Introduction to Computer Networks: History of Evolution of the Internet, Network Topology , Layered Protocol Stack, Point-to - point and broadcast communications, LAN, WAN, MAN, and the Internet. Delay analysis in circuit switching, message switching, and packet switching. Queuing models. 

Introduction to Machine Learning: Capacity, overfitting and underfitting, regularization techniques, hyperparameters, bias and variance, PAC model, Rademacher complexity, growth function, VC-dimension, model evaluation and selection, ML frameworks in python. 

Supervised Learning: Concepts of classification and regression, linear and ridge regression, perceptron, k-nearest neighbor classifiers, decision tree, logistic regression, naive Bayes, Gaussian discriminant analysis, linear models for classification and regression, multi-class classification techniques. 

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.