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SCHOOL OF INFORMATICS AND ROBOTICS

Programming for AI (Artificial Intelligence) — Summer Course

Course Information

Duration: 3 Weeks

Audience: Students & Beginners

Frequency: 4 sessions per week

Total Sessions: 12 Sessions

Session Duration: 60–90 minutes

Fee Structure: PKR 8,000

Prerequisite: Basic computing skills and elementary logic

Course Overview

This course introduces students to Artificial Intelligence programming concepts, machine learning foundations, and generative AI tools. Students will learn how AI systems work, how data drives intelligence, and how to build simple AI-driven projects using modern tools and techniques.

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Course Objectives

  • Understand how programming drives Artificial Intelligence and Machine Learning models.
  • Learn how Machine Learning models work and the importance of data logic.
  • Explore Generative AI and prompt engineering techniques.
  • Recognize ethical considerations and future career trends in AI.
  • Build or configure a basic AI-driven micro-project.

Weekly Breakdown

Week 1: Foundations of AI & Core Logic

  • What is Programming for AI? Introduction to AI logic and milestones.
  • AI Spectrum: Weak AI vs Strong AI, Narrow vs General Intelligence.
  • Real-world impact of AI in industries like Healthcare, Finance, Entertainment.
  • Introduction to data logic and rule-based vs learning-based systems.
  • Overview of Machine Learning, Deep Learning, NLP, Computer Vision.

Week 2: Machine Learning Concepts & Generative AI

  • Supervised, Unsupervised, and Reinforcement Learning concepts.
  • Classification and Regression basics (without complex math).
  • Case studies: Netflix recommendation system & spam filters.
  • Introduction to Generative AI and Large Language Models (LLMs).
  • Prompt engineering basics and practical exercises.

Week 3: Ethics, Future Trends & Micro-Project

  • AI Ethics: bias, fairness, privacy, and deepfakes.
  • Future of work and AI collaboration in careers.
  • Project brainstorming: AI tools, workflows, or GPT-based ideas.
  • Final project development and demonstration.
  • Course recap, Q&A, and certificate distribution.
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