This website is designed to help students in the Master of Computer Science program improve their performance in class. It provides access to essential resources like:
- Quizzes
- Assignments
- Exam Materials
- Data Type Resources
Before heading to class, students can explore these materials to better prepare and maximize their chances of scoring high marks.
I have several courses, and I will be sharing their data with you. Additionally, I will upload notes for many courses from time to time. Here are the course titles:
- Advanced Theory of Computation
- Advanced Analysis of Algorithms
- Data Mining
- Information Retrieval
- Applied Cryptography
In the Advanced Theory of Computation course, we will cover various topics in detail, including context-free grammar (CFG), regular expressions, languages, finite state automata (FSA), push down automata (PDA), and Turing machines (TM). We will also explore concepts such as palindromes and non-palindromes, equal and unequal numbers, operations like replacing and reversing strings, copying strings, inserting positions, and deleting symbols. Additional topics and notes will be uploaded from time to time as the course progresses.
In the Data Mining course, we will cover various topics in detail to enhance learning, such as mean, median, and mode, measuring the dispersion of data, histogram analysis, decision tree induction, chi-square, correlation analysis, Apriori algorithm, Naive Bayes classifier, agglomerative clustering algorithm, and confusion matrices. Complete details about these topics can be found on our website if you thoroughly explore it.
In the Advanced Analysis of Algorithms course, we will share information on several important topics. The course will cover areas such as an introduction to the course and its objectives, the importance of algorithm analysis, algorithm analysis techniques and basic mathematics, recurrence relations, the divide-and-conquer algorithm design strategy, and the analysis of recurrences. Additionally, we will study sorting and searching algorithms, string matching, dynamic programming algorithm design strategies, greedy algorithms, backtracking, branch and bound, and graph algorithms. The course will also include a guided study of some interesting algorithms from research papers. Moreover, additional topics will be uploaded over time if we receive positive feedback from you.
Additionally, your feedback is important! If you’re a new user, feel free to share your thoughts and suggestions so we can continuously improve and make this website even more helpful for everyone.
