Welcome to Exposure to Code!

We will be taking a whirlwind tour through the world of code using Python. After learning some basic coding concepts, we will be exploring hands-on various interesting things you can do with code, then wrapping up with a problem solving capstone. If you are new to coding, and are looking to learn about code the same way one would learn about dolphins in an aquatic park, keep reading!

The objective of this course is to give you a sneak peek into what you can do with code, and have you walk away with some coding basics after we’re done. We believe that short courses are not suitable for teaching solid fundamentals for coding. Rather, recognizing that coding ultimately is a skill that needs to be mastered on your own, we prefer spending the little time we have to get you really really interested so you will be motivated to continue learning on your own!

Thus, we hope your experience with this course will be more like a zoo safari than a museum tour. The things we hope you will be doing during the course are as follows, in order of importance:

• Reading up on interested material on your own

• Experimenting with the code

• Listening to the instructor :)

• Taking notes

Have fun learning!

Contents

• Week 1 : Introduction to Python
  • Setup
  • Spyder
  • Variables & primitives
  • Doing simple algebra
  • Exercise: Python as a calculator
  • Lists in Python
  • Conclusion
  • Further reading
• Week 2: Loops with for and while
  • Concept of for loops and while loops
  • Exercise: ASCII Animation I
  • Exercise: ASCII Animation II
  • Exercise: Prime finder
  • Exercise: Caesar cipher
  • Conclusion
  • Further Reading
• Week 2: Class Exercise solutions
  • Nested for loops
  • Exercise: ASCII Animation I
  • Exercise: ASCII Animation II
  • Exercise: Prime finder
  • Exercise: Caesar Cipher
• Week 2: Advanced Exercises
  • Adv Exercise : ASCII animation III
  • Adv Exercise : ASCII animation IV
• Week 3: If/else, Functions
  • If, else, and elif
  • Functions
  • Exercise: Quadratic solver
  • Exercise: Fizz Buzz
  • Conclusion
  • Further reading
• Week 3: Advanced Exercises
  • Adv Exercise: Finding Fibonacci numbers by recursion
  • Adv Exercise: Solve Tower of Hanoi
• Week 3: Class Exercise solutions
  • In-class exercise: multiple conditions for if-else
  • elif
  • In-class exercise: functions
  • Exercise: Fizz Buzz
  • Exercise: Quadratic solver
• Week 4: Visualizing data with matplotlib
  • Code to … draw?
  • What is matplotlib + setup check
  • Basic plotting
  • Plotting from CSV files
  • Basic styling
  • Slightly more advanced styling
  • Exercise: Recreating the World Health Chart
  • Conclusion
  • Further reading
• Week 5 : Numpy vectors & cellular automata
  • Introduction to numpy + setup check
  • Basic numpy operations
  • Cellular automata
  • Exercise: Conway’s Game of Life, but on a one-dimension grid
  • Conclusion
  • Further reading
• Week 5: Advanced Exercises
  • Adv Exercise: 1D fluid simulation by cellular automata
• Week 5: Class Exercise solutions
  • In-class exercise: array-indexing
  • Exercise: Thinking in array indices
  • Exercise: Conway’s Game of Life, but on a one-dimension grid
• Week 6 : Numpy arrays & exploring chaotic phenomena
  • Setup check
  • 2D arrays in numpy
  • Exercise: Sum of all elements in a 2D array
  • Chaotic systems
  • Exercise: Lorenz System
  • Exercise: Mandelbrot Set
  • Conclusion
  • Further reading
• Week 6: Class Exercise solutions
  • Exercise: Sum of all elements in a 2D array
  • Exercise: Lorenz System
  • Exercise: Mandelbrot Set
• Week 7 : Numerical methods
  • Setup check + Intro to numerical methods
  • Why do we need numerical methods?
  • Applications of numerical methods
  • Exercise: Solving roots using Newton-Raphson’s method
  • Exercise: Solving optimization problems with scipy
  • Conclusion
  • Further reading
• Week 7: Advanced Content
  • Adv Content: Verlet integration
• Week 7: Class Exercise solutions
  • Exercise: Solving roots using Newton-Raphson’s method
  • Exercise: Solving optimization problems with scipy
• Week 8 : Differential Equations & Modelling Populations
  • Setup check + Introduction to differential equations
  • Differential equations around us
  • Differential equations in life sciences
  • Exercise: SIR disease model I
  • Exercise: SIR disease model II
  • Exercise: SIR disease model III
  • Conclusion
  • Further reading
• Week 8: Advanced Exercises
  • Adv Exercise: Predator-prey relationship
• Week 8: Class Exercise solutions
  • Exercise: SIR disease model I
  • Exercise: SIR disease model II
  • Exercise: SIR disease model III
• Week 9 : Randomness and Generative art
  • Setup check + intro to randomness
  • Why do we need randomness in computing?
  • Sampling random numbers with numpy.random
  • Generative art with code
  • Primer on turtle graphics library
  • Exercise: Circle packing generative art
  • Conclusion
  • Further reading
• Week 9: Class Exercise solutions
  • Circle packing generative art
• Week 10 : Problem solving mini-capstone
  • Intro
  • Mini-capstone 1: n-body simulation (physics)
  • Mini-capstone 2: 1D fluid simulation (cellular automata)
  • Mini-capstone 3: Ecosphere equilibrium (biology + optimization)
  • Where to from here?
• Week 10: Example outcomes from problem solving mini-capstone
  • Mini-capstone 1: n-body simulation (physics)
  • Mini-capstone 2: 1D fluid simulation (cellular automata)