Embarking on your first AI project doesn’t need to be intimidating. At EduWelle, we break it down into 5 clear and actionable steps.
1. Define the Problem
What are you solving? Is it classification (e.g., spam detection), regression (e.g., house price prediction), or clustering (e.g., customer segments)?
2. Collect & Clean Data
Start with public datasets like Kaggle or UCI ML Repository. Clean and preprocess for missing values, noise, or outliers.
3. Choose a Model
Begin with simple models using scikit-learn. As you gain confidence, explore deep learning frameworks like TensorFlow or PyTorch.
4. Train and Evaluate
Split your data into training and test sets. Evaluate performance using metrics like accuracy, F1-score, or RMSE depending on your problem.
5. Visualize and Deploy
Use matplotlib or seaborn to generate insights from your model. Try deploying a simple web app using Streamlit or Gradio.
Join our upcoming AI Bootcamp for a hands-on walkthrough with live mentoring and real-world datasets.
📩 Want a free project template? Email us at info@eduwelle.com