AI-Enhanced Python Programming

A 12-week immersive course for first-year engineering students, blending fundamental Python skills with modern, AI-assisted learning methodologies.

12

Weeks

72

Total Contact Hours

5

Core Syllabus Units

Core Philosophy

This course transforms traditional instruction into an AI-augmented experiential learning environment. It integrates generative AI tools as learning partners, emphasizing project-based learning to prepare students for the future of software development.

Weekly Curriculum Explorer

Select a week to view detailed session plans and lab objectives.

Progressive AI Integration

The course strategically evolves the student's relationship with AI tools, fostering independent problem-solving skills alongside AI literacy.

This chart visualizes the planned shift in AI's role from a simple companion for learning basic concepts to an active collaborator in complex projects over the 12-week course. The goal is to build student confidence and competence, ensuring AI augments rather than replaces their critical thinking.

Technology & Tools

A curated ecosystem of AI assistants, development environments, and applications to support a seamless learning experience.

Primary AI Assistants

  • ChatGPT, Claude, Gemini
  • Microsoft Copilot, Mistral
  • Perplexity, DeepSeek, Grok

Development Environments

  • Google Colab & AI Studio
  • GitHub Copilot (in IDE)
  • Replit, Microsoft VDE

Recommended Mobile Apps

  • Free apps for tutoring
  • Rapid on-the-go development
  • Offline resource access

Assessment Revolution

Our framework embraces AI tools in evaluation, focusing on authentic learning, immediate feedback, and tracking both programming and AI literacy skills.

Continuous Assessment Methods

The assessment is designed to be ongoing and supportive. This chart shows the balance between different evaluation methods, emphasizing formative feedback and project-based work to build skills progressively.

Key Evaluation Strategies

  • ✓

    Weekly Formative Quizzes

    AI-generated feedback helps students identify gaps in understanding immediately.

  • ✓

    Portfolio-Based Projects

    Students build a portfolio showcasing their AI-assisted project's evolution, demonstrating practical skills.

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    Peer Assessment

    AI tools facilitate structured peer reviews, enhancing collaborative learning and code quality analysis.