He initiated his career as a Faculty member in the Department of Computer Science and Engineering at the University of Information Technology & Sciences (UITS). Following that, he assumed the role of a Lecturer in the Department of Computer Science at Daffodil International University. At present, he is on a study leave. Throughout this professional journey, he has delivered numerous courses.
CSE 131: Discrete Mathematics:
Course curriculum includes: Set theory; Relations; Functions; Graph theory; Propositional calculus and predicate calculus; Mathematical reasoning: induction, contradiction and recursion; counting; Principles of inclusion and exclusion; Recurrence relations; Algebraic structures: rings and groups.
CSE 122: Problem Solving Lab ( C Programming Lab):
data types, operators, expressions, control structures; Functions and program structure: parameter passing conventions, scope rules and storage classes, recursion; Header files; Preprocessor; Pointers and arrays; Strings; Multidimensional array; User defined data types: structures, unions, enumerations; Input and Output: standard input and output, formatted input and output, file access; Variable length argument list; Command line parameters; Error Handling; Graphics; Linking; Library functions. This is Laboratory works based on CSE 121.
Reference language: C
CSE 414: Artificial Intelligence Lab:
Introduction to old and new AI techniques; Knowledge representation; Propositional and first order logic, inference in first order logic; Frame problem; Search techniques in AI; Game playing; Planning; Probabilistic reasoning; Learning in symbolic and non-symbolic representation; Natural language processing. Introduction to expert system. This is Laboratory works based on CSE 413.
CSE 415: Simulation And Modeling:
Simulation modeling basics: systems, models and simulation; Classification of simulation models; Steps in a simulation study; Concepts in discrete-event simulation: event-scheduling vs. process-interaction approaches, time-advance mechanism, organization of a discrete-event simulation model; Continuous simulation models; Combined discreet-continuous models; Monte Carlo simulation; Simulation of queuing systems.
Building valid and credible simulation models: validation principles and techniques, statistical procedures for comparing real-world observations and simulated outputs, input modeling; Generating random numbers and random variates; Output analysis. Simulation languages; Analysis and modeling of some practical systems.
Database Management System
Database Management System Laboratory
Compiler Design
Compiler Design Laboratory
Computer Fundamentals
Compiler Design
Compiler Design Laboratory
Computer Architecture
Algorithm
Algorithm Laboratory