DS-AI Minor Program Details
Program Coordinator: Tuna Çakar
cakart@mef.edu.tr
Program Student Assistants:
Pelin Mişe misepe@mef.edu.tr
Kerem Kaya kayake@mef.edu.tr
Mehmet Talha Bozan bozanm@mef.edu.tr
What is the DS-AI Minor Program?
Data Science & Artificial Intelligence Minor Program has been designed to provide competence with extracting value from data, analyzing data, and reconciling artificial intelligence with statistical approaches, which is presented to the students from all of the faculties. The program was designed by the active academicians, experts and professionals to present diversified dimensions of data science and artificial intelligence from data management to exploratory data analytics and from machine learning to deep learning enriched with the common grounds of the contemporary trends and current applications.
Scope and Design of the DS-AI Courses
The first courses of the minor program are mathematical foundations (statistics etc.) and programming (Python) is a basis for data science which is a subset of artificial intelligence. After obtaining this core information, the process of learning databases and analyzing data is started. Machine learning, artificial intelligence, and ethics of these topics are other courses for the program. In addition to these must courses of the minor program, there is a wide range of options for the elective courses. Because of the enriched diversity in elective courses, students who take the minor program are expected to establish and further develop the potential relationships between their departments and DS-AI as well as to be capable of generating new insights and innovative ideas for novel applications to these domains.
Why is there an urgent need for the DS-AI Minor Program?
According to the World Economic Forum's Future of Jobs 2020 report, in the list of the top 20 job roles in increasing demand across industries, the first of the top is Data Analysts and Scientists, and the second of the top is AI and Machine Learning Specialists (Future of Jobs Survey 2020, World Economic Forum). This report's result proves the efficiency of this minor program in business life. Covering data science and artificial intelligence, which are the most important topics of today and the future, the minor program will be entirely free and also accessible to all students with online course options. Courses, which are provided to learn topics about the minor program, are taken from the well-known online course platforms such as Coursera, edX, Udacity, DataCamp and Alison.
What is aimed with this DS-AI minor?
The courses are completed by putting the gains into practice with processes such as writing-running code, preparing video presentations, and realizing projects. This program will enable students to become pioneers in the work environment where DS-AI is rapidly entering, with courses specific to entire departments ranging as teaching, architecture, psychology, and law. It is aimed to enable young people in these disciplines to become professionals with expertise that can add innovative values to their competitiveness by identifying, collecting, analyzing, and interpreting data, and taking the lead in artificial intelligence.
DS-AI Minor Program Educational Objectives
DS-AI Minor Program identified the following list of educational objectives for the minor program, which describes the broad vision for what our students will be achieving in their careers within a few years after graduation:
Understand, diagnose, analyze, and solve real-life problems by reflecting a good understanding of DS-AI knowledge and approach,
Learn and apply new approaches, technologies, solutions, and values utilizing modern DS-AI related techniques together with their innovative and entrepreneurial skills to meet the needs of society,
Demonstrate high levels of communication skills integrated with responsibility, teamwork, and organizational skills, and ethical and environmental considerations.
Course Plan of DS-AI
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Program Course Credit Guidelines
The DS-AI Minor Program students must complete 8 of the MUST courses and 2 of the courses in the table for Elective courses.
Each credit in ECTS corresponds to 25-30 hours of workload for the whole term.
These courses are independent from the courses of the other faculties thus one cannot transfer any credits from this program to another or from another program to this program.
Each student should complete a Capstone Project with a project and should work on a DS-AI oriented case obtained from a company.
Course Descriptions for the MUST Courses in the DS-AI Program
DSAI 101 Introduction to DS-AI
This course is a broad introduction to core concepts of data science and artificial intelligence programs. It begins by examining what data is, what the data scientist is doing, and examines the history and future of data science.
DSAI 102 Mathematical Foundations for DS-AI
Mathematics provides many powerful insights into the basic principles of Computer Science.This course reveals the basic mathematics that you need to understand and apply to write machine learning algorithms. You will learn how to analyze the accuracy and compliance of production processes, raw data, and interpret the results of each technique using statistical tools. You will work on modeling problems mathematically, reasoning them abstractly, and then applying techniques to explore their properties. At the end of the course, you should be able to fully understand and apply basic statistical concepts to a wide range of data. This broad introduction to mathematical applications will prepare you to advance and solve today's most important problems in the field of Computer Science.
DSAI 103 Programming for DS-AI
Python is a popular and highly readable object-oriented language that is both powerful and relatively easy to learn. The minor program provides a basis for the Python programming language. This Python course guides students from the basics of writing and running Python scripts to more advanced features. Especially needed programming skills for data science and ml will be gained. Python libraries such as NumPy, Pandas, Matplotlib etc will be learned. At the end of the course, you will be able to do some applications with python such as data preprocessing, data analyzing etc.
DSAI 201 Fundamentals of Machine Learning and Data Science
This course provides a comprehensive introduction to the field of machine learning. Firstly, the practical aspects of machine learning using Python's Scikit-Learn package will be examined. Contains the following topics: Hyper-parameters and model validation, Classification, Naive Bayes, linear regression, support vector machines, Random Forests and decision trees, Principal Component Analysis, Manifold Learning, K-mean Clustering, Gaussian Mixture models and kernel density estimation.
DSAI 202 Fundamentals of Artificial intelligence
This is an introductory course on Artificial Intelligence Fundamentals. This course of artificial intelligence (AI) to know what is, explore use cases and applications of artificial intelligence. Topics include: Basic AI and ML core concepts, computer vision, machine learning, natural language processing and conversational AI. At the end of the course, students will be able to activate artificial intelligence applications by using the information they have learned.
DSAI 203 Social & Ethical Issues in AI and DS
This course covers how to include ethical principles and provide a societal perspective in the projects and also explores how to add several central concepts including transparency and build trust by examining the main issues of justice and prejudice in artificial intelligence. At the end of the course, students will explore many aspects of building more ethical models, from human bias to dataset awareness.
DSAI 301 Fundamentals of Databases
This course is an introduction to the basic concepts, organization and application models of databases. It provides the basis for data management concepts and database systems. It includes representing information with the relational database model, manipulating data with an interactive query language (SQL) and database programming, On-Line Analytical Processing (OLAP), Modeling and Theory, analyzing data with Python. At the end of the course you will have knowledge about categorizing, saving and updating information in database management systems by using SQL.
DSAI 302 Capstone Project
Once courses are taken to develop the main set of skills in basic data science and artificial intelligence, a capstone project will be conducted to apply these skills, give clear feedback, and demonstrate all the skills gained. The Capstone project will be created by individuals and will work on a DS-AI-focused case obtained from a company.
DSAI 30X Elective-1
DSAI 30X Elective-2