Discover which critical phase of AI-first software engineering focuses on training and fine-tuning AI models to power innovative applications. Learn how implementation and coding play a key role in the AI development process.
Table of Contents
Question
Which phase of Al-First Software Engineering involves training and fine-tuning Al models?
A. Requirements gathering
B. Design and architecture
C. Implementation and coding
D. Testing and quality assurance
Answer
C. Implementation and coding
Explanation
In the AI-first software engineering lifecycle, the implementation and coding phase is where AI models are trained and fine-tuned. This phase comes after the requirements gathering and design phases, where the problem to be solved and the high-level architecture are defined.
During implementation and coding, data scientists and ML engineers:
- Prepare and preprocess training data
- Select appropriate AI/ML algorithms and models
- Train the models on the prepared data
- Fine-tune model hyperparameters to optimize performance
- Evaluate the trained models and iterate to improve them
- Integrate the final models into the application codebase
The other phases like requirements gathering, design, and testing are also important in the AI development process, but do not directly involve training and tuning the AI models themselves. That crucial work happens during the hands-on implementation and coding phase.
So in summary, the implementation and coding phase is where the core development work to build, train and refine AI models takes place, making it the clear answer to the question of which phase involves training and fine-tuning AI models in the software engineering lifecycle.
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