Generative AI Engineering & AI Agents Foundation Internship Program
Learn Generative AI. Build AI Agents. Create Your First AI Project.
About This Program
What if you could move beyond asking AI questions and start building applications that help solve real problems?
Welcome to the Generative AI Engineering & AI Agents Foundation Internship Program by VELYON AI Institute—your starting point for understanding how modern AI applications and AI agents work.
Generative AI is changing how people create content, analyse information, write code and automate workflows. But using an AI chatbot is only the beginning. The next step is learning how to connect AI models with instructions, knowledge sources, tools and structured workflows to build more useful applications.
This foundation-level program introduces you to the building blocks behind these systems. You will explore large language models (LLMs), prompt engineering, AI application design, tool calling, retrieval-augmented generation (RAG), agent workflows and responsible AI practices.
Your learning journey is built around missions
Instead of only reading theory, work through a structured progression of learning missions. Understand a concept, try it in practice, review your output and improve your solution.
Mission 1 — Understand the AI Engine
Explore generative AI, LLMs, tokens, context windows and the fundamentals behind AI-powered applications.
Mission 2 — Master the Prompt
Learn to write clearer instructions, structure outputs and evaluate AI responses.
Mission 3 — Give AI a Knowledge Base
Discover how retrieval-augmented generation can help applications use relevant information from documents and knowledge sources.
Mission 4 — Give AI Tools to Use
Understand how tool calling connects an AI model with functions, APIs or other capabilities.
Mission 5 — Build an Agent Workflow
Explore how an AI application can break a task into steps, use tools and coordinate a workflow under appropriate controls.
Mission 6 — Test, Improve and Present
Evaluate your project, identify weaknesses and prepare a clear demonstration of what you built.
Your final challenge
Apply what you learn to a small AI-powered project, such as a document Q&A assistant, a tool-using support assistant or a structured research workflow.
The objective is not to pretend you have mastered every part of AI engineering in one program. It is to build a solid foundation, understand the essential concepts and take your first practical steps toward developing AI-powered solutions.
Learn. Experiment. Build. Test. Level up.
Begin your journey into Generative AI Engineering and AI Agents with VELYON AI Institute.
What You'll Learn
- Understand the difference between generative AI, traditional automation and AI agents.
- Explain the basic concepts behind large language models and AI-powered applications.
- Write structured prompts with clear instructions, context and output formats.
- Use AI to generate, analyse and transform information while checking its limitations.
- Understand how tool calling connects models to functions and external services.
- Explore retrieval-augmented generation (RAG) and knowledge-grounded responses.
- Design simple multi-step AI workflows for practical use cases.
- Understand agent planning, task decomposition and workflow orchestration.
- Recognise hallucinations, prompt-injection risks and common failure modes.
- Apply basic testing, evaluation and responsible AI practices to a project.
- Plan, build and present a foundation-level AI application or agent prototype.
Program Content
Start your AI engineering journey by understanding generative AI, large language models, tokens, context windows and the basics of how AI applications produce responses. Explore real use cases, identify model limitations and complete your first AI experimentation mission.
Learn to write clearer instructions, provide useful context, specify output formats and refine prompts through testing. Explore structured outputs and simple evaluation methods to understand why some prompts work better than others.
Discover the building blocks of AI agents, including tool calling, retrieval-augmented generation (RAG), task decomposition and multi-step workflows. Understand how AI applications can retrieve relevant information and interact with tools, while learning why permissions, testing and human oversight matter.
Bring your learning together in a foundation-level project. Choose a suitable use case, outline the workflow, build or prototype the solution using the tools provided in the program, test its responses and document what works and what needs improvement.
Frequently Asked Questions
This program is designed for students, beginners, aspiring developers and professionals who want to understand Generative AI and learn how AI-powered applications and agents are built. No advanced AI engineering experience is required.
You will explore generative AI, large language models, prompt engineering, tool calling, retrieval-augmented generation (RAG), AI workflows, agent fundamentals, testing and responsible AI practices.
An AI agent is an AI-powered system that can use available tools and information to work toward a goal. Depending on its design, it may plan steps, retrieve information or perform actions within defined permissions and safeguards.
Basic computer and internet skills are important. Programming knowledge is helpful for coding-based projects, but whether coding is mandatory depends on the practical activities included in the program. Review the listed requirements before enrolling.
The learning plan is designed around practical missions and a final project. Check the published curriculum for the exact project tasks, tools and submission requirements included in your cohort.
The proposed learning plan is structured across four weekly modules. Please check the program details on this page for the confirmed duration and schedule.
You will receive 182 days of access from the date you enroll if the standard site-wide access period applies to this program.
Certificate eligibility depends on completing the program requirements and submitting the required project, as specified in the published certification criteria.
Some AI tools and API providers may require paid plans, usage credits or separate accounts. Any specific tools or additional costs required for the program should be confirmed in the course requirements before enrollment.
No. Completing the program does not guarantee employment, paid projects or a particular career outcome. The program is intended to help you build foundational knowledge and practical experience that you can continue developing.
Review the curriculum, requirements, access terms and enrollment price on this page, then select Enroll Now to begin your enrollment.
Certification
On completing this program and submitting your project, you'll receive a Foundation Completion Certificate — and unlock enrollment into the next stage.
