Get in Touch

Course Outline

Introduction to Lightweight LLMs

  • Exploring compact model architectures.
  • The evolution of resource-efficient AI.
  • The significance of lightweight models for enterprise environments.

Understanding Nano Banana

  • Core features and design principles.
  • Model capabilities and inherent limitations.
  • Distinguishing Nano Banana from traditional LLMs.

Deployment Models and Use Scenarios

  • Benefits of on-device execution.
  • Comparing local versus cloud inference.
  • Choosing the optimal deployment path.

Practical Applications Across Industries

  • Internal automation and knowledge support.
  • Customer-facing use cases.
  • Operational and compliance-focused scenarios.

Integration Fundamentals

  • Evaluating system requirements.
  • Workflow and process implications.
  • Introduction to APIs and toolchains.

Cost Optimization and Efficiency

  • Leveraging compact models to lower inference costs.
  • Striking a balance between performance and resource usage.
  • Planning for scalable deployments.

Governance, Privacy, and Risk Management

  • Ensuring secure on-device execution.
  • Understanding data boundaries and protective measures.
  • Aligning with enterprise policies and standards.

Preparing for Organizational Adoption

  • Building internal capability and readiness.
  • Assessing business value through pilot projects.
  • Establishing the foundation for broader rollouts.

Summary and Next Steps

Requirements

  • A foundational understanding of general IT concepts.
  • Proficiency with basic software tools.
  • Familiarity with data-driven business workflows.

Audience

  • General IT teams integrating AI capabilities.
  • Business professionals interested in practical AI applications.
  • Technology managers assessing strategies for on-device LLMs.
 7 Hours

Number of participants


Price per participant

Testimonials (1)

Upcoming Courses

Related Categories