Learning stage
Applied AI foundations
Understand what model APIs can do, where uncertainty appears and how to define a bounded use case.
SVEO Academy
AI & GenAI Development
Learn how AI-enabled features fit into applications, where they add value and how to build with appropriate controls.
Learning pathAI & GenAI Development
Tools exploredLLM APIs · JavaScript · Python
Project briefs3 connected projects
Current detailsContact SVEO AcademyWho it is for
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Developers curious about applied AI
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Learners with basic programming foundations
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Technology professionals exploring automation
Helpful foundations
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Basic JavaScript or Python familiarity
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Understanding of APIs is helpful
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Curiosity and a critical approach to AI output
Tools explored
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LLM APIs
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JavaScript
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Python
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Prompt workflows
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Vector search
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Git
Learning outline
From foundations to connected practice
The final sequence and delivery format may vary. Contact SVEO Academy for current admission and schedule details.
Learning stage
Prompt and context design
Structure instructions and relevant context so output can be reviewed against a clear purpose.
Learning stage
Knowledge workflows
Explore retrieval patterns that connect approved information to model-assisted experiences.
Learning stage
Evaluation and integration
Connect an AI feature to an application while considering privacy, cost, failure and human review.
Portfolio projects
Project briefs with a clear learning purpose
Projects connect several concepts and give learners something concrete to explain, review and improve.
Knowledge assistant
Answer questions using a limited, approved information set.
Demonstrates
Context, retrieval, citations and output review.
Assisted workflow
Reduce repetitive drafting or classification work.
Demonstrates
Prompt design, structured output and human oversight.
AI product feature
Embed a focused model capability in a web application.
Demonstrates
API integration, states, limits, evaluation and cost awareness.
Practice
Activities between projects
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Compare prompts against a simple evaluation set
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Connect a model API to a small application
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Identify sensitive data in an example workflow
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Design a human review step for uncertain output
Preparation
What learners should prepare
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Basic JavaScript or Python
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Understanding of APIs
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Access requirements confirmed before using any paid external model service
Learning checks
Ways to review progress
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Prompt and output comparisons
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Use-case and privacy review
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Project evaluation against defined examples
Learning outcomes
Capabilities to keep developing
The track is a foundation for continued practice. Outcomes describe capabilities learners can work toward, not employment guarantees.
01
Identify suitable AI use cases
02
Integrate model APIs
03
Evaluate output quality
04
Design human-aware AI workflows
Questions
About the AI & GenAI Development track
Is this a machine-learning research course?
No. It focuses on applied integration and product workflows rather than training foundation models.
Do I need advanced mathematics?
Advanced mathematics is not central to this applied track, but basic programming foundations are important.
Will learners need a paid AI API account?
That depends on the current programme setup. Confirm account, credit and data-handling requirements before participation.
How is model output evaluated?
Learners can define representative examples, quality criteria and human review steps rather than assuming fluent output is correct.
Next learning paths
Continue into connected skills
Start a conversation
Interested in AI & GenAI Development?
Contact SVEO Academy for current availability, learning format, admission steps and other programme details.