Learn how to make your Python code more efficient by using algorithms to solve a variety of tasks or computational problems. In this video course, you’ll learn algorithm basics and then tackle a series of problems—such as determining the shortest path through a graph and the minimum edit distance between two genomic sequences—using existing algorithms.
With a gentle learning curve, Python is readable, writeable, and endlessly powerful. Its simplicity lets you become productive quickly. This Learning Path provides a solid introduction to Python, and then teaches you about algorithms, data modeling, data structures, and other tools that make Python the ideal choice for working with data.
A practical guide that will give you hands-on experience with the popular Python data mining algorithms.
When should you use Python’s built-in data types, and when should you develop your own? In this video course, George Heineman introduces Python programmers to several important data structures and demonstrates their use with example algorithms. Generic data structures such as arrays, linked lists, and stacks can solve many problems, but to work through some specialized problems, you need to learn different ways to structure data appropriately.