Tristan Schwekendiek

Building on the concepts from Introduction to Object-Oriented Programming, students utilize techniques that enable the creation of more sophisticated and complex applications. Students explore deeper applications for the Java programming languages, such as mobile applications and Graphical User Interface (GUI) design and construction.

The use of client-side scripting to implement interactive behaviour within the browser environment is an important part of modern web applications. Standard client-side scripting syntax, operations, conditional statements, loops, functions, methods, and objects are examined. Students learn to manipulate the standard Document Object Model (DOM), by modifying the structure (HTML) and the appearance (CSS) of Web pages and/or interfaces for the purposes of improving the user experience.

In this course, students learn how to plan, analyze, design, and implement IT projects. Through the course content, students focus on the Systems Development Life Cycle (SDLC) as well as formal Project Management processes, such as scope, quality, risk, and resource management. Emphasis is placed on the practical application of software tools to design and manage IT projects.

Students are introduced to the process of planning, creating and managing a relational database using Structured Query Language (SQL) statements. Students apply best practices such as the use of entity relationship diagrams (ERD). Normalization and atomicity, consistency, isolation, durability (ACID) are emphasized. Students also develop skills in data manipulation and extraction.

In this course, students learn how to use Python programming language to solve common programming problems that involve the automation of tasks, such as reading and manipulating word processing files, spreadsheets and web data, as well as scheduling tasks and launching programs.

Design principles meet Web standards and aesthetic challenges in this practical interface design course. Students learn about advanced CSS selectors, CSS normalization, page layout techniques, interactive interface elements, colour, typography, and a variety of CSS-based visual effects. Responsive design fundamentals that address a variety of screen-rendering contexts are also addressed.

Network systems interconnect computer related resources, services and users. Students gain fundamental knowledge of networking concepts and technologies. There is a strong emphasis on terminology, protocols, error detection/correction and network security. Students develop the necessary skills to plan and implement small networks across a range of applications.

Students learn to use the Object Oriented Programming principles of encapsulation, polymorphism and inheritance in the C++ programming language. Students obtain knowledge of C++ grammar and syntax. Emphasis is placed on the powerful programming techniques supported by C++, including object manipulation and reusability, function/operator overloading, pointers and dynamic memory allocation.

In this course, students are introduced to new cloud solutions. Students learn to describe many cloud services such as Data Warehouses, Containers, Kubernetes, and Cloud Functions, and how to administer security solutions in the Cloud, such as Security Center and cloud firewalls.

The design and analysis of data structures and algorithms including Stacks, Link Lists, Trees, Graphs, Searching, Sorting and their complexity analysis. The theory is reinforced by working examples, laboratories, projects, and the use of abstract data types from the C and C++ standard libraries.

Digital logic. Digital systems. Machine-level representation of data. Major component parts of a modern digital computer, namely, control unit, arithmetic and logic units, memory units and peripheral interfaces are studied.

Introduction to artificial intelligence (AI) and its applications. Topics include several of the following: logic and reasoning, AI languages, state-space search, heuristics, constraints-satisfaction problem, game-problem solving, planning, machine learning, agent and multi-agents programming, neural networks, genetic algorithms and reasoning about uncertainty. Students will design and implement a medium scale project related to game programming as part of the course requirements.

Design of algorithms and analysis of required time and space resources for execution. Lower bounds for resource requirements. Problems in arithmetic, order statistics, set manipulation, string matching, graph theory. Polynomial time, P, and non-deterministic polynomial time, NP, computable algorithms. NP complete problems.

An introduction to the concepts of Computer Networks: LAN, WAN, communication protocols, inter-process communication/synchronization. Concurrent programming and distributed systems. Real-time systems.

Topics include conventional encryption, public-key cryptology, authentication and digital signatures, key distribution, IP security, web security, and network management security.

Processes and device handlers and their implementation, communication and synchronization. Synchronization primitives. Process allocation. Memory management. The software required to support a virtual memory system. Resource allocation algorithms. File system implementation. Security and protection. System implementation strategies. The evolution of computer systems: batch processing, multiprogramming, multi-processing, real-time, time-sharing, distributive systems. Each student will design and implement a module for an operating system kernel.

An introduction to the main tools and ideas in the data scientist's toolbox. An overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning unstructured data into actionable knowledge. The second is a practical introduction to the tools that are commonly used in Data Science such as R and Python.

This course discusses the key cloud concepts of: (i) Infrastructure as a Service (IaaS), (ii) Platform as Service (PaaS), and (iii) Software Application as Service (SaaS), as well as new and contemporary trends in cloud computing. It also expose students to concepts and technologies related to cloud computing such as Virtualization, Cloud Computing Platforms, Public Cloud, Private Cloud, Hybrid Cloud and Community Cloud Deployment Models, Business Cost Metrics and Formulas for Comparing and Calculating Cloud and On-Premise Solution Costs and Service Level Agreements (SLAs) for Cloud-based IT Resources. Selecting a cloud environment and deploying/implementing cloud based applications will be among the student projects/assignments of this course.