Çift Anadal Programı

Introduction to academic genres. Key figures in particular areas of academic life. Synthesizing different sources. Key scientific figure. Reading about and listening to a scientific process. Choosing and describing a scientific process in speech and writing. Reports of different research methods. Lab report or literature search. Passive voice, adverbial clauses and adjective clauses. Understanding and using key vocabulary from a particular domain.

Key theories in particular areas of academic life. Technical diagrams. Key rhetorical features in a written argument. Future scientific developments in particular fields. Academic sources to write a review of literature. Presentation of the literature review. Language for describing part-whole relations in technical diagrams. Future tenses, noun clauses. Key academic vocabulary from a particular field.

Introduction to basic IT theory and terminology. Basic skills in a word processor programs, such as MS Word to create documents, format text, apply styles. Basic skills in a spreadsheet program, such as MS Excel, to create and format spreadsheets, including the use of mathematical formulas and to summarize given data in the form of graphics.

Basic methods and techniques of data mining. Relationship between databases, data warehouses, and data mining. Data mining functionalities: association, concept description, classification, prediction and clustering. Various algorithms for each type of functionality such as decision tree classification, artificial neural networks, Bayesian classification, logistic regression, K-means clustering. Applications and trends in data mining.

Sets of real numbers. Functions. Special functions. Symmetry, translations and reflections. Lines. Quadratic functions. Systems of equations. Exponential and logarithmic functions. Properties of logarithms. Limits and continuity. The derivative. Rules for differentiation. The chain rule. Derivatives of logarithmic and exponential functions. Implicit differentiation. Logarithmic differentiation. Higher order derivatives. Relative extrema. Absolute extrema on a closed interval. Concavity. The second derivative test. Asymptotes.

Propositional logic. Truth tables. Logical equivalences. Predicate calculus and quantifiers. Rules of inference. Proof methods and strategies. Sets. Set Operations. Functions. Sequences and summations. Divisibility. Modular arithmetic. Mathematical induction and strong induction. Recursive definitions and structural induction. Basic counting techniques. The pigeonhole principle. Permutations and combinations. Inclusion-exclusion. Relations. Equivalence relations. Graphs. Trees.

Counting methods. Basic topics in probability. Probability axioms. Sample space. Conditional probability. Random variables. Discrete random variables. Probability mass function. Expectations. Variance and standard deviation. Families of discrete random variables. Continuous random variables. Distribution function. Probability density function. Expected values. Families of continuous random variables. Pairs of random variables. Joint distribution function. Marginals. Joint probability density and mass functions. Functions of two random variables.

Introduction to statistics. Describing data and frequency distributions. Describing data and graphic presentation. Central tendency and dispersion measures. Probability and permutation and combination. Discrete probability distributions. Continuous probability distributions. Normal probability distribution. Sampling methods and distribution of sample statistics. Central limit theorem. Point estimation and confidence intervals.

Complexity of software development. Important models used in software engineering. Introduction to object-oriented fundamentals. Objects. Classes. Constructor. Destructor. Garbage collector. Static variables. Constants. Methods. Visibility. Scope. this operator. Abstraction. Encapsulation. Thinking in objects. Inheritance. Superclass. Subclass. Overriding. Overloading. Polymorphism. Casting. Binding. Interfaces. Abstract classes. Comparable and clonable interfaces. Exception handling. Advanced algorithms and data structures. Algorithm efficiency. Enterprise application development. Database programming. Multithreading. Parallel programming.

Problem solving and programming skills. Computational thinking. Abstracting. Analyzing problems and artifacts. Decomposition. Pattern recognition. Flowcharts. Basic data types. Variables. Pseudocode. Control structures: The sequence structure. Decision structure. Making choices. Logical structures: Compound logical operators. Repetition structures. Loops. Algorithm design. Examples.