Fundamentals of algorithmic programming for Operations Management

In this course, you develop fundamental programming and algorithmic skills for operations management. You learn to solve practical optimization problems using variables, functions, and basic algorithms, supported by weekly (video) lectures, instructions, and assignments. Examples of topics that will be discussed are:

• Variables and types
• Operators and expressions
• Conditional statements, loops and functions
• Data preparation and reporting
• Integration with tools and libraries
• Basic algorithms for searching, sorting, and optimizing

After successfully completing this course, the student is able to:

• Understand the following programming constructs: variables and types,

        operators and expressions,    
        conditional statements,    
        loops,    
        functions,   
        data structures.
  

• Apply these constructs, to create algorithms that solve simple operations management problems, such as loading data from a file system and from the web, preparing data for further processing (filtering and transforming data elements).

• Programmatically integrate existing tools and libraries for simple practical operations management problems, such as configuring and invoking a data analysis library

• Use basic algorithms for searching, sorting and optimization to solve operations management problems.

• Demonstrate by means of an automated test suite to which degree algorithmic correctness has been verified

You must meet the following requirements

• Registered for a degree programme other than
• HBO-TOP Applied Physics, Pre-Master
• Completed none of the course modules listed below
• Programming for PT (0HV120)
• Algorithmic prog for oper Mgt (1BK50)
• Fundamentals of algorithmic pro for OMgt (1BK60)
• Programming (2IP90)
• Programming Methods (2IPC0)
• Introduction to objectprogramming (2IPG0)
• Software Development for Engineers (2IS50)
• App Programming (2IS60)
• Programming and Modeling (CBL Component) (2MBA30)
• Programming and modelling (2WH20)
• Programming for Applied Physics (31PAP)
• Principles of design and programming (4CA10)
• Programming and engineering challenge (5EWC0)
• Programming and Linear Algebra (6BBR06)
• Programming for data analytics (8BA080)
• Programming and genomics (8CA10)
• Creative programming (DBB100)
• Programming (JBI010)

• Charles R. Severance, Python for Everybody: Exploring Data Using Python 3, 2009. Accessible from: https://www.py4e.com/book.php