Brief Introduction
Develop the thought processes involved in formulating a problem so a computer can effectively carry out the solution. In particular, this course emphasizes use of computers for modeling physical systems and predicting their behavior.Description
Computational thinking is becoming widely recognized as a skill necessary for every educated person in a technologically advanced society.We will focus on just a subset of computational thinking which concerns creating models of the physical world – something that engineers frequently need to do. Because of that choice, this course covers many topics normally viewed as within the domain of mathematics such as algebra and calculus, but the solution procedures are algorithmic rather than symbolic.
The major themes of the course are:
- Representation -- How do you encode information about the world in a computer? How do your choices in representation affect the ease with which you can solve problems?
- Decomposition -- How do you break a large and diverse problem into many simpler parts?
- Discretization -- How do you break up space and time into a large number of relatively small pieces? What are the alternative ways of doing this? What are the consequences of discretization procedures for accuracy and speed?
- Verification -- How do you build confidence in the results of a model?
Knowledge
- By the end of this course, students will be able to:
- Select and implement methods for interpolation and understand their consequences for convergence of model results as discretization is refined.
- Carry out a few simple methods for numerical integration
- Implement procedures for numerical differentiation
- Write programs to solve systems of equations, both linear and non-linear
Machine Learning and Data Science Hands-on with Python and R
- 3.9
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Machine Learning, Statistics, Python, AI, Tensorflow, AWS, Deep Learning, R Programming, NLP, Bayesian, BI and much more Learn by doing. Full Lifetime Access....
Learn Data Science Deep Learning, Machine Learning NLP & R
- 4.5
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Learn Data Science, Deep Learning, Machine Learning, Natural Language Processing, R and Python Language with libraries || DATA SCIENCE || What Does a Data Scientist Do?...
Introduction to Spreadsheets and Models
- 4.2
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The simple spreadsheet is one of the most powerful data analysis tools that exists, and it’s available to almost anyone. Spreadsheets: A Tool for Thinking with Numbers...
Interprofessional Healthcare Informatics
- 4.4
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We will be incorporating technology-enabled educational innovations to bring the subject matter to life. All healthcare professionals and IT geeks are welcome!...
