Role-Based Programme
RB0934

Hugging Face for Product & Service Management

Design, Evaluate, Prototype & Scale AI-Powered Products

IMAGE REQUIRED
Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced proficiency in using the Hugging Face ecosystem to discover, evaluate, prototype, and plan AI-enabled products and services.
  • Translate customer problems and product requirements into appropriate AI tasks, model-selection criteria, datasets, evaluation frameworks, and acceptance criteria.
  • Compare models using Model Cards, evaluation results, leaderboards, practical testing, quality measures, latency, cost, and deployment considerations.
  • Build and validate AI-product prototypes using Hugging Face Spaces and develop production pathways using Inference Providers and Inference Endpoints.
  • Establish responsible AI-product practices covering model limitations, data suitability, licensing, security, access, governance, human oversight, and lifecycle management.

Tools covered

Hugging Face HubModelsModel CardsDatasetsDataset CardsSpacesGradioInference PlaygroundInference ProvidersInference EndpointsEvaluation ResultsCommunity LeaderboardsOrganizationsPrivate RepositoriesAccess Controls & Security Features

Who should attend

  • Product Managers
  • Senior Product Managers
  • AI Product Managers
  • Product Owners
  • Service Managers
  • Service Design Professionals
  • Digital Product Managers
  • Platform Product Managers
  • Product Strategy Professionals
  • Product Operations Professionals
  • Product Innovation Leaders
  • Business Product Owners
  • Solution Product Managers
  • Product & Service Portfolio Managers
  • AI Transformation & Innovation Professionals

Prerequisites & Participant Readiness

  • Good understanding of product or service-management principles
  • Familiarity with product discovery, requirements, user journeys, prioritisation, and product lifecycle activities
  • Basic understanding of Generative AI and machine-learning concepts is recommended
  • Familiarity with APIs, data, and cloud services is helpful
  • Basic spreadsheet and analytical skills
  • No advanced programming expertise required
  • Prior hands-on exposure to AI tools is recommended for this advanced programme

TOC Modules

Concepts
  • Understanding Hugging Face Hub, models, datasets, Spaces, inference, and evaluation within an AI-product ecosystem
  • Mapping Discovery → Model Selection → Evaluation → Prototype → Pilot → Production → Monitoring
  • Understanding open, gated, private, and enterprise AI assets
  • Identifying responsibilities of product, engineering, data, security, legal, and business teams
Practical activities
  • Exploring representative models, datasets, Spaces, and AI tasks on the Hugging Face Hub
  • Mapping a selected product idea to relevant Hugging Face capabilities
  • Building an AI Product Lifecycle Canvas for the selected use case

Scenarios

AI Service Assistant – Idea to Production-Ready Proposal

Customer Problem → AI Use Case → Hugging Face Model Discovery → Model Card Review → Dataset & Evaluation Criteria → Comparative Testing → Space Prototype → User Validation → Inference Strategy → Production Readiness

Participants design an AI-enabled service assistant, evaluate multiple candidate models, prototype the experience, define user and business acceptance criteria, and develop a production recommendation covering performance, cost, security, and governance.

AI Product Feature Evaluation & Launch Decision

Product Requirement → Candidate Models → Benchmark Evidence → Product-Specific Testing → Quality / Latency / Cost Comparison → Risk Review → Pilot Results → Go / Revise / Stop Decision

Participants act as an AI-product team evaluating a proposed intelligent feature, using Hugging Face model information, evaluation evidence, prototype testing, deployment options, and governance requirements to produce an evidence-based product launch recommendation.

Related programmes

Continue with programmes from the same capability area.

Take the next step

Ready to make this programme work for your team?

Customise modules, duration and business scenarios for your team.

Instructor-ledVirtualHybrid

Designed around your roles, tools and real workflows.