Course Hive
Search

Welcome

Sign in or create your account

Continue with Google
or
Dynamic Programming Full Course 2023 | Knapsack Problems using Dynamic Programming
Play lesson

Data Structures and Algorithms (DSA): Stacks & Queues | Linked Lists | Sorting | Arrays - Dynamic Programming Full Course 2023 | Knapsack Problems using Dynamic Programming

Master the Art of Data Structures & Algorithms: Crack Coding Interviews with Ease in 2023! Explore Comprehensive Tutorials & Interview Prep on Stacks, Queues, Graphs, and More. Get Ready to Ace FAANG with Expert Guidance from SCALER!

5.0 (2)
17 learners

What you'll learn

Develop proficiency in implementing commonly used data structures such as stacks, queues, and linked lists
Enhance problem-solving skills by applying algorithms to various coding challenges
Understand and optimize time complexity for efficient algorithm performance
Master dynamic programming and graph theory techniques for complex problem-solving

This course includes

  • 389 hours of video
  • Certificate of completion
  • Access on mobile and TV

Summary

Keywords

Full Transcript

Dynamic programming is used to deal with problems that can be divided into similar sub-problems so that their results can be re-used. We aim to solve Knapsack Problems and other important coding problems. Learn more about Scaler: https://bit.ly/3gitdEx 🔹Introduction to Dynamic Programming: Dynamic Programming is most commonly an optimization over plain recursion. A recursive solution that has repeated calls for the same inputs is optimized using Dynamic Programming. In a nutshell, the results of subproblems are stored, to omit the need of re-computing them when required. This simple optimization reduces time complexities from exponential to polynomial. 🔹Applications of Dynamic Programming: Dynamic programming is used where we have problems, which can be divided into similar sub-problems so that their results can be re-used. From this exclusive dynamic programming tutorial, you can learn how to solve important coding problems. The following topics are covered in this video 👇🏼 0:00 - Introduction to Knapsack Problems 40:12 - Fractional Knapsack 1:05:13 - Longest Increasing Sub-sequence Problem 1:17:14 - Regular Expression Match Problem 1:47:16 - Max Sum Path in Binary Tree Problem 2:08:33 - Best Time to Buy and Sell Stocks Problem 2:27:57 - Min Jumps Array Problem 2:37:06 - Edit Distance Problem 2:59:05 - Rod Cutting problem 3:21:27 - Turn on the Bulbs Problem 3:44:00 - Valid Parenthesis Problem ---------------------------------------- About Scaler -------------------------------------------------- We are a tech-focused upskilling and reskilling platform catering to tech enthusiasts in universities and working professionals. There are more Scaler graduates working at Amazon than all of the IITs combined! Know More about Scaler: https://bit.ly/3gitdEx 📌 Follow us on Social and be a part of an amazing tech community📌 👉 Meet like-minded coder folks on Discord - https://discord.com/invite/ejFeksEtTq 👉 Tweets you cannot afford to miss out on - https://twitter.com/scaler_official 👉 Check out student success stories, expert opinions, and live classes on Linkedin - https://www.linkedin.com/school/scalerofficial 👉 Explore relatable memes and get access to exclusive updates on Instagram - https://www.instagram.com/scaler_official/ 📢 Be a part of our one of a kind telegram community: https://t.me/Scalercommunity 🔔 Hit that bell icon to get notified of all our new videos 🔔 If you liked this video, please don't forget to like and comment. Never miss out on our exclusive videos to help boost your coding career! Subscribe to Scaler now! https://www.youtube.com/Scaler?sub_confirmation=1 #dynamicprogramming #dsalgo #knapsack

Course Hive

Continue this lesson in the app

Install CourseHive on Android or iOS to keep learning while you move.

Related Courses

FAQs

Course Hive
Download CourseHive
Keep learning anywhere