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Duration 7 hours
Course Outline
Overview of Lightweight LLMs
- Exploring compact model architectures
- The progression of resource-efficient AI
- The significance of lightweight models for enterprise operations
Gaining Insight into Nano Banana
- Core features and design methodologies
- Model strengths and constraints
- Distinguishing Nano Banana from conventional LLMs
Deployment Strategies and Scenarios
- On-device execution and its advantages
- Comparing local and cloud inference
- Choosing the optimal deployment route
Real-World Applications Across Sectors
- Internal automation and knowledge support
- Applications designed for customer interaction
- Scenarios driven by operations and compliance
Foundations of Integration
- Reviewing system requirements
- Considerations for workflows and processes
- Introduction to APIs and toolchains
Cost Efficiency and Optimisation
- Leveraging compact models to lower inference costs
- Striking a balance between performance and resource usage
- Planning for scalable implementations
Governance, Data Privacy, and Risk Control
- Safeguarding on-device execution
- Comprehending data boundaries and protective measures
- Ensuring alignment with corporate policies and standards
Readying the Organisation for Adoption
- Developing internal expertise and preparedness
- Evaluating business impact through pilot initiatives
- Establishing the foundation for wider deployment
Conclusions and Forward Path
Requirements
- A solid grasp of general IT concepts
- Proficiency with fundamental software tools
- Exposure to data-driven business processes
Target Audience
- IT teams looking to adopt AI capabilities
- Business professionals interested in practical AI solutions
- Technology leaders evaluating on-device LLM strategies
Testimonials (1)
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