03 : Courses

Courses that I have taken.

Artificial Intelligence (Python) (CMPT310)

  • Problem solving with search, adversarial game playing.
  • Bayesian networks, machine learning.
  • Applications such as robotics, visual computing and natural language

    • Data Structures and Algorithms (C++) (CMPT307)

  • Designed and analysis efficient data structures and algorithms.
  • General techniques for building and analyzing algorithms (greedy, divide & conquer, dynamic programming, network flows).
  • Introduction to NP-completeness

    • Software Engineering (Java) (CMPT276)

  • Designed and implemented project using iterative development process --> SPACE MONKEY)
  • Major tasks and phases in modern software development, including requirements, analysis, documentation, design, implementation, testing,and maintenance.

    • R for Data Science (R) (STAT260)

  • Designed and implemented web scrapping project --> WEB SCRAPPING)
  • Data visualization transformation, and summaries; data wrangling (reading, tidying, and data types)

    • Database Systems (SQL) (CPSC2221)

  • Designed and implemented a relational database for an enterprise using Oracle --> HAPPY DENTAL DATABASE)
  • Relational model, relational algebra, SQL, UML or E/R approach to database design.

    • Linear Optimization (Matlab) (MATH308)

  • The simplex method and its variants, Duality theory, post-optimality analysis, applications and software

    • Data Science (R) (STAT240)

  • Applied tools and methods for data acquisition, management, and visualization capable of scaling to Big Data

    • Computer Systems (C) (CMPT295)

  • Fundamental topics in computer architecture

    • Discrete Math 2 (MACM201)

  • Graph theory, trees, inclusion-exclusion, generating functions, recurrence relations, optimizing and matching

    • Probability and Elementary Mathematical Statistics (STAT2281)

  • Random variables, moment generating functions
  • Discrete distributions: binomial, hypergeometric and Poisson distributions
  • Continuous distributions: exponential, uniform, Chi-square, Beta, and Normal Distribution

    • Algorithms and Data Structures 2 (C++) (CPSC2150)

  • Non-linear data structures and hashing.
  • Algorithms analysis, non-comparative sorting, algorithmic paradigms (divide and conquer, greedy, heuristic, backtracking, dynamic programming), binary search trees, balanced trees, tree traversals, priority queues and heaps, Huffman codes, graphs.

    • Descriptive and Elementary Inferential Statistics (STAT1181)

  • Probability, descriptive statistics, regression, correlation, contigency tables, sampling distributions, estimation, hypothesis testing.

    • Linear Algebra (MATH2362)

  • Vectors, matrices, linear equations, and their application.
  • Gaussian elimination, Euclidean and abstract vecto spaces.

    • Algorithms and Data Structures 1 (C++) (CPSC1160)

  • Applied recursion, abstract data types, algorithms analysis, sorting and searching, pointers, arrays, dynamic memory management, linked lists, stacks, and queues

    • Discrete Math 1(CPSC2190)

  • Sets and propositions; relations and functions; permutations, combination and counting
  • Induction proof; graphs, trees and networks; Boolean algebra and mathematical models; application of theoretical concepts to program development

    • Object-oriented Computing (Java) (CPSC1181)

  • Concepts of programming from an object-oriented (OO) perspective: abstraction, classes hierarchies, methods, encapsulation. inheritance, polymorphism.
  • Applied OO design with modeling tools (e.g. class diagrams), container/collection classes, event-driven programming, exception handling, GUI, multi-threading, and networking.

    • Program Design (Java) (CPSC1150)

  • Buit and implemented algorithms in a programming language using good software development principles.
  • Developed problem-solving techniques while learning the basics of algorithm development, procedural abstraction, and data representation.

    • Program Design (Python) (CPSC1050)

  • Introduction to computer hardware and programming; networks; applications (e.g., spreadsheet, database)
  • Networking; ethics; and history.