Module 1: Exploring the subject matter of Economics What is Economics? Definitions – Importance of Economics for Engineers – Schools of thought The Economic Problem – Scarcity and Choice – Resource allocation – the question of What to produce, How to Produce and How to Distribute Output – its nature and Importance in developing countries – Economic Systems – Basics of Capitalism, Socialism, Mixed Economy, Market Economy and Third World Economies. Is Economics a Science? Distinction between Micro and Macro Economics. 

Software development lifecycle. Life Cycle models. Process models. Requirements specifications. Basic software architecture. Basics of software design. Introduction to UML: Class and Interaction Diagrams, Design patterns in software. Procedural design methodology, Software implementation. Testing, verification and validation. Static analysis. Introduction to software model checking. Software metrics. Software project management.

Database system architecture: Data Abstraction, Data Independence, Data Definition and Data Manipulation Languages. Data models: Entity-relationship, network, relational and object oriented data models, integrity constraints and data manipulation operations.

Relational query languages: Relational algebra, tuple and domain relational calculus, SQL and QBE. Relational database design: Domain and data dependency, Armstrongs axioms, normal forms, dependency preservation, lossless design.

Introduction: review of computer organization, introduction to popular operating systems like UNIX, Windows, Android, etc., OS structure, system calls, functions of OS, evolution of OSs. Computer organization interface: using interrupt handler to pass control between a running program and OS. Concept of a process: states, operations with examples from UNIX (fork, exec) and/or Windows. Process scheduling, interprocess communication (shared memory and message passing), UNIX signals. Threads: multithreaded model, scheduler activations, examples of threaded programs.

Classification of signals and systems, Types of signals, Transformation of independent variable, Periodic signals and Periodicity , Types of systems, Analysis of Continuous Time Signals and LTI systems: Convolution, Impulse response, Trigonometric and exponential Fourier series, Eigen functions of LTI systems, Fourier Transform, Magnitude and Phase Spectra, Properties of Fourier Transform, Laplace Transform, Region of Convergence, Properties, Linear Constant coefficient Differential Equations, State Space Matrix for continuous time systems.

Introduction to computer organization: Structure and function of a computer- Processing unit: Characteristics of CISC and RISC processors- Performance of a processing unit.

1. Design and hardware implementation of: 
   a. 2-bit Adder/Subtractor with XOR as well as NAND gates,
   b. 4:1 Multiplexer using universal gates and realization of Full Adder using Multiplexers,
   c. BCD Adder using two binary adders (IC based) and other gates,

Introduction: Notion of formal language. Language membership problem, why this is taken as the central problem of the subject. Finite automata and regular expressions: DFA, NFA (with and without transitions), their equivalence. Proof that FAs recognize, and regular expressions denote the same class of languages, viz., regular languages. Properties of regular languages: Pumping lemma and its use to prove non-regularity of a language, closure properties of class of regular languages, decision properties: converting among representations, testing emptiness, etc.

Probability Theory: Elementary concepts on probability – axiomatic definition of probability – conditional probability – Bayes’ theorem – random variables – standard discrete and continuous distributions – moments of random variables – moment generating functions – multivariate random variables – joint distributions of random variables – conditional and marginal distributions – conditional expectation – distributions of functions of random variables – t and χ2 distributions – Schwartz and Chebyshev inequalities – weak law of large numbers for finite variance case – central limit theorem for