Kodu | Dersin Adı | Yarıyıl | Süresi(T+U) | Kredisi | AKTS Kredisi |
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YBS316 | VERİ ANALİTİĞİ II | 6 | 3 | 3 | 8 |
DERS BİLGİLERİ |
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Dersin Öğretim Dili : | Türkçe |
Dersin Düzeyi | BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle |
Dersin Türü | Zorunlu |
Dersin Veriliş Şekli | - |
Dersin Koordinatörü | Assist.Prof. DİDEM TETİK KÜÇÜKELÇİ |
Dersi Veren Öğretim Üyesi/Öğretim Görevlisi | |
Ders Ön Koşulu | Yok |
AMAÇ VE İÇERİK |
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Amaç: | This course aims to enable students to develop basic algorithms in order to solve different types of problems and to teach the basic structures of programming and programming in a computerized environment; thus, it aims to make students think like a data scientist. |
İçerik: | The content of the course is the concepts of algorithms and programming, variables, data types, input and output statements, arrays, lists, dictionaries, functions, file operations and the use of Python as a data analytics tool. |
DERSİN ÖĞRENME ÇIKTILARI (Öğrenciler, bu dersi başarı ile tamamladıklarında aşağıda belirtilen bilgi, beceri ve/veya yetkinlikleri gösterirler.) |
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Develop algorithm for solving problems encountered in daily life. {develop} |
Evaluate the functions of the Python programming language.{evaluate} |
Design algorithms with Python programming language. {design} |
Test the usability of algorithms.{testing} |
Apply machine learning design to create solutions that meet the needs identified taking into account global, cultural, social, environmental and economic factors, as well as public health, safety and well-being.{Application} |
HAFTALIK DERS KONULARI VE ÖNGÖRÜLEN HAZIRLIK ÇALIŞMALARI |
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Hafta | Ön Hazırlık | Konular | Yöntem |
1 | - | Data, Information, Knowledge Concepts | Lecture & Studying on Sample & Practice |
2 | Studying on Sample, Assignment | Explaining R infrastructure and its installation | Lecture & Studying on Sample & Practice |
3 | Studying on Sample, Assignment | Loop structure and its functions | Lecture & Studying on Sample & Practice |
4 | Studying on Sample, Assignment | Data types (structural, non-structural nominal, ordinal data) | Lecture & Studying on Sample & Practice |
5 | Studying on Sample, Assignment | Basic statistical calculation and visualisation | Lecture & Studying on Sample & Practice |
6 | Studying on Sample, Assignment | Data pre-processing process | Lecture & Studying on Sample & Practice |
7 | Studying on Sample, Assignment | Principal Component Analysis | Lecture & Studying on Sample & Practice |
8 | - | MID-TERM EXAM | - |
9 | Studying on Sample, Assignment | Regression analysis | Lecture & Studying on Sample & Practice |
10 | Studying on Sample, Assignment | Hypothesis tests | Lecture & Studying on Sample & Practice |
11 | Studying on Sample, Assignment | Decision trees | Lecture & Studying on Sample & Practice |
12 | Studying on Sample, Assignment | Choosing Model and its methods | Lecture & Studying on Sample & Practice |
13 | Studying on Sample, Assignment | Logistic Regression | Lecture & Studying on Sample & Practice |
14 | Studying on Sample, Assignment | Practice | Studying on Sample & Practice |
15 | Studying on Sample, Assignment | Practice | Studying on Sample & Practice |
16 | - | FINAL EXAM | - |
17 | - | FINAL EXAM | - |
KAYNAKLAR |
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Gursakal, N. (2014). Istatistikte R ile Programlama. |
Arslan, I. (2015). R ile Istatistiksel Programlama. Pusula Publications, Istanbul. |
ÖLÇME VE DEĞERLENDİRME |
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Yarıyıl İçi Yapılan Çalışmaların Ölçme ve Değerlendirmesi | Etkinlik Sayısı | Katkı Yüzdesi | Açıklama |
(0) Etkisiz | (1) En Düşük | (2) Düşük | (3) Orta | (4) İyi | (5) Çok İyi |
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0 | 1 | 2 | 3 | 4 | 5 |
KNOWLEDGE | |||||||
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Theoretical | |||||||
Program Yeterlilikleri/Çıktıları | Katkı Düzeyi | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Define concepts such as management, manager and leader.
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4 | |||||
2 |
Analyze the accuracy, reliability and validity of the new information obtained from the data.
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5 |
KNOWLEDGE | |||||||
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Factual | |||||||
Program Yeterlilikleri/Çıktıları | Katkı Düzeyi | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Report the obtained data.
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5 | |||||
2 |
Prepare software and projects related with the field.
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5 |
SKILLS | |||||||
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Cognitive | |||||||
Program Yeterlilikleri/Çıktıları | Katkı Düzeyi | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Use the appropriate resources for data analysis related with the field.
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5 | |||||
2 |
Analyze the work processes.
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5 |
SKILLS | |||||||
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Practical | |||||||
Program Yeterlilikleri/Çıktıları | Katkı Düzeyi | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Manage projects as part of a team.
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5 | |||||
2 |
Apply the material, techniques and analyzes in relation with the subject for project and work flows.
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5 |
OCCUPATIONAL | |||||||
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Autonomy & Responsibility | |||||||
Program Yeterlilikleri/Çıktıları | Katkı Düzeyi | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Fulfill responsibility with a focus on result in individual and team studies.
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5 |
OCCUPATIONAL | |||||||
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Learning to Learn | |||||||
Program Yeterlilikleri/Çıktıları | Katkı Düzeyi | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Recognizes what he/she knows about his/her field or not.
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5 | |||||
2 |
Act the theoretical knowledge in real life with learning to learn approach.
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4 | |||||
3 |
Apply different methods and techniques with an innovative approach in his/her research.
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5 |
OCCUPATIONAL | |||||||
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Communication & Social | |||||||
Program Yeterlilikleri/Çıktıları | Katkı Düzeyi | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Apply the results obtained in accordance with voluntarism and social responsibility projects.
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5 | |||||
2 |
Establish a healthy contact with colleagues
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3 | |||||
3 |
Share the analyzes and obtained results with colleagues.
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3 | |||||
4 |
Cooperate with colleagues at international level with the help of foreign language competency.
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4 |
OCCUPATIONAL | |||||||
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Occupational and/or Vocational | |||||||
Program Yeterlilikleri/Çıktıları | Katkı Düzeyi | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Behave in accordance with ethical values regarding the collection, analysis and reporting of data.
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4 | |||||
2 |
Participate the design of work processes and systems with full quality.
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5 | |||||
3 |
Cooperate with other employees for the continuation of sustainability in the profession.
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3 |
DERSİN İŞ YÜKÜ VE AKTS KREDİSİ |
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Öğrenme-Öğretme Etkinlikleri İş Yükü | |||
Öğrenme-Öğretme Etkinlikleri | Etkinlik(hafta sayısı) | Süresi(saat sayısı) | Toplam İş Yükü |
Lecture & In-Class Activities | 14 | 3 | 42 |
Preliminary & Further Study | 13 | 3 | 39 |
Land Surveying | 0 | 0 | 0 |
Group Work | 7 | 4 | 28 |
Laboratory | 0 | 0 | 0 |
Reading | 0 | 0 | 0 |
Assignment (Homework) | 0 | 0 | 0 |
Project Work | 0 | 0 | 0 |
Seminar | 0 | 0 | 0 |
Internship | 0 | 0 | 0 |
Technical Visit | 0 | 0 | 0 |
Web Based Learning | 0 | 0 | 0 |
Implementation/Application/Practice | 14 | 2 | 28 |
Practice at a workplace | 0 | 0 | 0 |
Occupational Activity | 0 | 0 | 0 |
Social Activity | 0 | 0 | 0 |
Thesis Work | 0 | 0 | 0 |
Field Study | 0 | 0 | 0 |
Report Writing | 0 | 0 | 0 |
Final Exam | 1 | 1 | 1 |
Preparation for the Final Exam | 7 | 5 | 35 |
Mid-Term Exam | 1 | 1 | 1 |
Preparation for the Mid-Term Exam | 7 | 4 | 28 |
Short Exam | 0 | 0 | 0 |
Preparation for the Short Exam | 0 | 0 | 0 |
TOTAL | 64 | 0 | 202 |
Genel Toplam | 202 | ||
Toplam İş Yükü / 25.5 | 7,9 | ||
Dersin AKTS(ECTS) Kredisi | 8,0 |