[2025] Fase 2 | NÍVEL 3 AULA 3 Criando um Protótipo com Inteligência Artificial

Introduction

In this tutorial, we will explore how to create a prototype using artificial intelligence. This guide is designed for learners who want to understand the basics of AI prototyping, providing practical steps to help you bring your ideas to life. Whether you're a beginner or looking to enhance your skills, this tutorial will equip you with the knowledge to get started.

Step 1: Define Your Project Idea

• Begin by identifying the purpose of your prototype.
• Consider what problem your AI solution will solve.
• Write down your project idea, including key features and functionalities.

Step 2: Research Existing Solutions

• Investigate existing AI tools and frameworks that align with your project.
• Look into similar applications to gather inspiration.
• Take note of strengths and weaknesses in those solutions to inform your design.

Step 3: Choose Your Development Tools

• Select the programming language and tools best suited for your prototype. Common choices include:
  • Python for its simplicity and extensive libraries.
  • JavaScript for web-based projects.
• Familiarize yourself with AI libraries such as TensorFlow or PyTorch if using Python.

Step 4: Design the User Interface

• Sketch a wireframe of your application's interface.
• Determine how users will interact with your AI features.
• Use tools like Figma or Adobe XD for creating digital mockups.

Step 5: Develop Your AI Model

• Gather and prepare your dataset for training the AI model.
• Split your data into training and testing sets to evaluate performance.
• Use the following code snippet as a starting point for building a simple model:

import tensorflow as tf
from tensorflow import keras

# Define the model
model = keras.Sequential([
    keras.layers.Dense(64, activation='relu', input_shape=(input_shape,)),
    keras.layers.Dense(10, activation='softmax')
])

# Compile the model
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])

• Train your model with the training dataset and validate it using the testing dataset.

Step 6: Integrate AI with Your Application

• Connect your AI model to the user interface.
• Ensure that user inputs are correctly processed by the model.
• Test the integration thoroughly to confirm functionality.

Step 7: Gather Feedback and Iterate

• Share your prototype with peers or potential users to collect feedback.
• Use their insights to make necessary improvements.
• Iterate on your design and functionality based on the feedback received.

Conclusion

Creating a prototype with artificial intelligence involves several key steps, from defining your project idea to gathering feedback post-development. By following these steps, you can effectively turn your AI concept into a tangible prototype. As a next step, consider exploring advanced topics such as model optimization or user experience design to enhance your skills further.