Sem2

Course Objectives

1.    Identify and explain the concepts, policies, and technologies associated with a layered and diversified defence-in-depth strategy.
2.    Discuss the objectives of access control methods and describe how the available methods are implemented in the defense of a network.
3.    Identify the impact of a layered defense on the performance of the network.
4.    Define the concepts of auditing in a network, including the types of audits and the handling of data.

Course Outcomes

1.    Apply various access control techniques to ensure authenticity.
2.    Explore techniques for integrity management.
3.    Explain the different types of attacks and 
4.    Explore the use of security tools in defending user/group accounts.
5.    Demonstrate the use of logging, auditing, and backup techniques for security
6.    Explain the basic cryptography concepts.

Skill Level: Beginner

Course Objectives

1.    Introduce basic digital image processing fundamentals.
2.    Familiarize students with different image transform techniques. 
3.    Explain different techniques employed for the enhancement of images.
4.    To familiarize students with image compression and restoration techniques.
5    Introduce  Image Analysis techniques and Computer Vision approaches
6.    Familiarize students with different  Emerging IT applications

Course Outcomes

1    Learn basics of digital image processing fundamentals.
2    Apply different image transform techniques.
3    Learn different techniques employed for the enhancement of images.
4    Apply image compression and restoration techniques.
5    Apply Image Analysis techniques and Computer Vision approaches  
6    Develop IT applications using image processing and computer vision.

Skill Level: Beginner

Course Objectives

1    Introduce fundamentals of GIS, Spatial Data, Spatial Data Modeling, and Attribute Data Management to the students.
2    Provide the knowledge of Data, Input, Editing and Data Analysis to the students.
3    Introduce to the students about Analytical Modelling in GIS, From New Maps to Enhanced decisions
4    Provide the knowledge of Development of Computer methods for handling spatial data to the students.
5    Provide the knowledge of Data quality issues, Human and Organizational issues to the students.
6    Provide the knowledge about GIS project Design and Management to the students.

Course Outcomes

1    Demonstrate a solid understanding of fundamental GIS concepts, including spatial data models, coordinate systems, map projections, and the basic components of a GIS.
2    Effectively use GIS tools to perform tasks such as data collection, data management, spatial analysis, and data visualization.
3    Gather, preprocess, and structure data from field surveys, remote sensing, and other sources for analysis.
4    Conduct spatial analysis using GIS techniques such as spatial querying, overlay analysis, proximity analysis, spatial interpolation, network analysis
5    Learn to acquire, preprocess, manipulate, convert, integrate, and assess vector and raster data quality.
6    Use GIS tools to address spatial challenges in urban planning, environmental management, and resource management.

Skill Level: Beginner

Course Objectives

1    Describe the concepts of database technology for the need of data mining and its applications. 
2    Elaborate different models used for OLAP and data pre-processing. Apply pre-processing statistical methods for any given large amount of raw data. 
3    Explains the performance of different data mining methods and tools. 
4    Help the study students, various developing areas in data mining as web mining, text mining, spatial mining, temporal mining and Identifying business applications of data mining. 
5    Explain critical thinking, problem-solving, and decision-making skills. 
6    To interpret the contribution of data warehousing and data mining to the decision support level of organizations. 

Course Outcomes

1    Understand the role of data warehousing and enterprise intelligence in industry. 
2    Compare and contrast the dominant data mining algorithms. 
3    Evaluate and select appropriate data-mining algorithms and apply, and interpret, report the output appropriately. 
4    Design and implement of a data-mining application using sample, realistic data sets and modern tools. 
5    Evaluate and implement a wide range of emerging and newly-adopted methodologies and Technologies to facilitate the knowledge discovery. 

Skill Level: Beginner

Course Objectives

1    Equip students with understanding of the fundamental concepts of cryptography and introduce them to essential encryption techniques.
2    Provide a thorough explanation of modern cryptosystems.
3    Engage in a discussion on the concepts of finite mathematics and number theory, as well as delve into the principles of public key cryptography.
4    Cover a comprehensive discussion on various security policies, including authentication, integrity, and confidentiality.
5    Provide students with a solid understanding of key management and key distribution.
6    Discuss network and Web security
protocols.

Course Outcomes

1    Understand of the fundamental terminology used in cryptography, as well as the principles behind classical cryptosystems.
2    Analyze advanced cryptographic systems used to secure information in today's digital world.
3    Explore mathematical structures, discrete mathematics, number systems, and their applications in the context of public key cryptography.
4    Understand their role in system security, authentication mechanisms, data integrity techniques, and confidentiality preservation.
5    Learn principles, best practices, and protocols for secure key management, distribution, integrity, and confidentiality throughout the key lifecycle
6    Gain knowledge of how these protocols are implemented and their significance in maintaining the confidentiality, integrity, and authenticity of network and web communications.

Skill Level: Beginner

Course Objectives

  1. Discuss history, evolution, classifications & current trends of Computer Architecture. Summarize and analyze the most important parallel architectures in order to distinguish their main differences
    2. Explain advanced microprocessor techniques & the salient features of state-of-the- art processors deployed in current High Performance Computing systems
    3. Discuss the details about System Area Networks, Storage Area Networks
     4. Introduce Internal/ External, Disk Storage, Network Attached Storage (NAS) and Direct Attached Storage
    5. Describe the System Software Architecture, various parallel programming models, message passing paradigms & typical HPCC software stack.

        6. Discuss a supercomputer case study.

Course Outcomes

1. Understand the history, evolution, classifications & current trends of Computer Architecture; Learn to evaluate & compare System’s performance using standard benchmarks
2. Describe the basics of advanced microprocessor techniques & the salient features of state-of-the- art processors deployed in current High Performance Computing systems
3. Discuss the details about System Area Networks, Storage Area Networks
4. Identify Internal/ External, Disk Storage, Network Attached Storage (NAS) and Direct Attached Storage
5.Analyse and implement the System Software Architecture, various parallel programming models, message passing paradigms & typical HPCC software stack.
6. Analyse A typical Pet flop System based on Hybrid CPU/GPU Architectures and Design case studies on supercomputer.

Skill Level: Beginner

Course Objectives

1.Provide a comprehensive understanding of the concept, origin, and types of Intellectual Property Rights (IPR) and their significance in the global context.
2. Introduce the legal framework of IPR, including the TRIPS agreement and its relationship with the WTO.
3. Familiarize students with the processes and laws related to patents, copyrights, and trademarks, along with their infringements and remedies.
4. Understand the significance of designs, geographical indications, and layout designs, as well as their protection under international and national laws.
5. Explore the legal provisions and ethical considerations related to the Information Technology Act, 2000, including cybercrime, e-commerce, and digital signatures.
6. Develop the ability to identify, register, and manage intellectual property rights in various domains, including traditional knowledge and modern technologies.

Course Outcomes

1. Explain the fundamental concepts, origin, and significance of various types of Intellectual Property Rights (IPRs) in protecting innovations and creations.
2. Apply the knowledge of patent laws, registration procedures, and infringement remedies in the protection of inventions and technologies.
3. Demonstrate an understanding of copyright laws, including software copyrights, piracy issues, and the remedies for infringement.
4. Analyze and manage issues related to trademarks, including registration, infringement, and offenses in cyberspace, such as domain name disputes.
5. Evaluate the legal framework for design protection, including the Semiconductor Integrated Circuits Layout Design Act and international conventions.
6. Assess the implications of the Information Technology Act, 2000, particularly in the areas of e-governance, e-commerce, digital signatures, and combating cybercrime.

Skill Level: Beginner

Course Objectives: 

  1. Introduce basic digital image processing fundamentals.
    2. Familiarize students with different image transform techniques. 
    3. Explain different techniques employed for the enhancement of images.
    4. To familiarize students with image compression and restoration techniques.
    5. Introduce  Image Analysis techniques and Computer Vision approaches
    6. Familiarize students with different  Emerging IT applications

Course Objectives: 

  1. Learn basics of digital image processing fundamentals.
    2. Apply different image transform techniques.
    3. Learn different techniques employed for the enhancement of images.
    4. Apply image compression and restoration techniques.
    5. Apply Image Analysis techniques and Computer Vision approaches  
    6. Develop IT applications using image processing and computer vision.
Skill Level: Beginner