CCMAS Course Search

Rational Databases: Mapping conceptual schema to relational schema; Database Query Languages (SQL) and NoSQL, Concept of functional dependencies & multi-valued dependencies. Transaction processing; distributed databases, XML and semantic Web. Data warehousing. Introduction to data science. Introduction to Data Warehouse, OLTP Systems; Differences between OLTP Systems and Data Warehouse: Characteristics of Data Warehouse; Functionality of Data Warehouse: Advantages and Applications of Data Warehouse. Advantages, Applications: Top- Down and Bottom-Up Development Methodology: Tools for Data warehouse development: Data Warehouse Types. Introduction: Scope of Data Mining: What is Data Mining. How Data Mining Works, Predictive Modelling: Data Mining and Data Warehousing: Architecture for Data Mining: Profitable Applications: Data Mining Tools. Lab work: Practical exercises on basic R commands and data structures for manipulating data; how to read data from multiple formats in and out of R, using loops, conditional statements, and functions to automate common data management tasks. Exercises on how to clean and manage multiple complex datasets, manipulate textual data, basic web scraping techniques, for both standard web pages and the Twitter API. Work on techniques and hardware necessary to manage large datasets efficiently. Practical exercise on managing multiple data sets by example; working with text data; converting long- and wide-format data; and dealing with messy data. R Programming Fundamentals for data I/O and packages, looping and conditional statements, and functions.

Fundamentals of data mining, Data Mining Functionalities, Classification of Data Mining systems, Data Mining Task Primitives, Integration of a Data Mining System with a Database or a Data Warehouse System, Information retrieval, machine learning, optimisation, microeconomics, algorithms, mathematical formulas, computer programs, analytic tools and online portals, Data Cleaning, Data Integration and Transformation, Data Reduction, Discretisation and Concept Hierarchy Generation, Data Warehouse and OLAP Technology for Data Mining: Data Warehouse, Multidimensional Data Model, Data Warehouse Architecture, Data Warehouse Implementation, Further Development of Data Cube Technology, From Data Warehousing to Data Mining Data Cube Computation and Data Generalisation

Fundamental concepts of innovation, and business ideas in general. Product development. Business leadership. Digital marketing. Entrepreneurial opportunities in IT. Legal issues and Business ethics. New venture creation process. Business feasibility planning. Market research. Business strategy. Business models and Business plans. Technical presentations. Report on a successful entrepreneurial outfit.

Primitive types, Arrays, Records Strings and String processing, Data representation in memory, Stack and Heap allocation, Queues, TREES. Implementation Strategies for stack, queues, trees. Run time Storage management; Pointers and References, linked structures. Lab work: Writing C+/C++ functions to perform practical exercises and implement using the algorithms on arrays, records, string processing, queues, trees, pointers and linked structures.

Primitive types, Arrays, Records Strings and String processing. Data representation in memory, Stack and Heap allocation, Queues, Trees. Implementation strategies for stack, queues, trees. Run time storage management; Pointers and References, linked structures. Lab work: Writing C+/C++ functions to perform practical exercises and implement using the algorithms on arrays, records, string processing, queues, trees, pointers and linked structures. CSC 308 Operating System (3 Units C: LH 30; PH 45) Learning Outcomes At the end of this course, students should be able to: 1. recognise operating system types and structures; 2. describe OS support for processes and threads; 3. recognise CPU scheduling, synchronisation, and deadlock; 4. resolve OS issues related to synchronisation and failure for distributed systems; 5. explain OS support for virtual memory, disk scheduling, I/O, and file systems; 6. identify security and protection issues in computer systems; and 7. use C and Unix commands, examine behaviour and performance of Linux, and develop various system programmes under Linux to make use of OS concepts related to process synchronisation, shared memory, mailboxes, file systems, etc. Course Contents Fundamentals of operating systems design and implementation. History and evolution of operating systems. Types of operating systems. Operating system structures. Process management: processes, threads, CPU scheduling, process synchronisation. Memory management and virtual memory. File systems; I/O systems; Security and protection; Distributed systems; Case studies. Lab work: Practical hands-on engagement to facilitate understanding of the material taught in the course. All the process, memory, file and directory management issues will be demonstrated under the LINUX operating system. Also UNIX commands will be briefly discussed. Alternatively, hands-on exposure may be through the use of operating systems developed for teaching, like TempOS, Nachos, Xinu or MiniOS. Another possibility is through programming exercises that implement and simulate algorithms taught. Simulation of CPU scheduling algorithms, producer-consumer problem, memory allocation algorithms, file organisation techniques, deadlock algorithms and disk scheduling algorithms.

Various methods for presenting data for visualisation as well as how to choose between them. Fundamentals of data presentation using tables, graphs, images and video animations. Create engaging visualisations using graphs, images and video animations. Data summaries, working with tables, presenting data through graphs and plots, presenting data through video animation, creating interactive/augmented visualisation of data (ability to zoom into sections). Lab work: Practical experiments on different methods of presenting data for visualisation. Practice on how to use graphs, tables, images, and video on animation for data presentation.

The theory, design, development, and management of modern relational databases. Basic technical skills for the class covers database design and implementation: entity-relationship modeling, normalisation, structured query language, and database management. Rational Databases: Mapping conceptual schema to relational Schema; Database Query Languages (SQL) Concept of Functional dependencies & Multi-valued dependencies. Transaction processing; Distributed databases.

A brief introduction to database concepts: file systems and databases; and the relational database model; design concepts and implementation: entity relationship (E-R) modelling; normalisation of database tables and structured query language; database design and implementation; Transaction management and concurrency control and distributed database management systems; database privacy; security; failure and recovery; Object-oriented databases; client/server systems; data warehouse; data mining; databases in electronic commerce; web database development and database administration

Dark web, deep web, clear net. Tor Onion, Silk Road. How to get on the dark web. Users of dark and deep web. Invisible Web Search Engines. Privacy and anonymity as core values of the darknet. Decentralisation on the dark web. Accessing the Deep web and the Dark web through the TOR browser. Web security. Cryptocurrencies. Overview on Dark Web and Deep Web. The Hidden side/area of the web. Deep/Dark Web Anonymity, TOR, Hidden services, TAILS, Web Security, Cryptocurrencies. Crypto Trading and Cryptomining. Cryptocurrencies, Anonymity & Security. How to install a VPN, and adequate browsers like Chrome, Opera, or Firefox with tracking technologies. How Does the Dark Web Work? Reasons for Accessing the Dark Web. Security issues of Dark and Deep web. How to use the Tor over VPN method - Session logs storage. Encryption of traffic. Protection against malicious Tor exit nodes. How to use Tor over VPN - bypass blocked Tor nodes, ISP visibility in accessing onion content, susceptible to end-to-end timing attacks. Tor alternatives such as I2P, Matrix.org, Orbot, Globus Secure Browser, Comodo Ice Dragon and FreeNet. Cons and Pros of Tor. Use of virtual machine software. Navigating the Dark Web. The Hidden Wiki as Wikipedia’s evil twin. Search engines such as DuckDuckGo, Torch, the triple-W Virtual Library, Uncensored Hidden Wiki, and ParaZite. Commercial services. Email clients. Darknet version of social media and instant messaging - Zuckerberg’s Facebook, BlackBook, Torbook, Campfire, MadIRC Chat Server. Safety on the dark web. Inside the dark and deep web. The Best Sites and Services on the Dark Web. Deep web radio. Benefits of Deep and Dark web. Cyber Threats and Dangers on the Deep/DarkWeb. How to fight hackers underground. Dark web and Deep web monitoring. Lab work: Install your VPN. Practice how to access the Deep web and the Dark web with enhanced security. Investigate advanced and famous websites located on the Deep and Dark Web. Practically learn how to anonymously access the darknet and TOR hidden services (onion services), and how to enter the dark web while staying safe. Try to visit the best sites and buy an educational resource.