Build, train & deploy AI NLP text‑based ML models.

About this course

Most machine learning tutorials stop at theory or leave you with a model that never leaves a notebook. This project-based course goes all the way to production deployment.

You will build a real AI solution that detects cyberbullying-level toxicity in social media text. Instead of small toy datasets, you will train on 47,692 real posts, reflecting the scale and complexity used in real projects.

You will:

• Clean and structure messy text data for modeling
• Engineer TF-IDF features and train classification models
• Evaluate model performance and improve reliability
• Detect and address bias using responsible AI techniques
• Build an interactive web app with Streamlit

Deploy the system to the cloud with a live public URLAt the end, you will have:

• A fully deployed machine learning applicationA professional GitHub repository
• Visualizations and reports explaining your results
• Practical experience in ethical, interpretable, deployable AI

This course prepares you to discuss your work confidently in job interviews:

• “I built a production system. Here is the live demo. Here’s the code. Here’s how I managed fairness and explainability.”
• All tools are free, all code is provided, and every concept is explained clearly.
• Who This Course Is ForPython developers transitioning into machine learning or AI engineering
• Aspiring data scientists seeking strong portfolio projects
• Career changers gaining practical, job-focused ML experience
• Students and graduates wanting to go beyond theoretical practice
• Software engineers adding ML deployment skills to their workflow
• Product managers, analysts, UX professionals working with AI teams
• Entrepreneurs building AI-enabled applications or p

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