Artificial Intelligence

Period 2: Artificial Intelligence

Language: English Dates: 8 – 20 August 2021

Introduction to Artificial Intelligence

What is Artificial Ingelligence (AI)? Can we program machines to see, to listen, or to talk? How AI is transforming science and improving our lives? In this introductory lecture, we will look at the history of AI — what we achieved so far and what are the future possibilities. The lecture will follow with a crash course on Python, which will be programming language foe the mini projects in the other lectures.

Aykut Erdem Assoc. Prof. College of Engineering
Machine Learning Basics

It will be a short introduction to Deep Learning with some toy examples.

Fatma Güney Assist. Prof. College of Engineering
Natural Language Processing

Understanding human language is one of the long term goals of artificial intelligence. The field of natural language processing tries to solve problems such as question answering, machine translation, document summarization, sentiment analysis and power today's popular digital assistants such as Alexa, Siri and Google Assistant. In this class we will introduce some of the basic problems and algorithms of NLP and learn how to build simple NLP models.

Deniz Yüret Prof. College of Engineering
Machine Learning and Security

The risk and severity of cyberattacks have grown over the past years. In this mini course, we will learn about the intersection of machine learning (ML) and cybersecurity from two complementary perspectives: (i) using ML to combat cyberattacks, and (ii) making ML models more secure, robust, and dependable. We will study examples involving spam filtering, fraud detection, and image recognition.

M. Emre Gürsoy Assist. Prof. College of Engineering
Artificial Intelligence in Drug Discovery

Artificial Intelligence in Drug Design

Finding small molecules that are effective against a target protein involved in disease is at the core of pharmaceutical research. The vast chemical space of molecules makes determining such interactions very challenging. In this mini course, first, we review the computational approaches to predict drug-target interactions. A hands-on session in the second part will show how machine learning can be used to predict such interactions.

Attila Gürsoy Prof. College of Engineering
Deep Learning

Today's AI based technologies can solve problems such as driving cars, translating sentences, recognizing tumors using a set of brain-inspired techniques called "deep learning". These techniques were developed in a span of 60 years but have come to their own during the last decade due to larger datasets, larger computers and better algorithms. In this class we will introduce the basic ideas underlying deep learning and learn how to build and use simple deep learning models.

Deniz Yüret Prof. College of Engineering
Speech & Audio Processing

This mini course will teach how humans produce speech and perceive sounds through the hearing system. We will look into acoustics of concert halls for the fundamentals of filtering and extensions of these fundamentals to various AI applications. Finally, we will run a mini project to simulate acoustics of different halls.

Engin Erzin Prof. College of Engineering
Computer Vision

Computer vision deals with all aspects of understanding digital images with a computer. As such it is one of the main components of an artificial intelligence system. In this course we will first introduce the fundamental tasks of computer vision, including image classification, segmentation and object detection. We will then focus on image classification which is the task of assigning a category label to a given image so as to recognize the types of objects that it contains, such as a "cat" image, a "flower" image, etc. We will learn about different methods to tackle this problem, including deep learning. The course will also involve some hands-on work that demonstrates how to do image classification in practice.

Yücel Yemez Prof. College of Engineering
Robotics

Motion Planning for Robots

The first part of this mini course will introduce the basic concepts of AI-based motion planning for robots (i.e. planning the trajectory of a robot for moving from point A to point B). The second part will involve practical demonstrations of this concept in a software environment.

Çağatay Başdoğan Prof. College of Engineering
Medical Image Analysis

This mini course will first overview image analysis applications in medicine and biology research. It will then look into the problem of cell segmentation in microscopy images and AI techniques to address this problem. Finally, it will run a mini project for counting cells in microscopy images.

Çiğdem Gündüz Demir Assoc. Prof. College of Engineering
Generating Images with GANs

This mini course will teach the basics of Generative Adversarial Networks (GANs), a modern machine learning technique for generative modeling. In particular, we will discuss what are GANs and how they can create realistic looking but fake images. Finally, we will run a mini project where we aim to train a GAN model to synthesize novel images.

Aykut Erdem Assoc. Prof. College of Engineering
Autonomous Driving & Motion Estimation

We will first learn about the problem of autonomous driving, look at some example data and challenges. Then we will learn about two general approaches to the autonomous driving problem.  In the second lecture, we will focus on a particular problem, motion estimation in videos, and see an application of it to create a slow-motion effect as in the movie Matrix.

Fatma Güney Assist. Prof. College of Engineering

Course Outline

1. Week
09-Aug 10-Aug 11-Aug 12-Aug 13-Aug
10:00-10:50 Introduction to Artificial Intelligence Extracurricular Activities Machine Learning and Security Extracurricular Activities Extracurricular Activities
10:50-11:10 Break Break
11:10-12:00 Python Crash Course Mini ML and Security Project
12:00-13:00 Break Break
13:00-13:50 Machine Learning Basics Deep Learning Artificial Intelligence in Drug Discovery Natural Language Processing
13:50-14:10 Break Break Break Break
14:10-15:00 Mini ML Project Mini Deep Learning Project
Mini Drug Discovery Project
Mini NLP Project
15:00-16:00 Break Break Break Break
16:00-17:00 Extracurricular Activities Extracurricular Activities Extracurricular Activities Extracurricular Activities
2. Week
16-Aug 17-Aug 18-Aug 19-Aug 20-Aug
10:00-10:50 Speech & Audio Processing Extracurricular Activities Medical Image Analysis Extracurricular Activities Extracurricular Activities
10:50-11:10 Break Break
11:10-12:00 Mini Speech & Audio Processing Project Mini Medical Image Analysis Project
12:00-13:00 Break Break
13:00-13:50 Computer Vision Robotics Learning to Generate Images with GANs Autonomous Driving
13:50-14:10 Break Break Break Break
14:10-15:00 Mini Computer Vision Project Mini Robotics Project Mini GAN Project Mini Autonomous Driving Project
15:00-16:00 Break Break Break Break
16:00-17:00 Extracurricular Activities Extracurricular Activities Extracurricular Activities Extracurricular Activities
Please note that this schedule is subject to changes.