MODELING, SIMULATION & MACHINE LEARNING

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 The simulation market will continue to expand in

 numerous simultaneous directions: advancing predictive

capabilities, improving speed & accuracy, developing

smart adaptive systems and overcoming barriers to access and computational power.

  ~ Seth Hindman (Senior Product Manager, Autodesk).

Modeling, Simulation, and Machine Learning (MSML) is a dynamic field that is utilized in engineering, science, health science, business, education, and many other disciplines. This emerging field is based on developments in diverse engineering areas and brings elements of art, engineering, and science together in a complex and unique way that requires domain experts to enable appropriate decisions. Due to its dynamic nature, MSML has tremendous potential for creating student interest in science, technology, engineering, and mathematics disciplines. This specialization requires designing of mathematical model of actual or theoretical physical systems, executing the model on a computer and analyzing the output. Computer simulations are extensively being used in aerospace industry, automobile systems, financial markets, environment systems and medical sciences. Machine Learning provides a practical treatment of design, analysis, implementation and applications of algorithms, which learn from examples. Modeling, Simulation, and Machine Learning are particularly important because the description of the system behavior by experimentation might not be feasible due to some of the following reasons.

  • Some experiments may be very harmful
  • Some experiments might take longer time than expected and may also be very costly
  • There might be obstructions during experimentation
  • We might not have access to inputs and outputs.

 

Careers in MSML: Computer Simulations and Machine Learning are extensively being used in aerospace industry, automobile systems, financial markets, logistics planning, environment systems and medical sciences. Job market includes:

  • Simulation and Software Design
  • Data Mining and Machine Learning
  • Autonomous Systems
  • Data Science and AI
  • Computational Mathematics
  • Industrial Management
  • Logistics and Planning
  • Financial Engineering
  • Oil and Gas Industry
  • Space and Defense
  • Academia and Research
  • Engineering Entrepreneurship
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