Introduction to database design: database design and ER diagrams, entities, attributes and entity sets, relationships and relationship sets, additional features of the ER model, conceptual design with the ER model. JAVA: Introduction to Object Oriented Programming - Features of Java – Data types, variables and arrays – Operators – Control statements – Classes and methods – Inheritance. Introduction to information retrieval systems: definition of information retrieval systems, objectives of information retrieval systems, functional overview, relationship to database management systems, digital libraries, and data warehouses.
Data structure: Introduction to data structure, voting algorithms, inverted file structure, N-Gram data structures, PAT data structure, signature file structure, hypertext and XML data structures, hidden Markov models. Text Search Algorithms: Introduction to text search techniques, software text search algorithms, hardware text search systems. Introduction to the Internet of Things – Definition and Characteristics of IoT, Physical Design of IoT – IoT Protocols, IoT Communication Models, IoT Communication APIs IoT Compatible Technologies – Wireless Sensor Networks, Cloud Computing, Big Data Analytics, Communication Protocols, Embedded systems, IoT levels and templates Domain specific IoTs – Home, City, Environment, Energy, Retail, Logistics, Agriculture, Industry, Health and Lifestyle.
IoT and M2M - Software Defined Networks, Virtualization of Network Functions, Difference between SDN and NFV for IoT Fundamentals of IoT System Management with NETCOZF, YANG-NETCONF, YANG, SNMP NETOPEER. Introduction to Python - Python Language Features, Data Types, Data Structures, Flow Control, Functions, Modules, Packaging, File Handling, Data/Time Operations, Classes, Exception Handling Python Packages - JSON, XML, HTTPLib, URLLib, SMTPLib. Physical Devices and IoT Endpoints - Introduction to Programming Raspberry PI Interfaces (Serial, SPI, I2C) - Python program with Raspberry PI focusing on connecting external devices, controlling output, reading input from pins.
IoT Physical Servers and Cloud Offerings – Introduction to Cloud Storage Models and Communication APIs Web Server – Web Server for IoT, Cloud for IoT, Python Web Application Framework Design a RESTful web API.
OBJECTIVES
At this level, students must prepare for their careers, which may require them to listen, read, speak and write in English for both their professional and interpersonal communication in a globalized context.
SYLLABUS
MINIMUM REQUIREMENT
SUGGESTED SOFTWARE
Introduction to intellectual property: Introduction, types of intellectual property, international organizations, agencies and treaties, importance of intellectual property rights. Introduction to Finite Automata: Structural Representations, Automata and Complexity, Central Concepts of Automata Theory – Alphabets, Strings, Languages, Problems. Turing Machines: Introduction to Turing Machine, Formal Description, Immediate Description, Language of a Turing Machine.
To provide knowledge of concepts in software testing such as testing process, criteria, strategies and methodologies. Course Outcomes: Design and develop the best test strategies in accordance with the development model. To understand the variety of bad practices implemented in relation to the Business and Integration levels.
Introduction to UML: Importance of Object Orientation, Object Identity, Encapsulation, Information Hiding, Polymorphism, Generosity, Importance of Modeling, Modeling Principles, Object Oriented Modeling, UML Conceptual Model, Architecture. Factor Levels, Factor Summary, Ordered Factors, Comparison of Ordered Factors, Introduction to Data Frame, Subset of Data Frames, Extension of Data Frames, Classification of Data Frames. Database - Introduction to SQLite database, creating and opening a database, creating tables, inserting data for retrieval and etindelg, registering content providers, using content providers (insert, delete, retrieve and update).
The customer will be asked to insert an ATM card and enter a personal identification number (PIN) - both of which will be sent to the bank for verification as part of each transaction. A customer should be able to make a cash withdrawal from any eligible account linked to the card, in multiples of Rs. A customer must be able to make a deposit to any account linked to the card, which consists of cash and/or checks in an envelope.
A customer must be able to make a transfer of money between any two accounts linked to the card. A customer must be able to make a balance inquiry from any account linked to the card. The ATM will communicate each transaction to the bank and obtain verification that it has been authorized by the bank.
In the case of a deposit, a second message will be sent to the bank indicating that the customer has deposited the envelope. If the customer fails to deposit the envelope within the expiration period, or instead presses cancel, no second message will be sent to the bank and the deposit will not be credited to the customer.).
R AS CALCULATOR APPLICATION a. Using with and without R objects on console
DESCRIPTIVE STATISTICS IN R
READING AND WRITING DIFFERENT TYPES OF DATASETS
VISUALIZATIONS
CORRELATION AND COVARIANCE a. Find the correlation matrix
REGRESSION MODEL
MULTIPLE REGRESSION MODEL
REGRESSION MODEL FOR PREDICTION
CLASSIFICATION MODEL
CLUSTERING MODEL
Create an Android app that displays Hello + username and run it in the emulator. Develop an application that displays the names as a list and on selecting the name displays the candidate details on the next screen with a "Back" button. Develop an application that inserts some notifications into the notification area and every time a notification is inserted it should display a toast with the notification details.
Develop an application that shows all the contacts of the phone along with details like name, phone number, mobile number etc. Introduce some of the problems and solutions of NLP and their relationship to linguistics and statistics. Finding the structure of documents: introduction, methods, complexity of the approaches, performance of the approaches.
Topics include: software economics; software development life cycle; artifacts of the process; workflows; check points; project organization and responsibilities; project management and process instrumentation. The aim of the course is to introduce the basics of privacy-preserving data mining methods. The software quality challenge: the uniqueness of software quality assurance, the environments for which SQA methods are developed.
Software errors, errors and failures, Classification of the causes of software errors, Software quality - definition, Software quality assurance - definition and objectives, Software quality assurance and software engineering. Software Quality Factors: The need for comprehensive software quality requirements, Classifications of software requirements into software quality factors, Software quality factors for product operation, Quality factors for product revision software, Quality factors for product transition software, Alternative models of software quality factors, Who is interested in the definition of quality requirements. Software quality metrics: Objectives of quality measurement, Classification of software quality metrics, Process metrics, Product metrics, Implementation of software quality metrics, Limitations of software metrics.
Costs of software quality: Measures of costs of software quality measurements, The classical model of costs of software quality, An extended model of costs of software quality, Application of a quality management system for software costs, Problems with the application of software costs, quality measurements. Management and its role in software quality assurance: Top management quality assurance activities, departmental management responsibility for quality assurance, Project management responsibility for quality assurance. 0 0 2 1 Course objective: The purpose of this lab is to get an overview of the different machine learning techniques and can demonstrate them using python.
3 0 0 3 Course objectives: The purpose of the course is to provide the students with the conceptual framework and the theories underlying Organizational Behavior. Quality Metrics: Software Quality Metrics – Product Quality – Process Quality – Software Maintenance Metrics – Metrics Program Case Studies – Motorola – HP and IBM.
