E-mail - Computer GK in Hindi | Bank PO , Clerk / Railway / SSC / Computer Assistance / All Gov. Exam

E-mail - Computer GK in Hindi | Bank PO , Clerk / Railway / CCC / SSC / Computer Assistance(State Level) / All Gov. Exam

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E-mail - Computer GK in Hindi | Bank PO , Clerk / Railway / CCC / SSC / Computer Assistance(State Level) / All Gov. Exam

E-mail [ Electric Mail ]

Definition : It is process of sending and receiving  message , files from one place to another place. ( Invented by Ray Tomlinson in 1971 )

OR

E-mail is similar to writing a letter to recipients but transmitted in electronic medium, It is also called Electronic mail.

Structure of Email address -  abs123@gmail.com

1. Here abs123 is userid. (यहाँ abs123 यूजरआईडी  हैं | ) 

2. Here gmail is domain name. (यहाँ  gmail डोमेन नाम  हैं | )

3. No space are allowed.

Other domain name -  

.com - commercial 

.edu - education 

.gov -  government

.mil -  military

.net -  network

.org - organization

Parts of Email -  

• Compose  - This option is used to send any E-mail to another person / place. Here we provides some option(functions) which is helpful - 

1. To - 
2. CC (Carbon Copy) - when we send any email, in carbon copy(cc) , sender address written in CC is displayed in remaining receivers inbox.
3. BCC (Blind Carbon Copy ) - 
4. Subject - The main headline(Title) of email is written in this place. ( इस स्थान में ईमेल का मुख्य हैडलाइन (शीर्षक) लिखा जाता हैं। )
5. Attachment - 
6. Insert Link(CTR + K) -
7. Send -  
8. Forward - The content / mail already present in mail box and it is sent to another person through forward option. ( यदि किसी व्यक्ति दवारा किसी ईमेल को भेजा जाता  है तो नयी ईमेल बनाने से बचने के लिए हम फॉरवर्ड का उपयोग करते है। )

• Inbox
• Starred
• Snoozed
• Sent mail (Send box)
• Important
• Chats
• Draft - The important documents /  mails / data / attachments can be stored but which is not sent , is stored in Draft.
• Spam - The unsolicited and  junk mails are stored in this place. ( इस स्थान पर अनचाही और जंक मेल संग्रहित होती हैं।  )
• Trash -  The deleted items from mail box is moved to Trash. It is similar to Recycle Bin. ( मेल बॉक्स से हटाए गए आइटम को ट्रैश में स्थानान्तरित कर दिया गया है। यह रीसायकल बिन के समान हैं।  )
• Categories- 

Email Service Provider : 1. Google   2. Yahoo   3. Hotmail   4. Outlook    5. MSN

Terminology which is used in E-mail - 

• Sign in
• Sign out
• Authenticatoin - The process of verifying the username and password is called. ( उपयोगकर्ता नाम और पासवर्ड को सत्यापित करने की प्रकिया को प्रमाणीकरण कहा जाता हैं |  )
• Sign up process - The process of creating an account by providing our details to the server for their confirmation.
• Captcha Code
• POP
• POP3
• SMTP ( Simple Mail Transfer Protocol ) - 
• IMAP ( Internet Message Access Protocol ) -  

Computer terminology -  

 " Protocol "  ,  " Topology "   ,  " DNS "   ,   " Web Server "    ,   " HTML "    ,   " TCP / IP "   ,    " Machine Code "

Syllabus of Machine Learning Using Python (A10.5-R5)

A Level - Syllabus of Module: A10.5-R5-Machine Learning Using Python

Introduction : The course would cover the spectrum of data analytics, machine learning, deep learning, natural language processing and computer vision. The student would dive straight into data analytics and applied machine learning and deep learning algorithms. 

A Level - Syllabus of Module: A10.5-R5-Machine Learning Using Python

Detailed Syllabus : 

(i) Advanced Python : Overview of Python language, Programming Constructs, Data Structures like lists, dictionaries, tuples, sequences and their manipulations. Python Functions. Modules and Packages, Exception Handling, NumPy Library, Broadcasting and numpy functions. Pandas Library, working with dataframes, loading csv, manipulating dataframes, Aggregation functions, Analysis. Visualization using matplotlib and Seaborn. 

(ii)Machine Learning : Categories of ML, Supervised, Unsupervised, Reinforcement, Semi-Supervised. Supervised Learning Models, Regression, Classification, Naive Bayes, Support Vector Machines, Decision Trees, K-nearest Neighbours, Ensemble Methods of Classification, Machine Learning Evaluation Metrics, Cross Validation.

(iii) Computer Vision : Introduction  to Computer Vision, Face Recognition and Detection with OpenCV, Face Recognisers, Training data, Prediction. 

(iv) Deep Learning : Artificial  Neural Networks and Model, ANN structure, Feed Forward Neural network, Back Propagation, Deep Learning Concepts, Convolution Neural Network (CNN), Neural Network using TensorFlow. Learning Algorithms, Error correction and Gradient Descent Rules, Perceptron Learning Algorithm. 

(v) Natural Language Processing  : Basics of text processing, Lexical processing, NLP tasks in syntax, semantics, and pragmatics. Applications like Automatic Summarization, Sentiment Analysis and Text Classification.  

Click Here for PDF - A Level - Syllabus of Module: A10.5-R5-Machine Learning Using Python

Syllabus of Artificial Intelligence Concepts and R Programming (A9.5-R5)

A Level - Syllabus of Module: A9.5-R5 –Artificial Intelligence Concepts and R Programming 

Introduction : Artificial Intelligence is the intelligence exhibited by machines or software. The application areas of artificial intelligence are very vast and so this is a field of study which is gaining importance day by day. This branch of engineering emphasizes on creating intelligent machines that work and react like humans. There are different dimensions for artificial intelligence, in which the decision taking capacity is most important. 

A Level - Syllabus of Module: A9.5-R5 –Artificial Intelligence Concepts and R Programming 

Detailed Syllabus :

(i) Introduction To Artificial Intelligence  : Introduction to Artificial Intelligence (AI), history of AI. Advantages of AI, need for AI for modern applications, Intelligent agents, structure of Agents, agent program: goal-based agents, utility-based agent, learning agents, agent environment, multi agent systems, components of intelligence. Foundations of AI based Systems. Introduction to Business Intelligence, Business Analytics, Data, Information, how information hierarchy can be improved/introduced, understanding Business Analytics, Introduction to OLAP, OLTP, data mining and data warehouse. Difference between OLAP and OLTP. Use of AI in data analytics. 

(ii) Applications of AI : Applications of AI, health care sector, finance sector, smart cars, devices and homes, travel and navigations, entertainment, security, automation, automobile industry.

 

(iii) Data Preparation and Machine Learning Basics : Learning Systems. Supervised and Unsupervised Learning. Tasks performed by Machine Learning Algorithms – Classification, Regression, Clustering, Association rule Mining. Linear Regression, K-Nearest Neighbor Classifier, K-Means Algorithm. Performance evaluation metrics of machine learning algorithmsAccuracy Score, Confusion Matrix, Root Mean Squared Error. 

(iv) R Programming R Programming: Basics - Vectors, Factors, Lists, Matrices, Arrays, Data Frames, Reading data. Data visualization –barplot, pie, scatterplot, histogram, scatter matrix. 

(v) Statistical Data Analysis : Statistical data analysis –Summary Statistics, Correlation and Regression, Probability distributions- Normal distribution, Poisson distribution, Binomial distribution Types of data- Structured, Unstructured and Semi structured data.

Click Here for PDF - A Level - Syllabus of Module: A9.5-R5 –Artificial Intelligence Concepts and R Programming

Syllabus of Internet of Things using Raspberry Pi (A10.4-R5)

A Level - Syllabus of Module: A10.4-R5-Internet of Things using Raspberry Pi 

Introduction : The module is designed to make students understand the basics of Single Board Computer (SBC) specifically Raspberry Pi. The purpose is for installation, configuring and using Raspberry Pi in different verticals in the connected world of Internet of Things (IoT). The genesis of this module lies around open source hardware/software. The file system and other basics of Linux operating system is discussed with respect to Raspberry Pi, along with installing and configuring new software. Raspberry host bundle of open source software and are being discussed in this module such as python programming language, interfacing hardware (GPIO programming) through Clanguage using wiringPi library. Visual programming editor Node-RED makes easy for novice to expert level programmer to interface hardware using easy flow based programming. This module provides the theoretical and practical aspects of installing different software on Raspberry Pialong with interfacing sensors, storing and/or publishing data over Cloud. Configuring software to make web server run on Raspberry Pi. 

A Level - Syllabus of Module: A10.4-R5-Internet of Things using Raspberry Pi

Detailed Syllabus : 

(i) Introduction to Single Board Computer – Raspberry Piand programming language Python  : Introduction –Single Board Computer (SBC) History, Architecture, working, characteristics, applications/ use-cases, Introduction to SoC. Introduction to programming through Python: Python Basics – Python IDE – IDLE, variables, input/output, operators, strings, control statements, loops, functions, Modules, Packages. Python List and Dictionaries – creating, accessing, iterating, enumerating, sorting. 

(ii) Configuring and Managing Raspberry Pi : Understand Raspberry Pi family - Selecting the model of Raspberry Pi, power supply, operating system distribution- NOOBS, raspbain, preparing operating system on SD-card. Using raspi-config command –change password, boot options, configure camera, etc. Networking – connecting to wired or wireless network. 

(iii) Linux Operating System Basics : Introduction –using Terminal to access File system, creating, moving, deleting files/folders, Privileges/file permissions, ownership, apt-get, pip Shell scripting – understanding and writing shell scripts, running scripts/command in background, creating aliases, pipes, running program or script automatically - on startup, as a service, at regular intervals

(iv) Hardware interfacing - GPIO programming : Introduction–General Purpose Input Output(GPIO) pins, understanding WiringPi, BCM pinout, classification of pins- I2C, SPI, UART, digital/PWM Controlling Hardware – Connecting LED, Buzzer, DC Motor, Digital Inputsbutton/push switch, toggling, debouncing, keypad, etc. Interfacing sensors-light, temperature, humidity, gases, etc. LCD interfacing. WiringPi – programming digital I/O’s using WiringPi (C language) library. Arduino-styled programming for Raspberry Pi. Advanced programming using Python– file handling, making web Requests from python, running Linux commands from python Python packages of Interest for IoT – JSON, XML, HTTPLib & URLLib 

(v) Raspberry Pi based IoT application use-cases : Web Server– simple python web server e.g. bottle, for controlling GPIO outputs through web. Display sensor readings on a web page. Configuring Apache-MySQL-PHP stack, to install WordPress. Sending data to public and/or private web server. Introduction to Node-RED – Using Node Red to make MQTT dashboard.

Click Here for PDF -A Level - Syllabus of Module: A10.4-R5-Internet of Things using Raspberry Pi 

Syllabus of Internet of Things: A Practical Approach (A9.4-R5)

A Level - Syllabus of Module: A9.4-R5-Internet of Things: A Practical Approach

Introduction : The module is designed to equip the students to understand the advanced concepts of Internet of Things (IoT) and its applications. The Internet of Things (IoT) is expanding at a rapid rate, and it is becoming increasingly important for professionals to understand what it is, how it works, and how to harness its power to improve business. This introductory course will enable learners to leverage their business and/or technical knowledge across IoT-related functions in the workplace. In the course, we will examine the concept of IoT. We will look at the ‘things’ that make up the Internet of Things, including how those components are connected together, how they communicate, and how they value add to the data generated. We will also examine cyber security and privacy issues, and highlight how IoT can optimize processes and improve efficiencies in your business. 

A Level - Syllabus of Module: A9.4-R5-Internet of Things: A Practical Approach

Detailed Syllabus : 

(i) Hardware Platform for Prototyping IoT Applications: Open IoT hardware platforms: ESP8266 - Architecture, Peripherals, NodeMCU architecture, Features, and its peripherals, pin diagram. Open Embedded IDEs: Ardunio IDE, familiarization and setting up for NodeMCU/ESP8266, Enabling libraries for application development. Programming: Overview of Arduino programming and interfacing 

(ii) Sensors, Actuators and its Interfacing : Sensors & Actuators: The principle of Sensing & Actuation, The sensors for IoT Applications, The operating principles of sensors & Actuators, Analog & digital sensors. The interfacing principles: Analog to Digital Converters, Sampling theory, ADC Classification, Digital to Analog converters. Protocols and its designs: I2C,SPI and CAN, Modern sensors interfacing with bus protocols. Interfacing Sensors-Actuators: Interfacing digital and analog sensors with NodeMCU, Interfacing Actuators with NodeMCU 

(iii) IoT - The Networking & Protocols : Overview: Network layer architecture, communication model, Introduction to Application layer protocols - http, https, telnet, ftp, Connection oriented vs Connection less protocols, Basics of IP Addressing. The IoT application protocols- MQTT, COAP, Its Applications. IoT physical layer connectivity solutions:WiFi, Bluetooth, Zigbee, Sub1Ghz Connecting IoT devices using IPv4 and IPv6 protocol. 

(iv) Webserver Basics for IoT Web servers : Socket and client basics, http, https servers, Web sockets Apache servers- Installation & familiarization, Configuring and personalizing web servers. Webserver -Tools, scripts & Languages: HTML basics- personalizing websites, creating buttons and text boxes on web pages. REST services, GET & POST methods, overview of CSS, JSS, PHP for modern web servers. Embedded Webserver localisation: Intranet vs Internet access, Development of local webserver using NodeMCU for remote monitoring, development of remote webserver for actuator application. Developing Embedded client & server model with NodeMCU. MQTT servers: MQTT broker, client basics, publishing and subscribing data, Publish and subscribe using open brokers. 

(v) The IoT Database Management & Cloud connectivity - Public & Private: Database management: MySQL, MySQL database creation, creation of remote and its database access. NoSQL based tools and its application. Overview of cloud: Cloud computing introduction, functioning of cloud computing, cloud architecture, cloud storage and services, Industrial applications. Discovery of Private and Hybrid Clouds- Introduction- Objectives, need for Privacy- Defining a private cloud- Public, Private, and Hybrid Clouds – A Comparison, Examining the Economics of the private cloud- Assessing capital expenditures- Vendor Private Cloud Offering. IoT cloud services: Private and public cloud for IoT, working principle, Features and comparisons. IoT cloud case studies: Thing speak cloud service, pushing data to thing speak from NodeMCU, developing smart environment monitoring and update to Thingspeak or open cloud.

(vi) Security for Next Generation IoT, IIoT Current Security & privacy Issues : Password Complexity, Account Enumeration, Secure Communication, Hardware / OTA - Over the Air communication, Cloud server security, IoT Privacy, IoT Ethics and Legal issues Penetration of Modern Technologies: Introduction to Industrial IoT, Security and privacy issues. 

Click Here for PDF - A Level - Syllabus of Module: A9.4-R5-Internet of Things: A Practical Approach

Syllabus of Information Security Management (A10.3-R5)

A Level - Syllabus of Module: A10.3-R5-Information Security Management 

Introduction : This module is designed to focus on information security skills and techniques to protect and secure organization's information assets and business systems. Students understand of various types of security incidents, threats and attacks, and learn methods to prevent, detect and react to incidents and attacks.

A Level - Syllabus of Module: A10.3-R5-Information Security Management 

Detailed Syllabus : 

(i) Network Fundamentals : Introduction to Ethernet, OSI layers, TCP/IP models, Functions/ protocols & devices at each layer, Protocol headers for frame, TCP, UDP, IP ,ICMP, applications layers like http, snmpetc, Network Topology, Working of Hub bridge, switch, router, UTM, remote administration of and managed network devices, Types of Networks, VLAN, Subnetting, NAT Working with Number systems, Fixed Length subnet masking, Variable Length subnet, masking, Classless Inter Domain Routing, Inter VLAN routing, Static Routing, RIP, RIPv2, OSPF, EIGRP, IGRP using IPv4, Routing in Ipv6. 

(ii) Introduction to cyber security and Attacks : Fundamentals of information security - CIA Triad, Cyber Security Controls, Logical Controls, Physical Controls, Tools & Techniques, understanding threats, attacks categories, hacking process, Vulnerability, Threat & Risk (with examples), Types of Attacks (DDOS, Phishing, Malware etc. with examples), Threats at Client systems (malware, social engineering, open ports, etc.) Threats to Network, Web, Storage & Devices, Understanding the network security, Mitigation Techniques, fundamental of web/mobile application security, Web Application Attacks (SQL Injection, Cross site scripting etc.), Mobile Application Attacks, data center security, cloud computing and data security.

(iii) Cryptography : Data Transmission and Organization, error detecting and correcting codes, need of cryptography. Cryptology fundamentals, Symmetric-Asymmetric cryptography & cryptographic algorithms, Private key encryption, Public key encryption, Protocols, Key management, including key generation, key storage, Key exchange, Encryption folders(Graphical/ using cipher), Data recovery agent, Symmetric key encryption algorithm, DES/3DES, IDEA,RC5, AES, Public key algorithm, RSA & ECC, Diffie-Hellman key exchange, Hash functions, MD5-message digest algorithm, SHA-1 Secure Hash algorithm, HMAC, Applications of cryptography- Secure Email PGP, SSL TLS S/MIME, File Encryption IPsec, IOT Attacks against encryption, Public Key Infrastructure Understanding digital certificates and signatures.PKI Standards and Management, X.500, X.509, ETF, IRTF. 

(iv) Network Security and countermeasures : Securing Networks, Network security devices– Router, ACL, firewalls, types of firewalls, configuration and deployment, overview of IDS, Network-based IDS (NIDS), Host-based IDS, Overview of IPS, Host-based IPS, (HIPS), Network-based IPS(NIPS), UTMTMG threat management gateway, network security tools (scanners, sniffers etc) and Countermeasures. wireless security, securing wireless networks: wireless overview, Bluetooth, 820.11 

(v) Web Server and Application Security : Client-Server Relationship, Vulnerabilities in web server and applications, Attack methods, Buffer overflow, SQL injection, cross site scripting, session hijack etc., Secure Coding Practices, OWASP top 10 vulnerabilities and mitigation techniques, Web Application vulnerability scanning, tools (Nessus), Web application security challenges 

(vi) Security Auditing : Audit planning (scope, pre-audit planning, data gathering, audit risk), Risk management, Overall Audit Risk, Risk based approach, Evidence, Evidence gathering techniques, Sampling, Control Self-Assessment, Risk analysis, Purpose of risk analysis, Risk based auditing, Types of Control, Risk Assessment using Simple Risk or Eramba (Open source Tools), 3 phase approach – Risk assessment IT/IS Audit, Log analysis, Using Microsoft Security Assessment Tool, Using Microsoft Security Baseline Analyzer, Configuring Windows File system auditing. Event ID Log Analysis, OS and Application specific auditing, Performing Risk Assessment based on ISO27001 using ISO27001 security toolkit, Preparing Audit Questionnaire and Performing Audit for ISO27001 Standard.

(vii) Cyber Law and IT Act 2000 : Information Technology Act 2000 (as amended in 2008), Rules under Information Technology Act 2000. The Rule of Cyberspace. Cyber Law – Policy Issues and Emerging Trends Online Contract. Digital Signature Cyber Crime, Data Protection, Liability of Intermediary, Copyright and Internet. Domain Name Dispute, Harmful content in Internet, Case Studies. 

(viii) Cyber Forensics : Digital Evidence, identification of digital evidence, Cyber forensics Processes Identification, Preservation, seizure and acquisitions, Analysis, authentication and presentations, fundamental of Incident response and handling, Reporting, mitigation, Volatile evidence collection and analysis, disk imaging and analysis, Investigating Information-hiding, analysis of e-mail, Tracing Internet access, Understanding importance of report, writing of reports, generating report finding with forensics tools, Chain of custody forms, Laboratory documents and procedures. 

Click Here for PDF - A Level - Syllabus of Module: A10.3-R5-Information Security Management

Syllabus of Network Management (A9.3-R5)

A Level - Syllabus of Module: A9.3-R5-Network Management

Introduction :  This course will allow students to develop background knowledge as well as core expertise in networking and data communication technologies, which is one of the fastest growing industries in today’s world. It forms an integral part of the modern Information and Communications Technology (ICT) in any organizations. Starting from intranet/extranet in small offices to the World Wide Web, principles of networking and data communication technologies DCN play an important role in designing any modern telecom infrastructure. A major ramification of the fantastic growth of telecommunications and networking is a dramatic increase in the number of professions, where an understanding of Computer Networking is essential for success. This course is designed with this new mix of students in mind. The course, being the first one on telecommunication and Computer networking in the NIELIT hierarchy, starts from the very basics of communication technology and goes up to the Internet, spanning all the five layers of TCP/IP model. The students will be exposed to communication principles, different types of media, modulation techniques, multiplexing, switched networks, the Internet, TCP/IP suite, network security, mobile wireless communication, fibre-optic communications and the state-of-art networking applications. 

A Level - Syllabus of Module: A9.3-R5-Network Management

Detailed Syllabus :

(i) Introduction To Computer Networks : Introduction: Definition of a Computer Network; What is a Network?, Components of a computer network: Use of Computer networks; Networks for companies, Networks for people, Social Issues: Classification of networks; Based on transmission technology, Based on the their scale, Local Area Networks(LANs), Metropolitan Area Networks (MANs), Wide Area Networks(WANs), Computer topologies: Physical vs Logical Topology, Types of topologies: Linear Bus Topology, Ring Topology, Star Topology, Hierarchical or Tree Topology, Topology Comparison, Considerations when choosing a Topology, Modes of communication: Simplex, Half Duplex, Full Duplex, Concept of Channel, Sender and receiver with Communication process 

(ii) Introduction: Networks Layers / Models : Protocol hierarchy, Design issues for the layers, Merits and De-merits of Layered Architecture, Service Primitives: Reference models; The OSI Reference Model, The TCP/IP Protocol Model, Comparison of the OSI Reference Model & the TCP/IP Protocol Models: Network standardization; Who's who in the telecommunication world?, Who's who in the standards world, Who's who in the Internet standards world?, TCIP/IP Protocol Suite. 

(iii) Physical Layer : Introduction: Basic Functions of Physical Layer, Digital Signals: Bit rate, Bit length, Transmission of digital Signals, Analog Signals: Amplitude, Phase, Frequency, Wavelength, Transmission Impairments, Data Rate limits: Noiseless Channel: Nuyquist Bit Rate, Noisy Channel: Shannon capacity, Performance: Bandwidth, Throughput, Goodput, Latency (delay), Jitter. Concept of Serial and Parallel transmission, Switching; Circuit switching, Message switching, Packet switching, Virtual Switching, Multiplexing; FDM – Frequency division multiplexing, WDM – Wavelength division multiplexing, TDM – Time Division Multiplexing: Synchronous and Statistical, Transmission Media: Guided Media, Unguided Media, PSTN, Modems, DSL and other standards, Cable Networks: HFC,CM,CMTS. 

(iv) Data Link Layer : Introduction, Basic functions of Data Link Layer (LLC and MAC Sublayers): Framinng, CRC, Checksum, Protocols:Stop andWait, Go- Back-N, Selective Repeat, Piggybacking, HDLC, Point to Point, Multiple Access: Random Access :CSMA / CA, CSMA / CD, Controlled Access: Reservation, Polling, Token Passing,Wired LANS: IEEE Standards,Wireless LANs: IEEE Standards. 

(v) Network Layer : IPv4 Addressing, IPv4 Subnetting: CIDR, VLSM, NAT, NAT Types, IPv6 Addressing, Transition from IPv4 to IPv6, Address Mapping: ARP, RARP, BOOTP, DHCP, ICMP, ICMPv6 and IGMP, Concept of Forwarding of Packets by Routers, Unicast Routing Protocols: Distance Vector, Link State, Path Vector with examples of each. 

(vi) Transport Layer : Introduction, Basic Functions of Transport Layer: Client server Process with Port Numbers concept in detail, Concept of Socket Multiplexing vs De-multiplexing, Connectionless vs Connection Oriented, Reliable vs Unreliable, UDP in detail, TCP in detail. 

(vii) Congestion Control : Flow control vs. congestion control. Congestion Basics, Congestion Control: OpenLoop Closed-Loop, Concept of Quality of Service, techniques to improve QoS. 

(viii) Application Layer : Basic Function of Application Layer, Concept of Namespace and DNS, Basics of Remote Logging (telnet and ssh), E-mail: Architecture, Introduction to SMTP, POP, IMAP protocols, File Transfer: FTP, Anonymous FTP and TFTP, Concept of www and HTTP: www, http, https protocols, Basics of Network Management System: SNMP protocol 

(ix) Networking Devices : Introduction; Goal of networking devices: Repeaters and their use, Hubs, Bridges, Managed vs Non Manageable switches, L-2 Switches, L-3 Switches, Stackable Switches, Concept of Collision Domain, Working of Hubs and Switches, Concept of Port Density, Concept of Broadcast Domain, Routers: Dedicated Hardware versus Server-Based Routers, Advantages and Disadvantages of dedicated hardware routers, Drawbacks of Routers, Gateways: Advantages of Gateways, Gateways Functionality, Other Devices: Brouter, Proxy Server, Wireless Access Point (WAPs)/Wireless Router, Wireless LAN Extender and Wireless LAN Controller 

(x) Fundamentals of Mobile Communication : Introduction to wireless communication, wireless transmission:frequencies & regularion, signals, antena, multiplexing, modulation, spread spectrum & cellualr system. Evolution of Mobile Generation Technologies: 1G, 2G, 3G, 4G and 5G. 

Click Here for PDF - A Level - Syllabus of Module: A9.3-R5-Network Management

Syllabus of Full Stack Web Development using MVC Framework (A10.2-R5)

A Level - Syllabus of Module: A10.2-R5-Full Stack Web Development using MVC Framework 

A Level - Syllabus of Module: A10.2-R5-Full Stack Web Development using MVC Framework 

Detailed Syllabus :  

(i) MVC Infrastructure Basics. PHP Frameworks& Introduction to CakePHP : Introduction to MVC, What are Model-View-Controller, Why use framework in the project (conventional vs. MVC project), Introduction to PHP Frameworks i.e Zend, CodeIgniter, Laravel. Installation of CakePHP, CakePHP folder structure, File naming conventions, Important config file (core.php, database.php) 

(ii) Models :  Models - Different models of databases and interaction between databases. Creating up model for a database, Accessing and manipulating table data using find, save, update methods of the model, Deleting Data, User defined functions in model, data validations.

(iii) Controller and Views : Application flow –Creating Controller Function, How Controller interact with model, how controller interact with views. CakePHPhelpers, Most commonly used helpers like Form, HTML, Session, Cookie etc, Create views and custom layouts 

(iv) Php Basics and Conditional Logic :  PHP introduction, Environment setup in different platforms, concept of Server-side scripting language and client side scripting language, Script syntax, How to declare variable and data types, Constants, Arrays, Strings, Web concepts, Decision making statements, loop types, operators 

(v) Functionsand Error handling  : What is Functions, Creating PHP functions, PHP functions with parameters, Argument by reference, setting default values for function parameters, dynamic function calls, regular expressions, Date and time functions ,Built-in functions, file inclusion, file manipulations 

(vi) Object Oriented Programming  :What is Object Oriented Concepts, Defining classes, Creating Objects, Member functions, The new keyword and Constructor ,Destructor, Access method and properties using $this variable, Inheritance& code reusability, Function overriding, Access Specifies- private, public and protected members, Static properties and method, Class constants, Polymorphism, Parent:: &self :: keyword, Instance of operator, Abstract method and class, Interface , Final, Exceptional handling. 

(vii) MySQL Installation and Basics Database  : Introduction, MySQL installation on various platforms, MySQL connection, Database creation, Database Manipulations- Add, Edit, Retrieve and Delete. Table creation and table manipulations- Add Edit, Retrieve and Delete, Like clause, Sorting, Group Functions with having clause 

(viii) Advance Queries and Data Manipulation using PHPand MySQL : Joins, Handling NULL Values, Regular Expressions, , ALTER Command, Indexes, Temporary Tables, Database Handling Duplicates, SQL Injections. Creating user login form, Registration Form using database, User Authentication, Search, Update, Delete Users and Data. Fetching the data from database 

(ix) Creating Dynamic Forms using CakePHP Html Helpers : Introduction to basic html form, get, post methods, Generate form elements like input boxes, dropdowns, radio buttons, and links using CakePHP html helper, Form validation using Model validation definitions, Create, retrieve and delete cookies, Create, retrieve and delete session variables, File handling in CakePHP (create, delete, read files), CakePHP Global variables and their use .

Click Here for PDF - A Level - Syllabus of Module: A10.2-R5-Full Stack Web Development using MVC Framework 

Syllabus of Web Application Development Using PHP (A9.2-R5)

A Level - Syllabus of Module: A9.2-R5-Web Application Development Using PHP

Introduction : The combination of PHP and MySQL is the most convenient approach to dynamic, database-driven web design. Flexible, scalable, extensible, stable, open—PHP is all of these and more, which is why it’s one of the most popular programming toolkits in the world. Today, more than 20 million domains use PHP, including Facebook and Yahoo. PHP is easily embedded with HTML, and is used to manage dynamic content and the databases of websites or, we can say, Web applications. We can use PHP with many popular databases like MySQL, PostgreSQL, Oracle, Sybase, Informix and Microsoft SQL Server. So, using PHP is also good economics for organizations: it allows them to save on licensing fees and expensive server hardware, while simultaneously producing higherquality products in shorter time frames. Any would-be developer on a Unix/Linux or even a Windows/Apache platform will need to master these technologies. At the same time, JavaScript is important, as it provides in-browser dynamic functionality and, through Ajax, hidden communication with the web server to create seamless interfaces. In conjunction with CSS, these technologies integrate to provide a formidable array of powerful web-development tools. 

A Level - Syllabus of Module: A9.2-R5-Web Application Development Using PHP

Detailed Syllabus : 

(i) Introduction to the Website Development : Introduction of Web Site: Concept of Website and Web Pages, types of Websites Introduction to Open source Technologies: Operating system, Web Server, Database, Scripting Languages Platforms for website development: LAMP,WAMP and MAMP, Scripting language. 

(ii) Introduction to Linux Operating System : Linux Operating System: Topics- Introduction, Installation, Linux Architecture, Boot Process, Kernel, System Initialization. Different flavours of Linux, Review of Basic Commands and Editors: Topics – Introduction to NetBeans, Installation and Configuring NetBeans, gedit, Notepad++, Configuring Servers: Installation of PHP and MySQL on Linux Operating System, Installation of Net Beans IDE and its configuration, Configuration of Apache Server 

(iii) Design of Web Pages :  Basic HTML:HTML Basics, HTML Elements, HTML Attributes, HTML Headings, HTML Paragraphs, HTML Styles, HTML Formatting, HTML Quotations, HTML Links, HTML Table, HTML Lists, HTML Blocks, HTML Classes, HTML IFrames etc. HTML Forms: HTML Form Elements, Input Types, Input Attributes. CSS: CSS Introduction, CSS Types, CSS Padding, CSS Id & Class, Styling Backgrounds Fonts, Links, CSS Border, HTML5 

(iv) Client Side Validations using Various Techniques : Java Script: Java Script Introduction, Variable declaration, Operators, Control Statements, Error Handling, understanding arrays, Built in Functions, User defined Function, HTML Forms and Java Script, HTML DOM, Validations using Java Script AJAX: Introduction to AJAX, XML Http Request Object, Response Handling, AJAX Components, AJAX Framework, HTML in AJAX, XML and AJAX, Validations using AJAX JQUERY: JQUERY Introduction, JQUERY library, JQuery Selectors, JQuery Filters, Working with JQuery Events, JQuery and HTML Forms, Validations using JQuery 

(v) Server side programming language PHP : Introduction of Php: Programming Concepts, Architecture of web application, PHP Data Types and basics Control Structures: Conditional statement, if, else, case, for, while loops Arrays in PHP: Types of Arrays, Array attributes, Associative arrays, Array functions. PHP Functions: String and other functions in PHP, Super global, PHP Functions, Types of Function: User Defined Function and Inbuilt Functions, PHP Email Function etc. Object Oriented Concepts: Classes, defining a class and its usage, Constructor, Inheritance, Exception Handling, Use of include and require. PHP Forms methods: GET, POST & REQUEST, creating user forms. File handling in PHP: Uploading files and images, Using file system in PHP. 

(vi) Database Connectivity with PHP and MySQL : Creation of Database Connection file, Database connectivity, using MySQL functions in PHP. Server-side validations. Inserting, Updating, deleting data using PHP and MySQL through forms, Bind Parameters for Database Queries, Using MySQL Store procedures in PHP, Database server configuration using IPv4 and IPv6, Fetching Data from Database server. 

(vii) Web Services &Security Vulnerabilities : Web service architecture & Introduction, Session and cookies, Authentication and Authorization, storing hashed passwords in the database, Login and Logout operation, Access Control Filter, Session based and cookie-based login, Using security features etc. SQL Injection, Cross Site Scripting, Broken Authentication and Session Management, Insecure Direct Object References, Cross Site Request Forgery, Security Misconfiguration, Insecure Cryptographic Storage, Failure to restrict URL Access.

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Syllabus of Data Science Using Python (A10.1-R5)

A Level - Syllabus of Module: A10.1-R5-Data Science Using Python 

Introduction : Data science is an interdisciplinary field that uses scientific processes and various algorithms to extract knowledge and insights from data which may be structured and unstructured. Python has gathered a lot of interest recently as a choice of language for data analysis/science. Python is a free and open source and a general-purpose programming language which is easy to learn. Python, due to its versatility, is ideal for implementing the steps involved in data science processes. Python is being used for web development, data analysis, artificial intelligence, and scientific computing. The three best and most important Python libraries for data science are NumPy, Pandas, and Matplotlib. NumPy and Pandas are used for analyzing and exploring with data. Matplotlib is a data visualization library used for making various types of graphs depicting the analysis.

A Level - Syllabus of Module: A10.1-R5-Data Science Using Python

Detailed Syllabus : 

(i) Python Language, Structures, Programming Constructs : Review of Python Language, Data types, variables, assignments, immutable variables, Strings, String Methods, Functions and Printing, Lists and its operations, Tuples and Dictionaries programs, Slicing strings,lists, tuples. 

(ii) Data Science and Analytics Concepts : What is Data Science and Analytics? The Data Science Process, Framing the problem, Collecting, Processing, Cleaning and Munging Data, Exploratory Data Analysis, Visualizing results. 

(iii)Introduction to NumPy Library : Numpy - Array Processing Package, Array types, Array slicing, Computation on NumPy Arrays – Universal functions ,Aggregations: Min, Max, etc., N-Dimensional arrays, Broadcasting, Fancy indexing, sorting arrays, loading data in Numpy from various formats. 

(iv) Data Analysis Tool : Pandas : Introduction to the Data Analysis Library Pandas, Pandas objects – Series and Data frames, Data indexing and selection, Nan objects, Manipulating Data Frames, Grouping, filtering, Slicing, Sorting, Ufunc, Combining Datasets- Merge and join. Query Data Frame structures for cleaning and processing, lambdas. Aggregation functions and applying user defined functions for manipulations. 

(iv) Statistical Concepts and Functions : Statistics module, manipulating statistical data, calculating results of statistical operations. Python Probability Distribution, Functions like mean, median, mode and standard deviation. Concept of Correlation and Regression. 

(v) Matplotlib : Visualization with Matplotlib, Simple line plots, scatter plots, Density and Contour plots – visualizing functions, Multiple subplots, Plotting histograms, bar charts, scatter graphs and line graphs. 

(vi) GUI – Tkinter : Tk as Inbuilt Python module creating GUI applications in Python. Creating various widgets like button, canvas, label, entry, frame, check button, label etc. Geometry Management: pack, grid, place, organizing layouts and widgets, binding functions, mouse clicking events. Building the complete interface of a project. 

(vii) Machine Learning : The Next Step What is Machine Learning? Types of Machine Learning Algorithms, Training the data and Introduction to Various Learning Algorithms. Applications of Machine Learning. 

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Syllabus of Big Data Analytics Using Hadoop (A9.1-R5)

A Level - Syllabus of Module: A9.1-R5-Big Data Analytics Using Hadoop 

Introduction : The purpose of this module is to provide skills to students to analyze and process large volume of data using tools and techniques. It provides theoretical background as well as in-depth knowledge of Software/ packages that are used in analyzing the voluminous data.

A Level - Syllabus of Module: A9.1-R5-Big Data Analytics Using Hadoop

Detailed Syllabus : 

(i) Analyze and Define Business Requirement : Introduction to Business Intelligence, Business Analytics, Data, Information, how information hierarchy can be improved/introduced, understanding Business Analytics, Introduction to OLAP, OLTP, data mining and data warehouse. Difference between OLAP and OLTP. Introduction to database, characteristics of data in database, DBMS, advantages of DBMS, file-oriented approach versus Database-oriented approach to Data Management, disadvantages of file- oriented approach. A brief overview of relational model. Definition of relation, properties of relational model, Concept of keys: candidate key, primary key, alternate key, foreign key, Fundamental integrity rules: entity integrity, referential integrity. SQL statements: Insert, delete, update and select. Join, union. 

(ii) Introduction to Operating System : Introduction to Ubuntu Operating System, Managing files and folder through command line and Desktop. Basic Ubuntu commands like ls, mkdir, clear, rm. Creating users and groups in Ubuntu. User priviledges and roles (chown and chmod commands),gedit editor. Secure shell configuration, configuring. bashrc and environment files.

(iii) Java Programming : OOPS Principles, an Overview of Java Object-Oriented Programming, Data Types, Variables, and Arrays, Operators-Arithmetic Operators, The Bitwise Operators ,Relational Operators, Boolean ,Logical Operators, Programming Constructs, Methods and Inheritance, The basic Java I/O Classes and String Handling Exception-Handling Fundamentals, Exception Types, Uncaught Exceptions, Using try and catch , Displaying a Description of an Exception ,Multiple catch Clauses , Nested try Statements , Throw throws finally Java’s Built-in Exceptions Packages, Access Protection, Importing Packages and Interfaces Java Swing and its controls like JTextField, JLabel, JComboBox, JTable, JButton, JScrollBar, JOptionPane and JMenu. Java Database Connectivity JDBC-ODBC Bridge JDBC Drivers Creating DSN Driver Manager, Connection, Statement, Result Set. Connecting Java with Database. 

(iv) Hadoop Framework and Map-Reduce Programming Technique : Big Data Concepts, Need for analyzing Big Data, its roles in Business Intelligence and decision making. Big Data, Hadoop Architecture, Hadoop ecosystem components, storage, Hadoop Distributed File System (HDFS), Single node installation. Multi node installations. Cluster Architecture, Cluster configuration files Hadoop commands, Hadoop Server Role, name Node, secondary node, data node, file write and read. Shell commands, Accessing files on HDFS and local machine, Map Reduce Framework, Developing Map Reduce Programs, structure of Map Reduce program, 

(v) Analysing Data Using HIVE : Introduction to HIVE, installing HIVE, Data types, HIVE shell, HIVE commands, HIVE SQL, creating database and tables, bulk loading of data, SQL DML statements, SQL Join, HIVE Functions, Complex Data types, UDF in Hive using Java 

(vi) Basics of R Programming and RHIVE : R Overview, Basic Syntax, Data types, R Control constructs like loop and conditional, R Function. Connecting R with Hive. 

(vii) HIVE JDBC Connectivity : Starting HIVE in client-server mode, beeline, mapping HIVE datatype with Java datatypes, Connecting Java with HIVE. Integrating Java Swing, HIVE and JDBC for developing front end application. 

(viii) Introduction to HBASE, PIG and JAQL : HBASE introduction, integration with Hadoop, HBase Shell, introduction to JAQL data model, JAQL shell, introduction to JSON files and accessing JSON files through JAQL. Introduction to PIG.

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Syllabus of Systems Analysis, Design and Testing (A8-R5)

A Level - Syllabus of Module: A8-R5-Systems Analysis, Design and Testing 

Introduction : The module is designed to equip a person to understand System Analysis and Design aspects. It provides theoretical background as well as in depth knowledge through case studies. This module covers both structured and Object-oriented techniques to analyse and design software. 

A Level - Syllabus of Module: A8-R5-Systems Analysis, Design and Testing

Detailed Syllabus : 

(i) Introduction  : System Definition and concepts, types of systems, systems user, designers, analysts, introduction to simple system development process- initiation, analysis, design, coding, testing, implementation and maintenance. Basic principles of successful systems, Role and Need of Systems Analyst. Qualifications and responsibilities, System Analysis as a Profession. 

(ii) Requirement Gathering and Feasibility Analysis : System requirements specification, Classification of requirements as strategic, tactical, operational and statutory, Requirement gathering techniques- interview, questionnaire, on-site observation, document observation, selecting appropriate technique, Feasibility analysis, deciding project goals, examining alternative solutions, Cost Benefit Analysis, quantifications of costs and benefits, payback period, system proposal preparation for managements, parts and documentation of a proposal 

(iii) Structured Analysis : Data flow diagrams, case study for use of DFD, good conventions, Levelling of DFDs, Levelling rules, Logical and physical DFDs, Software tools to create DFDs. Preparation of Software Requirement Specification 

(iv) Structured Design : Entity relationship model, E-R diagrams, Relationships cardinality and participation, Normalizing relations, various normal forms and their need, Some examples of relational data base design. Data input methods, designing outputs, output devices, designing output reports, screen design, graphical user interfaces, interactive I/O on terminals. Application Architecture, server-based architecture, client-based architecture, n-tier architecture, Program design- structured chart. Preparation of Design Specification Document, 

(v) Object Oriented Modelling using UML : Object Oriented (OO) Development Life Cycle and Modelling. Static and dynamic modelling. Comparison of OO and Module-oriented Approach. Modelling using UML; class diagram, use case diagram, object diagram, package diagram, activity diagram, interaction diagrams, sequence diagram, state transition diagram. Deployment diagram, component Diagram. 

(vi) Testing : Software Testing, need for software testing, types of testing, Functional Testing-unit testing, integration testing, user acceptance. Non-functional Testing-performance, stress testing, peak load testing, Maintenance Testing-Regression Testing. 

(vii) System Implementation and Maintenance : Planning considerations, Conversion methods, procedures and controls, System acceptance criteria, System Evaluation and Performance, Testing and Validation. Preparing, User Manual, Maintenance Activities and Issues. 

(viii) Other Software Development Approaches : Different Software Development approaches-waterfall model, prototype, rapid application development, spiral, agile development, DevOps development methodology. Distributed System, centralized versus distributed system, components of distributed system-processes, interfaces and data. Layers of distributed system-presentation layers, application logic layer, data manipulation layer and data layer. Design and layers of Internet Based applications.

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Syllabus of Databases Technologies (A7-R5)

A Level - Syllabus of Module: A7-R5-Databases Technologies 

Introduction  : Application software requires data to be stored permanently. Databases provide the facility to store data permanently. Further, databases provide functionality to maintain and retrieve data. Depending upon different types of data storage, retrieval and processing, different types of databases are required. This module is designed with view to equip learner with two types of databases, RDBMS and NoSQL databases.

A Level - Syllabus of Module: A7-R5-Databases Technologies

Detailed Syllabus : 

(i) An Overview of the Database Management System : What is database? Why database? Database system, database management system (DBMS), advantages of DBMS. 

(ii) An Architecture of the Database system : Three levels of architecture, Logical View, Physical View, Conceptual View, Logical data independence, Physical Data Independence 

(iii) Relational Database Management System (RDBMS) : Introduction, RDBMS terminology, relational model, base tables, keys, primary key, foreign key, constraints, Codd Rules 

(iv) Database Design : Normalization, Normal forms-1NF, 2NF, 3NF, BCNF 4NF and 5NF, E-R Diagram. Mapping ER-diagram to database tables. 

(v) Maria DB : Introduction to Maria DB, Data Types, SQL Commands, Create, insert, update, delete, drop, alter, SQL functions (String functions, date functions), indexing, key, primary key, foreign key

(vi) Manipulating Data with Maria DB : SQL Statements, Select, like clause, group by, order by, joins-left join, natural join, right join, union. Correlated and nested queries. Backup and restore commands 

(vii) NoSQL Database Technology : Introduction to NoSQL Databases, Difference between relational and NoSQL databases. NoSQL features, types, advantages, Architecture of MongoDB, Documents, Collections, Dynamic Schemas, Mongo Shell, Mongo Server and Client, Data Types, Embedded Documents, Creating Configuration file for Mongo, JSON File format for storing documents, Inserting and Saving Documents, Batch Insert, Insert Validation, Removing Documents, Updating Documents, Document Replacement, Using Modifiers, Updating Multiple Documents, Returning Updated Documents, Introduction to Indexing, Introduction to Compound Indexes, Using Compound Indexes, Indexing Objects and Arrays, Aggregation Framework, Pipeline Operations- $match, $project, $group, $unwind, $sort, $limit, $skip, Using Pipelines, MongoDB and MapReduce, Aggregation Commands, Introduction to Replication, configuring a Replica Set, Member Configuration Options 

(viii) Selecting the Right Database : Selection of right databases, RDBMS or NoSQL, selection of database based on performance, data size, type of data, frequency of accessing data, business needs, type of application.  

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Syllabus of Computer Organization and Operating System (A6-R5)

A Level - Syllabus of Module: A6-R5-Computer Organization and Operating System 

Introduction : Operating System is an intermediate software layer between user and computer hardware. The program which is executed on computer requires difference resources like memory, hardware, CPU etc. On the other hand, computer consists of various blocks memory, ALU, control unit, input/output devices and other peripherals. This module provides information on both the topics, Computer Organization and Operating System. The functions of Operating System help user to interact with all components of computers.

A Level - Syllabus of Module: A6-R5-Computer Organization and Operating System

Detailed Syllabus : 

Part 1 – Computer Organization 

(i) Basic Structure of Computers : Structure of a Computer System, Arithmetic Logic Unit, Control Unit, Bus Structure, Von Neumann Architecture. 

(ii) Computer Arithmetic Operations : Introduction to logic gates, Boolean algebra, Data Representation-Number system, Fixed and Floating point numbers, Floating point representation, Signed numbers, Binary Arithmetic, 1’s and 2’s Complements Arithmetic, Binary adder, 2’s Complement method for multiplication, Map Simplification. 

(iii) Central Processing Unit and Instructions : General Register Organization, Types of Instructions, Instruction Formats, Addressing Modes, Data Transfer and Manipulation, Program Control, Instruction cycle. 

(iv) Memory Organization : Characteristics of Memory Systems, Type of memories, Main memory, Static & Dynamic memories, Secondary Memory, Performance Considerations, Cache Memory with mapping, Virtual Memory, Address memory used pages, page replacement, Introduction to RAID. 

(v) I/O Organization : Peripheral Devices, Input-Output Interface, Asynchronous Data Transfer Modes, Interrupt handling, Types of Interrupts, Priority Interrupt, Direct Memory Access, Input-Output Processor (IOP), Synchronous and Asynchronous Data Transfer. 

Part 2 – Operating System 

(vi) Operating Systems : Overview: Overview of Computer Operating Systems, Types of OS, Functions of OS, Protection and Security, Distributed Operating Systems, System Calls, Scheduling algorithms, memory management, threads. 

(vii) Linux Basics : Open source, Overview of Linux, Basic Linux commands, structure of kernel and shell, Getting help, Linux File System, Some Important Directories, Inodes, Current Working Directory, File and Directory Names, Absolute and Relative Pathnames, Creating and Removing Directories, Changing Directories, Listing Directory Contents, Creating and Removing Files, Copying Files and Directories, Moving and Renaming Files and Directories, fundamental file types, Hard Links, Symbolic ( or soft) Links, Viewing and working with large Text files – cat, more, less, head, tail, cut commands, search text within a file, grep. 

(viii) Process Management and Shell Script Processes : Definition, Process Relationship, Process states, Process State transitions, Process Control Block, Context switching – Threads – Concept of multithreads, Listing Processes, Finding Processes, Foreground and background processes, Interactive Process management tools, Sending signals to processes. Shell Script, shell variables, control structure using variables in shell script. 

(ix) Users, Groups and Permissions : Users, Groups, Linux File Security, Examining Permissions, accessing root user, creating user and groups, Changing File Ownership, Changing Permissions – Symbolic Method, Numeric Method, /etc/passwd, /etc/shadow and /etc/group files, Monitoring Logins, Default Permissions, Special Permissions umask, passwd. 

(x) Standard I/O and Pipes :  Standard Input and Output, Redirecting Output to a File, Redirecting STDOUT to a Program(Piping), Combining Output and Errors, Redirecting to Multiple Targets (tee), Redirecting STDIN from a file. 

(xi) Finding and Processing Files : Locate, find, Basic find Examples, find and Logical Operators, find and Permissions, find and Access Times.

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Syllabus of Data Structure Through Object Oriented Programming Language (A5-R5)

A Level - Syllabus of Module: A5-R5- Data Structure Through Object Oriented Programming Language

Introduction : Good knowledge of data structures and algorithms is the foundation of writing good code. Having good knowledge of essential Data structures like array, string, linked list, stack, queue, tree, graph etc makes one understand when to use which Data Structure and accordingly reduce the space and time complexity of the algorithm. Using the right data structure can drastically improve the performance of an algorithm. In depth understanding of Data Structures, enables one to understand how computer gets things done. Everything from memory allocation in the depths of operating system, to the inner workings of an RDBMS, to how networking stack manages to send data from one place to another, all computers rely on fundamental data structures and algorithms, so understanding them better makes one understand the computer better. In this course, the Data Structures and algorithms have been implemented using Object Oriented Approach with C++.Object-oriented programming (OOP) is a programming language model in which programs are organized around data, or objects, rather than functions and logic. An object can be defined as a data field that has unique attributes and behaviour. OOP approach enables a programmer to deal with real world entities. This opposes the historical approach to programming where emphasis was placed on how the logic was written rather than how to define the data within the logic.

A Level - Syllabus of Module: A5-R5- Data Structure Through Object Oriented Programming Language

Detailed Syllabus : 

(i) Object Oriented Concepts : Object Oriented Programming- a new paradigm, Abstraction, forms of Abstraction, OOP concepts- Classes, Objects, Polymorphism, Data Encapsulation, Data Hiding, Inheritance, 

(ii) Basics of C++, Classes and Objects : Features of C++, Tokens, keywords, Data types, Operators, Manipulators, Console input, output, Control statements (conditional and loops), Functions, Classes, Instantiation, Destructor, constructor, Polymorphism - Operator Overloading, Function Overloading, Inheritance-Single, Multiple, Multilevel, Pointers 

(iii) Analysis of Algorithm : Introduction to algorithm design and Data structures, Comparison of Algorithms, Complexity in terms of space and time, Calculation of O- notation. Abstract Data type and its implementation with a Rational number example 

(iv) Searching and Sorting : Searching- Linear and Binary Search, Sorting- Bubble Sort, Selection Sort, Insertion Sort, Quick Sort, Merge Sort, Comparison of various searching and sorting techniques in terms of time complexity.

(v) Elementary Data Structures : Arrays, Linked Lists Representation of arrays-single and multidimensional, Address calculation using row major ordering, Various operations on arrays, Linked Lists-Singly Linked List, Double linked List, Circular Linked List- traversing, deleting, inserting, searching, counting, reversing, printing of nodes. 

(vi) Stacks and Queues : Stack ADT, Implementation of stack using array and linked list, Application of Stack- Evaluation of postfix/prefix expression, Queue ADT, Implementation of queue using Array and Linked List 

(vii) Trees : Definition and notations, Binary Search Trees Implementation. Traversals using stacks and recursion - In-order, post-order, pre-order techniques, Threaded binary tree, B-trees with implementation of 2-3 trees. 

(viii) Graphs : Definition and notations, Components of Graphs, Types of Graphs, Graph Implementation using Adjacency Matrix and Adjacency List algorithms and programs, Graph Traversal Methods: Depth First Search and Breadth First Search. 

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Syllabus of Introduction to Internet of Things(IoT) and its Applications (A4-R5)

A Level - Syllabus of Module: A4-R5- Introduction to Internet of Things(IoT) and its Applications 

Introduction : The module is designed to equip the students to understand the basics of connected world that is Internet of Things (IoT) and its applications. IoT primarily refers to the connected and smarter world having physical and virtual objects with some unique identities. IoT applications spans across domains of industrial control, retail, energy, agriculture, etc. This module provides the theoretical and practical aspects of interfacing sensors and actuators, making informed world of Things speaking to each other. The different type of communication modes and models are discussed in detail. The in-depth knowledge of software and packages is provided to make applications in IoT paradigm. 

A Level - Syllabus of Module: A4-R5- Introduction to Internet of Things(IoT) and its Applications

Detailed Syllabus :  

(i) Introduction to Internet of Things – Applications/Devices, Protocols andCommunication Model : Introduction - Overview of Internet of Things(IoT), the characteristics of devices and applications in IoT ecosystem, building blocks of IoT, Various technologies making up IoT ecosystem, IoT levels, IoT design methodology, The Physical Design/Logical Design of IoT, Functional blocks of IoT and Communication Models. 

(ii) Things and Connections : Working of Controlled Systems, Real-time systems with feedback loop e.g. thermostat in refrigrator, AC, etc.Connectivity models – TCPIP versus OSI model, different type of modes using wired and wireless methodology, The process flow of an IoT application. 

(iii) Sensors, Actuators and Microcontrollers : Sensor - Measuring physical quantities in digital world e.g. light sensor, moisture sensor, temperature sensor, etc. Actuator – moving or controlling system e.g. DC motor, different type of actuators Controller – Role of microcontroller as gateway to interfacing sensors and actuators, microcontroller vs microprocessor, different type of microcontrollers in embedded ecosystem. 

(iv) Building IoT applications : Introduction to Arduino IDE – writing code in sketch, compiling-debugging, uploading the file to Arduino board, role of serial monitor. Embedded ‘C’ Language basics - Variables and Identifiers, Built-in Data Types, Arithmetic operators and Expressions, Constants and Literals, assignment. Conditional Statements and Loops - Decision making using Relational Operators, Logical Connectives - conditions, if-else statement, Loops: while loop, do while, for loop, Nested loops, Infinite loops, Switch statement. Arrays – Declaring and manipulating single dimension arrays Functions - Standard Library of C functions in Arduino IDE, Prototype of a function: Formal parameter list, Return Type, Function call. Interfacing sensors – The working of digital versus analog pins in Arduino platform, interfacing LED, Button, Sensors-DHT, LDR, MQ135. Display the data on Liquid Crystal Display (LCD), interfacing keypad Serial communication – interfacing HC-05(Bluetooth module) Control/handle 220v AC supply – interfacing relay module. 

(v) Security and Future of IoT Ecosystem : Need of security in IoT - Why Security? Privacy for IoT enabled devices- IoT security for consumer devices- Security levels, protecting IoT devices Future IoT eco system - Need of power full core for building secure algorithms, Examples for new trends - AI, ML penetration to IoT

(vi) Soft skills-Personality Development : Personality Development - Determinants of Personality- self-awareness, motivation, selfdiscipline, etc., building a positive personality, gestures. Self-esteem - self-efficacy, self-motivation, time management, stress management, Etiquettes & manners. Communication and writing skills- objective, attributes and categories of communication, Writing Skills – Resume, Letters, Report, Presentation, etc. Interview skills and body language. 

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Syllabus of Programming and Problem Solving though Python Language (A3-R5)

A Level - Syllabus of Module: A3-R5-Programming and Problem Solving though Python Language

Introduction to Module : Python is easy to use, powerful and versatile programming language, making it a great choice for developers. Python is used widely in different areas likes building Raspberry Pi applications, writing script program for desktop applications, configuring servers, developing machine learning & data analytics applications and developing web applications.

A Level - Syllabus of Module: A3-R5-Programming and Problem Solving though Python Language

Detailed Syllabus :

(i) Introduction to Programming : The basic Model of computation, algorithms, flowcharts, Programming Languages, compilation, testing &debugging and documentation. 

(ii)Algorithms and Flowcharts to Solve Problems : Flow Chart Symbols, Basic algorithms/flowcharts for sequential processing, decision-based processing and iterative processing. Some examples like: Exchanging values of two variables, summation of a set of numbers, Decimal Base to Binary Base conversion, Reversing digits of an integer, GCD (Greatest Common Division) of two numbers, Test whether a number is prime, factorial computation, Fibonacci sequence, Evaluate ‘sin x’ as sum of a series, Reverse order of elements of an array, Find largest number in an array, Print elements of upper triangular matrix, etc. 

(iii) Introduction to Python : Python Introduction, Technical Strength of Python, Introduction to Python Interpreter and program execution, Using Comments, Literals, Constants, Python’s Built-in Data types, Numbers (Integers, Floats, Complex Numbers, Real, Sets), Strings (Slicing, Indexing, Concatenation, other operations on Strings), Accepting input from Console, printing statements, Simple ‘Python’ programs. 

(iv) Operators, Expressions and Python Statements : Assignment statement, expressions, Arithmetic, Relational, Logical, Bitwise operators and their precedence, Conditional statements: if, if-else, if-elif-else; simple programs, Notion of iterative computation and control flow –range function, While Statement, For loop, break statement, Continue Statement, Pass statement, else, assert. 

(v) Sequence Data Types : Lists, tuples and dictionary, (Slicing, Indexing, Concatenation, other operations on Sequence data type), concept of mutability, Examples to include finding the maximum, minimum, mean; linear search on list/tuple of numbers, and counting the frequency of elements in a list using a dictionary. 

(vi) Functions : Top-down approach of problem solving, Modular programming and functions, Function parameters, Local variables, the Return statement, DocStrings, global statement, Default argument values, keyword arguments, VarArgs parameters. Library function-input(), eval(),print(), String Functions: count(), find(), rfind(), capitalize(), title(), lower(), upper(), swapcase(), islower(), isupper(), istitle(), replace(), strip(), lstrip(), rstrip(), aplit(), partition(), join(), isspace(), isalpha(), isdigit(), isalnum(), startswith(), endswith(), encode(), decode(), String: Slicing, Membership, Pattern Matching, Numeric Functions: eval(), max(), min(), pow(), round(), int(), random(), ceil(), floor(), sqrt(), Date & Time Functions, Recursion. 

(vii) File Processing : Concept of Files, File opening in various modes and closing of a file, Reading from a file, Writing onto a file, File functions-open(), close(), read(), readline(), readlines(),write(), writelines(), tell(),seek(), Command Line arguments. 

(viii) Scope and Modules : Scope of objects and Names, LEGB Rule Module Basics, Module Files as Namespaces, Import Model, Reloading Modules. (ix) NumPy Basics Introduction to NumPy, ndarray, datatypes, array attributes, array creation routines, Array From Existing Data, Array From Numerical Ranges, Indexing & Slicing.