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AI Data Analytics

900 000 ₸
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Allocated 10 Quotas

AI Data Analytics is a 26-week course designed for anyone looking to enter IT and data analytics. The program covers modern AI tools as part of the workflow. Students progress from business analytics in Google Sheets and Power BI to SQL, Python, and statistical methods used daily in real companies. The course emphasizes practical learning with real datasets, project work, and integration of AI tools such as Copilot, ChatGPT, and Claude for automating routine tasks. By the end of the course, participants will have the skills to independently analyze data, create dashboards, and apply analytics in real business scenarios.

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


Analyze business data in Google Sheets (ABC, cohort analysis) Work in Power BI: models, formulas, interactive reports Data visualization and dashboards with storytelling Use AI tools to speed up tasks (ChatGPT, Claude) Extract data via SQL (SELECT, JOIN, GROUP BY) Data processing in Python (NumPy, Pandas) Data visualization (Matplotlib, Seaborn) AI assistants for coding (Copilot, Cursor) Statistics: hypothesis testing, A/B tests Key business metrics: funnels, LTV, CAC, ROI, ARPU, RFM Automate reports with Python and LLM API

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