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10 Modules / ~100 pages
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~25 Modules / ~400 pages
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Algorithmic Design and Simulation
( 25 Modules )

Module #1
Introduction to Algorithmic Design
Overview of algorithmic design, importance, and applications
Module #2
Algorithmic Thinking
Developing problem-solving skills, breaking down problems, and designing algorithms
Module #3
Basic Data Structures
Introduction to arrays, linked lists, stacks, and queues
Module #4
Asymptotic Notation
Big O, Omega, and Theta notations, time and space complexity analysis
Module #5
Graph Theory Fundamentals
Introduction to graphs, graph representation, and graph traversal
Module #6
Sorting and Searching Algorithms
Bubble sort, selection sort, insertion sort, and linear search
Module #7
Divide and Conquer Algorithms
Merge sort, quick sort, and binary search
Module #8
Dynamic Programming
Introduction to dynamic programming, memoization, and tabulation
Module #9
Greedy Algorithms
Activity selection problem, Huffman coding, and greedy algorithm design
Module #10
Backtracking Algorithms
N-Queens problem, Sudoku, and backtracking algorithm design
Module #11
Simulation Fundamentals
Introduction to simulation, discrete-event simulation, and simulation models
Module #12
Discrete-Event Simulation
Simulation of queuing systems, inventory systems, and supply chains
Module #13
Monte Carlo Simulation
Introduction to Monte Carlo methods, random number generation, and stochastic simulation
Module #14
Simulation Modeling
Modeling complex systems, system dynamics, and system thinking
Module #15
Object-Oriented Programming for Simulation
Introduction to OOP concepts, classes, objects, and inheritance for simulation
Module #16
Algorithms for Simulation
Algorithms for event scheduling, entity management, and statistical analysis
Module #17
Simulation Software and Tools
Overview of simulation software, such as Simul8, Arena, and AnyLogic
Module #18
Case Studies in Simulation
Real-world applications of simulation in healthcare, finance, and logistics
Module #19
Design and Analysis of Experiments
Design of experiments, response surface methodology, and sensitivity analysis
Module #20
Verification and Validation
Verification, validation, and accreditation of simulation models
Module #21
Advanced Topics in Algorithmic Design
Machine learning, deep learning, and AI applications in simulation
Module #22
Cloud Computing and Simulation
Cloud-based simulation, high-performance computing, and distributed simulation
Module #23
Real-World Applications of Algorithmic Design and Simulation
Applications in healthcare, finance, transportation, and other industries
Module #24
Ethics and Professionalism in Algorithmic Design and Simulation
Ethical considerations, bias, and professionalism in algorithmic design and simulation
Module #25
Course Wrap-Up & Conclusion
Planning next steps in Algorithmic Design and Simulation career


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