A certification that keeps pace
with the evolution of Artificial Intelligence
Generative Artificial Intelligence is transforming how we work, communicate, learn and innovate.
If you aim to understand the technology, apply AI tools in your professional context, and validate your knowledge through a certification developed by a leading organization, now is the time to take the next step.
12+
Core topics, spanning AI foundations, ethics, security, multimodal models and AI agents.
LLMs
Governance
Why the certification
evolved
evolved
A changing technology
A more demanding market
Responsible use
What sets the
programme apart
The focus goes beyond theory and brings the certification closer to real professional contexts. Its structure provides the conceptual grounding to understand the technology and the practical breadth to apply it with confidence.
Tecnologia em mudança
- Foundations of Artificial Intelligence and Generative AI.
- Large Language Models, prompt engineering and AI agents.
- Multimodal models, process automation and productivity.
- Current AI tools, model limitations and bias.
- Ethics, security, privacy and AI governance.
Skills that translate into practice
Understand the core principles of Generative AI.
Explain how language models work.
Create more effective prompts for different objectives.
Identify opportunities for application across business areas.
Assess risks, limitations and responsible-use practices.
Who
it is for
it is for
Leadership profiles
Functional teams
Learning and transition
Benefits for
professionals
A certification helps structure knowledge, strengthen credibility and build confidence in the daily use of AI tools.
- Update skills in a fast-evolving field.
- Improve personal productivity and delivery quality.
- Build confidence using current tools and models.
- Explore new career opportunities.
Benefits for
organizations
For teams and companies, the certification works as a capability-building tool aligned with responsible digital transformation.
- Develop internal skills from a shared foundation.
- Accelerate AI adoption with less operational risk.
- Promote ethics, security and responsible use.
- Improve productivity and readiness for innovation.
How it works
1
Preparation
Study the content provided by DSPA through an autonomous, progressive learning approach.
2
Consolidation
Explore concepts, tools and practical applications to build transferable knowledge for real work.
Assessment and certification
Complete the assessment of acquired knowledge and receive certification upon approval.
Frequently asked questions
Develop skills
for the future of Artificial Intelligence
for the future of Artificial Intelligence
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