Big Data

SEMISTER 1SEMISTER 2
CODECOURSECODECOURSE
BD 100Introduction to Big DataBD 200Machine learning with Big Data
BD 110Big Data FundamentalsBD 210Graph Analytics for Big Data
BD 120Big Data Modeling and Management SystemsBD 215Managing Data with MySQL
BD 150Business Data Communications BD 315Big Data Analysis with Scala and Spark
BD 115Database Management Systems BD 350Information Security in Public and Private sectors

  • BD 100: Introduction to Big Data: This course is an introduction to big data and some fundamental concepts and technologies for Big Data scenarios.
  • BD 110: Big Data fundamentals : In this course, you will learn how big data is driving organisational change and the key challenges organizations face when trying to analyse massive data sets.
  • BD 120: Big Data Modeling and Management Systems: In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools.
  • BD 150 : Business Data Communications: Data communications, networks, protocols, Internet and electronic commerce.
  • BD 115: Database Management systems : Introduction to database management systems; relational models; security concurrency, integrity and recovery issues; query interfaces.
  • BD 200: Machine Learning with Big data : This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems.
  • BD 210: Graph analytics for Big data: This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data.
  • BD 215: Managing Data with MySQL: This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them.
  • BD 315: Big Data Analysis with Scala and Spark :  In this course, we’ll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout. We’ll cover Spark’s programming model in detail, being careful to understand how and when it differs from familiar programming models, like shared-memory parallel collections or sequential Scala collections.
  • BD 350: Information Security in Public and Private sectors : This course exposes the student to a broad range of computer systems and information security topics. It is designed to provide a general knowledge of measures to insure confidentiality, availability, and integrity of information systems. Topics range from hardware, software and network security to INFOSEC, OPSEC and NSTISS overviews. Components include national policy, threats, countermeasures, and risk management among others.

 

 

SEMISTER 3SEMISTER 4
CODECOURSECODECOURSE
BD 400Big Data Emerging technologiesBD 451Process Mining
BD 411Big Data ToolsBD 460Project management
BD 415Data-Driven Decision makingBD 470Business Intelligence: Web and social media analytics
BD 420Data management in the CloudBD 480Fundamentals of Object-oriented programming
BD 450Advanced Data Structures BD 490Software design and integration

  • BD 400: Big Data Emerging technologies : This course first focuses on the world’s industry market share rankings of big data hardware, software, and professional services, and then covers the world’s top big data product line and service types of the major big data companies. Then the lectures focused on how big data analysis is possible based on the world’s most popular three big data technologies Hadoop, Spark, and Storm. The last part focuses on providing experience on one of the most famous and widely used big data statistical analysis systems in the world, the IBM SPSS Statistics
  • BD 411: Big Data Tools: This course covers main topics associated with systems such as Hadopp MapReduce, Apache Spark, and Graph Processing Engines.
  • BD 415 : Data-Driven Decision making : You’ll be introduced to “Big Data” and how it is used. You’ll also be introduced to a framework for conducting Data Analysis and what tools and techniques are commonly used .
  • BD 420 : Data Management in the Cloud : This course covers the essential characteristics of data processing in the cloud, service and deployment models, and key components of implementing Amazon Web Services, as well as constructing Hadoop clusters and performing MapReduce operations.
  • BD 450: Advanced Data structures: This course serves as a broad overview of the many different types of data structures, including geometric data structures, like a map, and temporal data structures, as in storage that happens over a time series. It covers the major directions of research for a wide variety of such data structures.
  • BD 451: Frameworks and standards of IT governance : This course will enable students to learn about the frameworks as well as the standards of IT governance.s
  • BD 460: Process Mining:  The course explains the key analysis techniques in process mining. Students will learn various process discovery algorithms.
  • BD 470: Business Intelligence: Web and social media analytics: This course will provide students the opportunity to learn about Business Intelligence (BI) theory and combine it with powerful social media tools to gain insights into the emerging social media phenomena.
  • BD 480: Fundamentals of Object-oriented programming: The course is intended to provide a solid foundation in and understanding of the principles of object-oriented programming language using the Java language and/or to serve as a refresher for more advanced work.
  • BD 490: Software design and integration: This course aims to equip students with advanced object-oriented system design and software engineering principles and techniques to tackle modern challenges facing the development and maintenance of production-quality software systems in today’s fast-paced business environments. .

 

 

SEMISTER 5SEMISTER 6
CODECOURSECODECOURSE
BD 505Introduction to Data Exploration and VisualizationBD 530Database design and Development
BD 510Multivariete and Geographical data analysis BD 541 Application design and Development
BD 515Information Security risk management BD 550Web application Security
BD 520Enterprise Data ManagementBD 556Temporal and Hierarchical Data analysis
BD 525Data Mining for business intelligence BD 580Innovation in Information Systems

  • BD 505: Introduction to Data Exploration and Visualization: This course answers the questions, What is data visualization and What is the power of visualization? It also introduces core concepts such as dataset elements, data warehouses and exploratory querying, and combinations of visual variables for graphic usefulness, as well as the types of statistical graphs, —tools that are essential to exploratory data analysis.
  • BD 510: Multivariete and Geographical data analysis : Covering the tools and techniques of both multivariate and geographical analysis, this course provides hands-on experience visualizing data that represents multiple variables. This course will use statistical techniques and software to develop and analyze geographical knowledge.
  • BD 515 : Information Security Risk management : The objective of this course is to provide students a thorough and operational knowledge of information security so that this critical area is recognized as a management issue and not an I.T. issue
  • BD 520: Enterprise data management: This course introduces the student to fundamentals of database analysis, design, and implementation. Emphasis is on practical aspects of business process analysis and the accompanying database design and development.
  • BD 525: Data Mining for business intelligence : This course will cover data mining for business intelligence. Data mining refers to extracting or “mining” knowledge from large amounts of data. It consists of several techniques that aim at discovering rich and interesting patterns that can bring value or “business intelligence” to organizations. Examples of such patterns include fraud detection, consumer behavior, and credit approval. The course will cover the most important data mining techniques — classification, clustering, association rule mining, visualization, prediction.
  • BD 530: Database design and development: In this class students will study the principles of database management systems, their design, and development. Recent alternatives to the classical relational model will also be examined.
  • BD 541 : Application design and Development: This course provides students with the concepts and techniques to design and develop software applications, and to understand the design process. Students will learn the importance of user-centered design and will develop a prototype of a web application as a course project.
  • BD 550 : Web application Security: This is a technical course designed to help students learn how to exploit web applications and to be better able as developers to defend against such exploits. The course covers the process of hacking a web application, starting with initial mapping and analysis, followed by identifying common logic flaws in web apps, database and network exploits, command and SQL injections.
  • BD 556: Temporal and Hierarchical data analysis: This course covers the representation schemes of hierarchies and algorithms that enable analysis of hierarchical data, as well as provides opportunities to apply several methods of analysis.
  • BD 580 : Innovation in Information systems : In this course, students will be challenged to produce “proof of concept” systems or prototypes that are fully documented, tested, and ready.