Data and Artificial Intelligence (AI) skills are some of the most sought-after in today’s workplace. From predictive analytics to customer service automation, employers need people who can understand data and apply AI tools effectively. For career changers, job seekers, or IT professionals looking to progress, qualifications in this area provide a direct route into exciting, high-growth roles.
According to CompTIA’s 2025 Job Seeker Trends research, earning a technical, industry-recognised certification is the number one strategy for pursuing a career in technology. Data and AI are among the most in-demand specialisms, and the right qualifications can help you stand out in a competitive market.
So, what qualifications should you pursue if you want to start or progress in Data and AI? This guide uses the CompTIA IT Certification Roadmap as a reference, alongside NILC’s own course offerings, to provide a clear career pathway.
Why Choose a Career in Data and AI?
Data and AI roles are not just in the tech industry. CompTIA reports that 41% of technology jobs are now outside traditional tech companies – in healthcare, finance, retail, manufacturing, and even government. This means that skills in data and AI can take you virtually anywhere.
Typical roles include:
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Data Analyst
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Business Intelligence Specialist
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AI Engineer
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Data Scientist
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Machine Learning Engineer
Step 1: Beginner-Level Qualifications
If you’re new to technology, the first step is to build strong digital foundations.
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CompTIA Tech+ – A new entry-level qualification that introduces IT and technology concepts, including data fundamentals and digital fluency.
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CompTIA A+ – The industry standard for IT support, giving you a baseline understanding of systems and troubleshooting.
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CompTIA Project+ – A foundation in project management, useful for data and AI projects where teamwork and planning are key.
At this stage, the goal is to understand how technology works and where data fits into everyday business.
Step 2: Intermediate Data-Focused Qualifications
Next, you can build practical data skills that prepare you for real-world analysis.
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CompTIA Data+ – Focused on collecting, analysing, and reporting data accurately, this qualification is perfect for aspiring data analysts.
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CompTIA DataSys+ – Designed for those managing databases and information storage.
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Microsoft Certified: Designing and Implementing an Azure AI Solution (AI-102) – Teaches you how to apply AI models in natural language, vision, and conversational AI scenarios.
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Microsoft Certified: Azure Data Scientist Associate (DP-100) – Focuses on machine learning and predictive analytics within Azure.
Many NILC learners choose Data+ as their first data-specific qualification, as it provides a strong grounding before progressing into AI.
Step 3: Advanced Qualifications in AI
At this level, you’ll be moving beyond analysis into designing and implementing AI-driven solutions.
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AWS Certified Machine Learning – Associate – Focuses on building and deploying machine learning models in Amazon Web Services.
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Google Professional Data Engineer – Covers designing and operationalising data pipelines with AI-driven insights.
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Microsoft Certified: Azure Solutions Architect Expert – (AZ-305) – A broader certification that includes advanced AI solution design within enterprise systems.
Step 4: Expert-Level Recognition
For those aiming for leadership or highly specialised technical roles, expert-level certifications demonstrate mastery.
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CompTIA DataX – CompTIA’s advanced-level data certification covering data engineering and machine learning (expected to become increasingly important).
A Typical Learning Pathway
Here’s an example progression you could follow:
1. Foundations
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CompTIA Tech+ or A+
2. Data Analysis
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CompTIA Data+
3. Databases/Applied AI
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CompTIA DataSys+
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Microsoft Azure AI Engineer Associate
4. Advanced/Expert AI/ML
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CompTIA DataX
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AWS Machine Learning Associate
Pathway Diagram
Career Outlook
With 89% of workers rating digital fluency as critical to career success, the demand for data and AI professionals will only grow. Certifications remain the clearest way to show employers that you have the knowledge and practical skills to deliver value from day one.
Start Your Data and AI Career with NILC
A career in Data and AI offers exciting, future-focused opportunities. With the right qualifications, you can move from entry-level data analysis into advanced AI engineering, with options across multiple industries.
The key is to follow a structured learning pathway: start with digital foundations, move into data analysis, specialise in AI applications, and then pursue expert-level certifications. Along the way, practical experience combined with recognised qualifications will give you the strongest advantage.
Funding opportunities, such as the Personal Learning Account (PLA) scheme, can cover the cost of many NILC’s Data and AI courses. Check our PLA page to see if you’re eligible.
At NILC, we provide flexible virtual and classroom-based training for all stages of the Data and AI journey. Whether you are starting with CompTIA Tech+ or preparing for more advanced certifications like Data+ or DataSys+, our courses are designed to fit around your work and life commitments.
If you’re ready to take the next step, explore NILC’s Data and AI training courses today.
