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The course mainly focuses on software implementations in C Programming Language. Firstly, basic concepts of algorithms are discussed and then structures of programming are studied. Then, arrays and searching and sorting algorithms on arrays are studied. Fundamentals of basic data structures, which are arrays, structures and unions are discussed together with bitwise operations and enumerations in C. Pointers, functions and file processing are studied in the second part of the course, after midterm examination. Case studies related to searching and sorting algorithms are also studied. Functions, characters and strings are studied as last topics of algorithm developments and course is finalized with complexity analysis of algorithms.
- Teacher: Olanrewaju Adekoya
- Teacher: Gad Bambembe
- Teacher: Tarek Ghamrawi
- Teacher: Masoud Moradi
- Teacher: Cannur Onoral
Course Description and Objectives:
This course introduces fundamental concepts, principles, and best practices in project management based on the PMI PMBOK Guide 6th edition. Students will gain the knowledge and skills needed to initiate, plan, execute, monitor, control, and close projects successfully.
- Understand the key principles and terminology of project management.
- Apply project initiation and planning processes.
- Create project schedules, budgets, and resource plans.
- Monitor and control project performance.
- Close projects and perform lessons learned.
- Teacher: Erkan EmIrzade
- Teacher: Muesser Nat
This course provides
a comprehensive definition of “Big Data” and the machine learning approaches
for managing and processing them. With storage and computational power getting
significantly cheaper and faster, big data sets are increasingly available and
the need for machine learning approaches for handling big data becomes more
significant. In this course, big data harvesting and manipulating methods,
supervised and unsupervised machine learning techniques (especially artificial
neural network), text data analysis and cloud computing are covered. By
completion of this course, students will gain the ability to harvest big data
from the web and process them by using supervised and unsupervised neural
networks.