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Data Science with Vibe Coding

900 000 ₸
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Allocated 13 Quotas

Data Science with Vibe Coding is a 26-week course by Outpeer for those who want to enter Data Science and AI development from scratch. No prior experience is required — we start with the basics: Python, working with data, and basic machine learning models. Then you move to the Vibe Coding approach, where you describe a task, and AI tools help turn it into code and ready-made solutions. You will learn to create AI applications, work with PyTorch, build RAG systems, develop AI agents, and automate processes using no-code tools like n8n, Make, and Flowise. By the end of the course, you will develop your own AI product and defend it as a full project. The course is conducted online, three times per week, with instructor support and a practical focus on real tasks.

Special condition

Student Selection Criteria: Stage 1 — Application Submission: The participant fills out an online form with their CV. Stage 2 — Application Review: The Outpeer committee selects candidates. Stage 3 — In-depth Interview: Selected candidates participate in a 20-minute online video interview. Stage 4 — Pre-study: Self-study of preparatory material before the main course starts. Other Conditions: Full course fee: 900,000 KZT Students receiving the TechOrda grant pay an additional 500,000 KZT — the rest is covered by the grant If a student is on the waitlist, Outpeer covers the remaining fee Failure to pass the final test at the end of the course results in a penalty of 400,000 KZT Payment installment and discount terms are clarified with the course manager Waitlist: To join the waitlist, the student pays 500,000 KZT When a spot becomes available, the student is automatically transferred to the TechOrda grant The 500,000 KZT paid is counted as part of the grant contribution

Course details

level

For all

Study format

Online

Entrance exams

No

Duration, in weeks

26

Education language

Russian

Qualifications

junior

Skills


Work with LLMs and AI tools (for example OpenAI, Claude, Cursor) Build AI apps using Prompt Engineering and APIs Develop RAG systems and AI agents (LangChain, LangGraph) Work with vector databases and multi-agent architecture No-code AI automation (n8n, Make, Flowise) Deploy AI services (FastAPI, Docker) Monitor, test, and secure AI apps Create production-ready AI via capstone project

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