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Getting ready for Phase 2

Workshop
Complete

Welcome to Phase 2: Applying ML Techniques​

The second phase of the AI ML Fellowship program focuses on the practical application and refinement of machine learning models.

Phase 2 illustration

Phase 2 breakdown​

The core theme is the practical application, optimisation, and responsible deployment of machine learning models.

Main topics covered​

  • Model Engineering and Training: Developing, training, and optimising various ML model architectures and handling complex data.
  • Model Evaluation: Rigorously assessing models, selecting metrics, and analysing bias-variance trade-offs.
  • Data Security, Privacy, and Governance: Navigating compliance, implementing security measures, and fostering a security-conscious culture.
  • Hackathon: Putting Phase 2 learning into real-world practice.

Exciting connections to your role​

  • Improving decision-making accuracy: Accurate and reliable ML-driven insights through model optimisation.
  • Developing adaptive systems: Building models that adapt to changing data and environments.
  • Ensuring data integrity and compliance: Applying techniques to protect sensitive data and mitigate risk.

Action item: Share what you want to learn in Phase 2​

Directions: In the chat, share what you are most excited to learn or apply from this phase!