysis, data preparation, machine learning, deep learning, deployment, and...

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Advanced Data and AIRegistration Open

Programme overview

This programme develops advanced data-science and AI capabilities spanning business problem analysis, data preparation, machine learning, deep learning, deployment, and business impact. Learners progress from core concepts to practical application through guided examples, scenarios, exercises, and structured review aligned with the Trainocate course curriculum.

Programmes can be delivered via

HRD Corp Claimable

Yayasan Peneraju aligned

CompTIA

At a glance

Course code: C-015
Provider: CompTIA
Category: Advanced Data and AI
Status: Registration Open
Duration: 5 days
Price: RM 4,500

What participants should gain

Analyze complex enterprise requirements, threats, risks, and architectural trade-offs
Design and evaluate advanced technical or governance solutions
Integrate security, resilience, automation, and operational controls
Communicate defensible recommendations to technical and business stakeholders
Prepare for the corresponding advanced CompTIA certification objectives

Participant readiness

Strong practical experience in the relevant technical domain is recommended
Learners should be comfortable analyzing enterprise-level scenarios and making risk-based decisions

Who this course is for

Experienced data scientists and analysts
Machine-learning and AI practitioners
Technical professionals preparing for CompTIA DataAI

How the course is delivered

This programme will be conducted through interactive lectures, demonstrations, guided hands-on exercises, scenario-based activities, troubleshooting practice, group discussions, knowledge checks, and a final course review aligned with the stated CompTIA objectives.

This programme will be conducted through interactive lectures, demonstrations, guided hands-on exercises, scenario-based activities, troubleshooting practice, group discussions, knowledge checks, and a final course review aligned with the stated CompTIA objectives | By enquiry

Course outline

Module and topic breakdown

Module 1: Illustrating the Data Science Lifecycle

Business understanding, data work, modeling, deployment, and monitoring

Module 2: Analyzing Business Problems

Problem framing, stakeholders, value, constraints, and success metrics

Module 3: Collecting Data

Sources, acquisition methods, permissions, and sampling

Module 4: Cleaning and Preparing Data

Missing data, outliers, duplicates, and transformations

Module 5: Describing Data Features

Data types, distributions, relationships, and feature characteristics

Module 6: Exploring Data

Exploratory statistics and visualization

Module 7: Navigating the Model Selection Process

Problem types, algorithms, baselines, and trade-offs

Module 8: Employing Machine Learning Methods

Supervised and unsupervised learning

Module 9: Experimenting with Deep Learning

Neural network concepts, architectures, and use cases

Module 10: Evaluating and Refining Data Models

Performance, fairness, robustness, and error analysis

Module 11: Communicating for Business Impact

Visualizations, narratives, recommendations, and limitations

Module 12: Deploying Data Models

Packaging, integration, release, and operationalization

Module 13: Discovering Specialized Data Science Applications

Natural language, computer vision, forecasting, and recommendation

Assessment and completion

Continuous knowledge checks and facilitator feedback throughout the programme
Completion of guided exercises, scenarios, labs, or case-study activities applicable to the course
Final review or practical activity to confirm understanding of the stated course objectives
Official CompTIA examination and certification requirements depend on the selected training package and current exam version

Availability

This programme has a public intake path. Use the enquiry form below to confirm the next available session or a private cohort.

Programme enquiry

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