Coursework
List of relevant classes taken at Emory with descriptions
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Course Summary (CS170): Fundamental programming concepts, the Linux OS the X-window system, and the Java Programming Language. Emphasis on algorithm development and data structures.
Course Summary (CS171): Implementation and use of data structures such as Stacks, Queues, Linked Lists, Binary Search Trees, Hash Tables and Graphs; Introductory Algorithm Analysis; and Object Oriented design and programming with Java.
Course Summary: Elementary mathematics for Computer Science: proof writing, sets, functions, logic, quantifiers, finding and solving recurrence relations, simple probability, conditional probability, Baye's Theorem, and Permutations & Combinations.
Course Summary: C Programming, Elementary CPU and Computer Architecture, ASCII, Hex and Binary Representation and Conversion, and Assembly Language Programming (M68000).
Course Summary: Analysis, design and implementation of advanced data structures and algorithms. Algorithms include divide-and-conquer, dynamic programming, greedy methods, tree and graph traversal, with analysis emphasizing lower bounds, worst-case, and expected time complexity.
Course Summary: PHP and SQL Programming. Introduction to storage hierarchies, database models, consistency, reliability, and security issues. Query languages and their implementations, efficiency considerations, and compression and encoding techniques.
Course Summary: Foundations and problems of machine intelligence, application areas, representation of knowledge, constraint processing, AI programming languages, expert systems, design of an intelligent system.
Course Summary: Vectors, multivariable functions, partial derivatives, multiple integrals, surface area and volume, vector and scalar fields, Green's and Stoke's theorems, and Divergence Theorem.
Course Summary: Differential Equations course which covers first and second-order differential equations and systems of differential equations, with an emphasis placed on developing techniques for solving differential equations.
Course Summary: Systems of linear equations, matrices, determinants, linear transformations, eigenvalues and eigenvectors, QR factorization, and least squares.
Course Summary: An introduction to theoretical mathematics. Logic and proofs, operations on sets, induction, relations, functions.
Course Summary: Consumer theory (how individuals decide to consume goods), producer theory (how firms decide to use inputs and technology to produce goods and services), competitive firms, monopoly, game theory and oligopoly.
Course Summary: Macroeconomic issues such as growth, inflation, unemployment, interest rates, exchange rates, and economic growth; providing a unified framework to address these issues; the impact of different policies, such as monetary and fiscal policies, on the aggregate behaviors of economic agents.
Course Summary: Methods of collection, classification, analysis, and interpretation of economic data; measures of central tendency and dispersion; probability; estimation; hypothesis testing; regression analysis.
Course Summary: Introduction to construction and testing of econometric models; analysis and critique of general linear regression model; simultaneous equations models; computer program for regression analysis; applications.
Course Summary: The class draws on a variety of domains on how businesses can improve their decision making. The focus of the class is how businesses structure their decisions-making using mathematical approaches, probability, and data trends.
Course Summary: The course focuses on various models from microeconomics and on the mathematical tools used to analyze these models. The scope includes consumer behavior, theory of the firm, risk analysis, and game theory. The underlying mathematical tools come generally from constrained optimization of functions of several variables.
Course Summary: Introduction to the economics of Transfer Pricing.