How to Create an Effective DSA Study Roadmap as a Beginner?

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Asked By TechyTurtle92 On

Hey folks! I'm a second-year BTech student majoring in AIML and I've just started diving into Data Structures and Algorithms (DSA) seriously. Being a total beginner, I'm a bit lost on how to approach my studies step-by-step. I came across a phase-wise study plan that many recommend, which is divided into three phases:

- **Phase 1 (Beginner):** Covers essential topics like Arrays, Strings, Sorting, Searching, Recursion, Linked Lists, Stacks, Queues, Hash Maps/Sets, Two Pointers, Binary Trees, Graphs, and basic Dynamic Programming.
- **Phase 2 (Intermediate):** Focuses on more complex areas like Heaps, Backtracking, Tries, Disjoint Sets, and Advanced DP problems.
- **Phase 3 (Advanced + Theory):** Includes advanced topics such as Segment Trees, B+ Trees, and complex graph algorithms.

My question is: if I follow this phase-wise plan, will it align smoothly with DSA roadmaps from resources like roadmap.sh, or will I encounter confusion and possibly have to revisit topics? I want to approach this systematically without jumping around and getting lost. If anyone has experience with a similar path, I'd love your insights on how to proceed. Thanks in advance!

3 Answers

Answered By CoderNinja47 On

Your Phase 1 topics are all foundational for any programmer, so you’re starting off on the right foot. Phase 2 and 3 do include some specialized areas but are essential for a deeper understanding. Just keep in mind that DSA isn't a straightforward journey; each topic has layers. You shouldn't have to go back and relearn things, just dive deep while you're there!

TechyTurtle92 -

Thank you so much for the reassurance!

Answered By AIMLGeek21 On

I'm in a similar boat, trying to balance DSA with machine learning. DSA is really crucial for understanding algorithms, especially for placements even in our AIML field. I’m learning it for both university and potential internships. I try to dedicate about an hour each day to stay consistent. It can be tough to juggle with machine learning, but having a schedule really helps!

Answered By DebuggingDynamo On

Just a heads up, make sure to include formal complexity theory in your studies; it’s vital! And remember, each topic contains a lot of details, so it's okay if things don’t flow perfectly in a straight line. DSA is complex, but with a structured approach, you'll navigate it fine!

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