[ FreeCourseWeb ] Udemy - Dynamic Programming Python, Coding Interviews & Applications

[ FreeCourseWeb.com ] Dynamic Programming Python, Coding Interviews & Applications

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Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz
Language: English | VTT | Size: 1.68 GB | Duration: 5 hours
What you'll learn
Recognize a problem that can be solved using Dynamic Programming
Come up with both a top down and bottom up Dynamic Programming solution using Python
Use Dynamic Programming for coding interview puzzles and practical applications
Improve your problem-solving skills and become a better developer
Revise your recursion knowledge

Requirements
Python programming language
Familiarity with recursion, although we also cover this in the course
Description
Have you ever wondered what makes a good developer? Why it is that big tech companies are increasingly asking candidates to solve challenging coding puzzles in interviews? Or why you should bother to learn about complicated algorithms?

With regards to technical skills a good developer has an understanding of computer science and knows when to apply this knowledge. Tech companies know that if someone has a good grasp of these fundamentals, she will likely be fine learning any programming language, using any new tool and solving a wide range of programming problems. As a developer comprehending data structures and algorithms you’ll be better equipped to tackle some of the more difficult problems both in your day-to-day job and for coding interviews.

Dynamic Programming is a topic in data structures and algorithms. It covers a method (the technical term is “algorithm paradigm”) to solve a certain class of problems. In this course we will go into some detail on this subject by going through various examples. The course is designed not to be heavy on mathematics and formal definitions. Instead you will learn through practical everyday programming algorithms and through some coding interview puzzles. We present a method to recognize problems that can be solved using dynamic programming and then build an efficient solution through small gradual steps.

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