Why this matters: This information matters because each resource provides information on one of the basic concepts needed to start off this course, ranging between perspective and mentality and technical concepts around Big 0 and data types.
In the context of the reading “Pain and Suffering,” describe the main challenges faced by beginners when learning Python and suggest at least two strategies for overcoming these obstacles.
Some of the main challenges students may face in an accelerated learning environment involve balancing mental, physical, and emotional health with learning and growth. Strategies students could employ to maintain as much balance as possible are to focus on MVP (minimum viable product) and not go unnecessarily overboard in their work, relying on positive relationships for support, and paying attention to basic needs like sleeping and eating.
After reading “Beginners Guide to Big O,” explain the concept of time complexity and space complexity.
Time complexity refers to the amount of time an algorithm takes to run when the input tends towards a specific or limiting value. It calculates the time taken to execute each code statement in an algorithm.
Space complexity indicates how much memory space the algorithm occupies. We compare the worst-case space complexities of the algorithm.
Based on the “Names and Values in Python” reading, explain the difference between mutable and immutable data types in Python.
A data type whose internal state can be changed is mutable. On the other hand, immutable doesn’t allow any change in the object once it has been created. Strings and tuples are immutable and lists, dictionaries, and sets are mutable.
Nothing at the moment!