AIDS 4th Semester Syllabus

Unit 1DBMS Concepts and Architecture

DBMS concepts and architecture introduction · Database approach versus traditional file‑accessing approach · Advantages of database systems · Data models, schemas and instances · Data independence · Database language and interfaces · Overall database structure · Functions of DBA and designer · Entity‑relationship (ER) data model: entities and attributes, entity types · Defining the ER diagram · Concepts of generalization, aggregation and specialization · Transforming ER diagram into relational tables · Other data models: object‑oriented, network, and relational data models · Comparison among object‑oriented, network, and relational models

Unit 2Relational Data Models

Domains, tuples, attributes, relations and characteristics of relations · Keys and key attributes of a relation · Relational database schemas · Integrity constraints and referential integrity · Intension vs. extension · Relational query languages: SQL DDL and DML · Integrity constraints in SQL · Complex queries and various joins · Indexing, triggers, assertions · Relational algebra operations: select, project, join, division, outer union · Relational calculus: tuple‑oriented and domain‑oriented · Operations of relational calculus

Unit 3Database Design and Query Optimization

Normalization: introduction, normal forms, functional dependency · Decomposition, dependency preservation and lossless join · Issues with null‑valued and dangling tuples · Multivalued dependencies · Query optimization: introduction and optimization steps · Algorithms for implementing select, project, and join operations · Heuristic‑based optimization methods · Cost‑estimation based optimization methods

Unit 4Transaction Processing and Distributed Databases

Transaction processing concepts and transaction system · Testing of serializability, conflict‑serializable and view‑serializable schedules · Recoverability and recovery from transaction failures · Log‑based recovery and checkpoints · Deadlock handling · Concurrency control techniques: locking, timestamp protocols, validation‑based protocols, multiple granularity locking · Multiversion concurrency control and recovery with concurrent transactions · Introduction to distributed databases · Data mining, data warehousing · Object technology and DBMS: comparative study of OODBMS vs. DBMS · Temporal, deductive, multimedia, web and mobile databases

Unit 5Relational DBMS Study and NoSQL

Study of RDBMS through Oracle/PL‑SQL/MySQL: architecture, physical files, memory structures, background processes · Concepts of tablespaces, segments, extents and blocks · Dedicated server vs. multi‑threaded server · Distributed database features: database links and snapshots · Data dictionary and dynamic performance views · Security, role management, privilege management, profiles, invoker‑defined security model · SQL queries: data extraction from single and multiple tables, equi‑join, non‑equi‑join, self‑join, outer join · Special operators: LIKE, ANY, ALL, EXISTS, IN · Hierarchical queries, inline queries, flashback queries · ANSI SQL: anonymous blocks, nested blocks, branching and looping constructs · Cursor management: nested and parameterized cursors · PL/SQL exception handling, stored procedures with IN/OUT/IN‑OUT parameters · User‑defined functions and their limitations · Triggers, mutating table errors, INSTEAD‑OF triggers · Introduction to NoSQL databases

Unit 1Introduction to Software Engineering

Software Development Life Cycles (SDLC) · SDLC Models: Waterfall, V-Model, Prototype, Incremental, Evolutionary, RAD, Spiral · Project Planning and Metrics for Project Size Estimation · Project Estimation Techniques · Requirements Gathering and Analysis · Software Requirements Specification (SRS) · Software Product and Process Characteristics · Software Process Models and Evolutionary Process Models · Agile processes · Software Process customization and improvement, CMM · Product and Process Metrics · Functional and Non‑functional requirements · Requirement Sources and Elicitation Techniques · Analysis Modeling for Function‑oriented and Object‑oriented development · Use case Modeling · System and Software Requirement Specifications · Requirement Validation and Traceability

Unit 2Software Design, Analysis and Testing

Software Design Process · Design Concepts and Principles · Software Modeling and UML · Architectural Design, Views and Styles · User Interface Design · Function‑oriented Design · Component‑Based Design (SA/SD) · Design Metrics · Software Static and Dynamic analysis · Code inspections · Software Testing Fundamentals · Software Test Process · Testing Levels · Test Criteria · Test Case Design · Test Oracles · Test Techniques · Testing Frameworks · Test Plan · Test Metrics · Testing Tools

Unit 3Software Maintenance & Software Project Measurement

Need and Types of Maintenance · Software Configuration Management (SCM) · Software Change Management · Version Control · Change control and Reporting · Program Comprehension Techniques · Re‑engineering and Reverse Engineering · Tool Support for maintenance · Project Management Concepts · Feasibility Analysis · Project and Process Planning · Resource Allocation · Software effort, schedule, and cost estimation · Project Scheduling and Tracking · Risk Assessment and Mitigation · Software Quality Assurance (SQA) · Project Plan · Project Metrics

Unit 4Fundamentals of Agile Methodology

Introduction to Agile software development methodology · Agile development life cycle · Comparison of Agile vs Traditional (Waterfall) development · Agile Manifesto: Principles, Benefits, Challenges · Agile Values · Agile Model and its phases

Unit 5Software Development using Agile Methodology

Gathering requirements using Agile approach · User Stories: definition and characteristics · Generating User Stories · Agile estimation and planning · Implementation of Agile · Applying an Agile Mindset to a Project · Roles in Agile development · Agile Frameworks: Scrum, Kanban, Crystal, XP, ASD, DSDM

Unit 1Introduction to Data Science

Types of Data: structured and unstructured data · Data Science Road Map: Frame the Problem; Understand the Data; Data Wrangling; Exploratory Analysis; Extract Features; Model and Deploy Code · Graphical Summaries of Data: Pie Chart, Bar Graph, Pareto Chart, Histogram · Measures of central tendency of Quantitative Data: Mean, Median, Mode · Measures of Variability of Quantitative Data: Range, Standard Deviation and Variance · Probability: Introduction to Probability, Conditional Probability

Unit 2Unstructured Data Analytics

Importance of Unstructured Data · Unstructured Data Analytics: Descriptive, diagnostic, predictive and prescriptive data analytics based on case study · Data Visualization: boxplots, histograms, scatterplots, features map visualization, t-SNE · Overview of Advance Excel: Introduction, Data validation, Introduction to charts, pivot table, Scenario manager, Protecting data, Excel macro basics, Introduction to macros

Unit 3Statistical & Probabilistic analysis

Statistical & Probabilistic analysis of Data · Multiple hypothesis testing · Parameter Estimation methods · Confidence intervals · Correlation & Regression analysis, logistic regression · Shrinkage Methods, Lasso Regression, Bayesian statistics · L1 and L2 regularizations · Powerful Data Analysis techniques: SUMIFS, SUMPRODUCT, VLOOKUP/XLOOKUP, INDEX + MATCH, handling formula errors, dynamic array formulas, circular references, formula auditing, pivoting

Unit 4Data Manipulation With Pandas

Introduction to Pandas: understanding DataFrame, handling missing values, data operations, string manipulation, regular expressions, data cleaning, outlier detection · Visualization tools in Python: representation of pie chart, bar chart, histogram, scatterplots · Data analysis performance metrics: ROC curve, types of errors, overfitting & underfitting, model evaluation techniques (holdout, random sampling, cross‑validation, bootstrap) · Ensemble methods: bagging & boosting, gradient boosting, random forests, committee machines

Unit 5Introduction to Business Intelligence

Introduction to Business Intelligence, types of Business Intelligence, modern Business Intelligence tools · Data Science and Ethical Issues: unfair discrimination, reinforcing human biases, lack of transparency · Discussions on privacy, security, ethics, and the role of next‑generation data scientists

Unit 1Introduction to Operating Systems

Function · Evolution · Desirable Characteristics and features of an O/S · Operating Systems Services: Types of Services · Different ways of providing these Services – Utility Programs · System Calls

Unit 2Process Management

Concept of a process · Process State Diagram · Process based kernel · Dual mode of process execution · CPU scheduling algorithms · deterministic modeling · System calls for Process Management · Concept of Threads: User level & Kernel level Threads · Process Management in UNIX & Windows · Inter Process Communication: Real and Virtual Concurrency · Mutual Exclusion · Synchronization · Critical Section Problem · Solution to Critical Section Problem: Semaphores and their Operations and their implementation · Deadlocks: Deadlock Problems · Characterization · Prevention · Avoidance · Recovery · IPC in UNIX & Windows

Unit 3Memory Management

Different Memory Management Techniques – Partitioning · Swapping · Segmentation · Paging · Paged Segmentation · Comparison of these techniques · Techniques for supporting the execution of large programs: Overlay · Dynamic Linking and Loading · Virtual Memory – Concept · Implementation by Demand Paging etc. · Memory management in UNIX & Windows

Unit 4File Systems Management

File Concept · User’s and System Programmer’s view of File System · Disk Organization · Tape Organization · Different Modules of a File System · Disk Space Allocation Methods – Contiguous · Linked · Indexed · Directory Structures · File Protection · System Calls for File Management · Disk Scheduling Algorithms · File Systems in UNIX & Windows

Unit 5Input / Output Management

Principles and Programming · Input/Output Problems · Different I/O operations: Program Controlled · Interrupt Driven · Concurrent I/O · Asynchronous Operations · Logical structure of I/O function · I/O Buffering · Kernel I/O Subsystem · Introduction to Network, Distributed and Multiprocessor Operating Systems · I/O management in UNIX & Windows

Unit 1Numerical Methods – 1

Solution of polynomial and transcendental equations · Bisection method · Newton-Raphson method · Regula-Falsi method · Finite differences · Relation between operators · Interpolation using Newton’s forward and backward difference formulae · Interpolation with unequal intervals · Newton’s divided difference and Lagrange’s formulae

Unit 2Numerical Methods – 2

Numerical Differentiation · Numerical integration · Trapezoidal rule · Simpson’s 1/3rd and 3/8 rules · Solution of Simultaneous Linear Algebraic Equations by Gauss’s Elimination · Gauss’s Jordan · Crout’s methods · Jacobi’s · Gauss-Seidal · Relaxation method

Unit 3Numerical Methods – 3

Ordinary differential equations · Taylor’s series · Euler and modified Euler’s methods · RungeKutta method of fourth order for solving first and second order equations · Milne’s and Adam’s predicator-corrector methods · Partial differential equations · Finite difference solution two dimensional Laplace equation and Poission equation · Implicit and explicit methods for one dimensional heat equation · Bender- Schmidt and Crank-Nicholson methods · Finite difference explicit method for wave equation

Unit 4Transform Calculus

Laplace Transform · Properties of Laplace Transform · Laplace transform of periodic functions · Finding inverse Laplace transform by different methods · Convolution theorem · Evaluation of integrals by Laplace transform · Solving ODEs by Laplace Transform method · Fourier transforms

Unit 5Concept of Probability

Probability Mass function · Probability Density Function · Discrete Distribution: Binomial, Poisson’s · Continuous Distribution · Normal Distribution · Exponential Distribution