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Datanomix Academy

9

AI Product Manager: Driving AI & ML Products from Concept to Metrics

400 000 ₸
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Allocated 34 Quotas

This course is dedicated to AI and ML product management, guiding participants through the complete product lifecycle: from formulating a product hypothesis and working with data to production deployment and performance evaluation. The program covers data management, model quality metrics, and ML project management frameworks (including the Data Product Canvas, hypotheses generation, and experimentation). Students will learn how to align AI features with business metrics and unit economics, as well as master A/B testing methodologies. A dedicated module focuses on cutting-edge technologies—including LLMs, RAG, multimodality, and AI agents—supplemented by a practical prompt library. The course is tailored for practicing Product and Project Managers seeking to confidently launch AI-driven products. Upon completion, students will be fully equipped to delegate tasks to Data Science teams, select appropriate metrics, and evaluate the business impact and economics of AI features. Heavy emphasis is placed on hands-on practice, real-world case studies, and regular feedback from instructors and mentors. Every participant will develop and pitch their own AI product project as a final capstone defense.

Special condition

In the event that the Student is unable to continue their studies after the commencement of the course, either at their own initiative or due to their fault, a penalty in the amount of 100% of the tuition fee (400,000 KZT) shall apply. Grounds for dismissal from the course: Failure to submit three (3) or more homework assignments within the established deadlines; Missing three (3) or more seminars without prior notice and approval from the course coordinator; Failure to take or refusal to take the final assessment test; Failure to pass the final exam case study. Payment Procedure: The School reserves the right to demand payment of the penalty. Upon issuance of such a demand, the Student must pay the amount within ten (10) business days from the date the School sends a written notice. Enrollment and Tuition Conditions for Waitlist Students Discounted Enrollment: Students enrolled from the waitlist are admitted on a paid basis with a 20% discount off the full grant value (the discounted tuition fee is 320,000 KZT). Transition to the Tech Orda Grant: If a Tech Orda grant slot becomes available during the course (due to the dismissal or transfer of another student) and this Student is officially transferred to the grant, the School will issue a full refund of the tuition fees previously paid by the Student. Candidate Evaluation & Selection This test effectively selects candidates who: Possess a foundational understanding of AI technologies and their product applications; Demonstrate a product-driven mindset and result-oriented approach; Understand business context and key success metrics; Can articulate their proposals in a structured and coherent manner; Are capable of balancing technological capabilities, business needs, and user experience (UX). To pass the test successfully, you must answer 80% of the questions correctly and solve the case study.

Course details

level

For advanced

Study format

Online

Entrance exams

No

Duration, in weeks

26

Education language

Russian

Qualifications

middle

Skills


AI/ML product lifecycle management — from hypothesis formulation to production deployment; Task scoping for Data Science teams and defining model requirements; Selection and interpretation of model quality metrics and proxy metrics; Utilizing the Data Product Canvas and validating product hypotheses; Calculating unit economics for AI features and aligning them with business outcomes (KPIs); Designing and analyzing A/B tests, including experiments for AI-driven functionality; Leveraging LLMs, prompt engineering, RAG, and AI agents to solve product use cases; Accounting for model interpretability, AI UX, and ethical considerations during AI solution deployment.

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