| School/Faculty/Institute | Faculty of Engineering | ||||
| Course Code | DSAI 102 | ||||
| Course Title in English | Mathematical Foundations for DS and AI | ||||
| Course Title in Turkish | Veri Bilimi ve Yapay Zeka için Temel Matematik | ||||
| Language of Instruction | EN | ||||
| Type of Course | Guided Personal Study | ||||
| Level of Course | Introductory | ||||
| Semester | Fall | ||||
| Contact Hours per Week |
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| Estimated Student Workload | 156 hours per semester | ||||
| Number of Credits | 4 ECTS | ||||
| Grading Mode | Pass / Fail | ||||
| Pre-requisites | None | ||||
| Expected Prior Knowledge | None | ||||
| Co-requisites | None | ||||
| Registration Restrictions | Only Undergraduate Students | ||||
| Overall Educational Objective | To develop your knowledge of the core concepts of data science and develop analytical and critical thinking abilities. | ||||
| Course Description | This course is a comprehensive introduction to mathematical foundations that are key to artificial intelligence and data science. The following topics are covered: Joint and conditional probabilities, random variables, discrete and continuous probability distributions, sampling, estimation, central limit theorem, hypothesis tests. | ||||
| Course Description in Turkish | Bu derste; yapay zeka ve veri biliminin anahtarı olan matematiksel temellere yönelik şu konu başlıkları kapsamlı bir biçimde incelenmektedir: Ortak ve koşullu olasılıklar, rastgele değişkenler, ayrık ve sürekli olasılık dağılımları, örnekleme, tahmin, merkezi limit teoremi, hipotez testleri. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) describe and explain the role of mathematical foundations of DS-AI while communicating effectively with a range of audiences via subject and case presentations; 2) recognize and discuss ethical and professional responsibilities in engineering situations that are directly related to artificial intelligence, data science and related technologies while considering the impact of engineering solutions in global, economic, environmental, and societal contexts; 3) acquire and demonstrate over a case related to contemporary issues in artificial intelligence and data processing/visualization etc. using appropriate learning strategies. |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 |
|---|---|---|---|
| 1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | |||
| 2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | |||
| 3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | |||
| 4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | |||
| 5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | |||
| 6) Internalization and dissemination of professional ethical standards. | |||
| 7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | |||
| 8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | |||
| 9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | |||
| 10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | |||
| 11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | |||
| 12) Ability to acquire knowledge independently, and to plan one’s own learning. | |||
| 13) Demonstration of advanced competence in the clarity and composition of written work and presentations. |
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | N | |
| 2) | Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | N | |
| 3) | Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | H | Exam,HW,Participation |
| 4) | Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | N | |
| 5) | Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | N | |
| 6) | Internalization and dissemination of professional ethical standards. | N | |
| 7) | Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | N | |
| 8) | Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | N | |
| 9) | Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | S | Participation |
| 10) | Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | S | HW,Participation |
| 11) | Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | N | |
| 12) | Ability to acquire knowledge independently, and to plan one’s own learning. | S | Exam,HW |
| 13) | Demonstration of advanced competence in the clarity and composition of written work and presentations. | H | Exam,HW |
| Prepared by and Date | TUNA ÇAKAR , November 2023 |
| Course Coordinator | TUNA ÇAKAR |
| Semester | Fall |
| Name of Instructor | Asst. Prof. Dr. UTKU KOÇ |
| Week | Subject |
| 1) | Introduction to Probability |
| 2) | Probability Basics |
| 3) | Important Probability Distributions, Probability Meets Statistics |
| 4) | Summary Statistics, Probability and distributions |
| 5) | More Distributions and the Central Limit Theorem |
| 6) | Correlation and Hypothesis Testing |
| 7) | One Sample Proportion Testing |
| 8) | Hypothesis Testing in Python I |
| 9) | Hypothesis Testing in Python II |
| 10) | Statistical Experiment and Significance Testing I |
| 11) | Statistical Experiment and Significance Testing II |
| 12) | Regression and Classification |
| 13) | Statistical Simulation I |
| 14) | Statistical Simulation II |
| 15) | Final Exam/Project/Presentation |
| 16) | Final Exam/Project/Presentation |
| Required/Recommended Readings | Shared videos | ||||||
| Teaching Methods | Guided personal study | ||||||
| Homework and Projects | Datacamp Assignments (40%), Final Exam (60%) | ||||||
| Laboratory Work | Application-based laboratory study | ||||||
| Computer Use | Required | ||||||
| Other Activities | - | ||||||
| Assessment Methods |
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| Course Administration |
dsai@mef.edu.tr 05309225505 Instructor’s office: 5th floor Phone number: 0 212 395 37 50 Office hours: After the lecture hours. E-mail address: cakart@mef.edu.tr |
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| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 1 | 2 | 42 | |||
| Laboratory | 10 | 1 | 2 | 30 | |||
| Study Hours Out of Class | 1 | 1 | 10 | 11 | |||
| Project | 1 | 5 | 25 | 30 | |||
| Homework Assignments | 10 | 1 | 2 | 30 | |||
| Final Examination | 1 | 10 | 3 | 13 | |||
| Total Workload | 156 | ||||||
| Total Workload/25 | 6.2 | ||||||
| ECTS | 4 | ||||||