MATH 105 • Final • Introduction to Finite Mathematics
Eğitmen
Ömer Faruk Altun
Co-founder & Head of Education
2011 yılında Endüstri Mühendisliği okumak için başladığım Sabancı Üniversitesi'nden 2018 yılında Bilgisayar Mühendisi olarak mezun oldum. 13 yıldır Altun ismiyle başta Sabancı Üniversitesi olmak üzere çeşitli okullarda Endüstri ve Bilgisayar Mühendisliği alanlarında ders vermekteyim. Unicourse'ta sunduğum derslerin yanında eğitim departmanının da sorumluluğunu üstlenmekteyim.
Geçme Garantisi
Derslerimize çok güveniyoruz. Dersi geçememen çok zor ama yine de geçemezsen paran iade.
Tüm koşullarPaketi Tamamla
🎓 Boğaziçi Üniversitesinde öğrencilerin %92'si tüm paketi alarak çalışıyor.
MATH 105 • Midterm
Introduction to Finite Mathematics
Dorukhan Özcan
1299 TL
MATH 105 • Final
Introduction to Finite Mathematics
Dorukhan Özcan
1299 TL
Konular
Linear Programming
Formulation
Example
Graphical Solution Method
Example
Example
Example
Alternative Optimal Solutions
Example
Counting
Basic Principles of Counting
Counting Examples
Permutations
Permutations Example
Groups and Circular Permutation Example
Identical Objects Example 1
Identical Objects Example 2
Identical Objects Example 3
Combination
n choose r
Committee Example 1
Committee Example 2
Ball Example 1
Ball Example 2
Classical Probability Concept
Sample Space and Events
Probability
Axioms of Probability
Some Rules
Coin Example
Dice Example
Card Example 1
Card Example 2
Ball Example
Set Example
Birthday Example
Conditional Probability
Conditioning Events
Total Probability Rule
Example 1
Example 2
Example 3
Example 4
Example 5
Example 6
Bayes' Rule and Independence
Bayes' Rule
Bayes' Rule Example 1
Bayes' Rule Example 2
Independence
Independence Example 1
Independence Example 2
Sample Final Problems
Linear Programming 1
Linear Programming 2
Linear Programming 3
Linear Programming 4
Counting 1
Counting 2
Counting 3
Counting 4
Counting 5
Counting 6
Counting 7
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Axioms of Probability 4
Axioms of Probability 5
Axioms of Probability 6
Axioms of Probability 7
Axioms of Probability 8
Axioms of Probability 9
Axioms of Probability 10
Axioms of Probability 11
Axioms of Probability 12
Conditional Probability 1
Conditional Probability 2
Conditional Probability 3
Conditional Probability 4
Conditional Probability 5
Conditional Probability 6
Conditional Probability 7
Conditional Probability 8
Independence 1
Independence 2
Independence 3
Conditional Probability and Independence
Conditional Probability and Independence
Bayes' Rule 1
Bayes' Rule 2
Bayes' Rule 3
Bayes' Rule 4
Bayes' Rule 5
Bayes' Rule 6
Bayes' Rule 7
Bayes' Rule 8
Bayes' Rule 9
Değerlendirmeler
Henüz hiç değerlendirme yok.
Ders İçeriği
Linear Programming
Formulation
Example
Graphical Solution Method
Example
Example
Example
Alternative Optimal Solutions
Example
Counting
Basic Principles of Counting
Counting Examples
Permutations
Permutations Example
Groups and Circular Permutation Example
Identical Objects Example 1
Identical Objects Example 2
Identical Objects Example 3
Combination
n choose r
Committee Example 1
Committee Example 2
Ball Example 1
Ball Example 2
Classical Probability Concept
Sample Space and Events
Probability
Axioms of Probability
Some Rules
Coin Example
Dice Example
Card Example 1
Card Example 2
Ball Example
Set Example
Birthday Example
Conditional Probability
Conditioning Events
Total Probability Rule
Example 1
Example 2
Example 3
Example 4
Example 5
Example 6
Bayes' Rule and Independence
Bayes' Rule
Bayes' Rule Example 1
Bayes' Rule Example 2
Independence
Independence Example 1
Independence Example 2
Sample Final Problems
Linear Programming 1
Linear Programming 2
Linear Programming 3
Linear Programming 4
Counting 1
Counting 2
Counting 3
Counting 4
Counting 5
Counting 6
Counting 7
Axioms of Probability 1
Axioms of Probability 2
Axioms of Probability 3
Axioms of Probability 4
Axioms of Probability 5
Axioms of Probability 6
Axioms of Probability 7
Axioms of Probability 8
Axioms of Probability 9
Axioms of Probability 10
Axioms of Probability 11
Axioms of Probability 12
Conditional Probability 1
Conditional Probability 2
Conditional Probability 3
Conditional Probability 4
Conditional Probability 5
Conditional Probability 6
Conditional Probability 7
Conditional Probability 8
Independence 1
Independence 2
Independence 3
Conditional Probability and Independence
Conditional Probability and Independence
Bayes' Rule 1
Bayes' Rule 2
Bayes' Rule 3
Bayes' Rule 4
Bayes' Rule 5
Bayes' Rule 6
Bayes' Rule 7
Bayes' Rule 8
Bayes' Rule 9
Geçme Garantisi
Derslerimize çok güveniyoruz. Dersi geçememen çok zor ama yine de geçemezsen paran iade.
Tüm koşullarSıkça Sorulan Sorular
Örneğin, Koç Üniversitesi - MATH 101 (Calculus) veya başka bir okulun benzer dersi olsun, paketlerimiz tam da o derse göre tasarlanır. Böylece nokta atışı çalışır, zaman kazanırsın.
Sınava özel videolar —konu anlatımları, çıkmış sorular ve çözümleri, özet notlar—içerir. Sınavda sıkça çıkan soruları hedefler. Eğitmenlerimiz, üniversitenin akademik takvimini takip ederek paketleri sürekli günceller. Böylece, gereksiz detaylarla vakit kaybetmeden başarını artırmaya odaklanabilirsin.