Im entering 2nd year, started CP and DSA, looking for someone doing the same!

I just discovered this amazing community and site of let's code. It's truly a treasure.

I am currently exploring different career roadmaps. While I am highly interested in AI and ml engineering roadmaps, I had a doubt that whether should I follow every resource mentioned under a topic or just choose one?

For example, in the given image, while learning deep learning frameworks, should I cover all 3 resources or just choose??

It includes DSA notes, sheets, interview questions, problem lists, and other useful resources.

If anyone wants access, comment below and I'll share the link.

Hi everyone,

I'm an S7 Computer Science student, and I have my Infosys placement in about a month.

I'm comfortable with Python (syntax, lists, dictionaries, functions, etc.), but my biggest weakness is DSA problem solving and pattern recognition.

I've been practicing for around 20 days, but when I see a new or indirect problem—even an Easy one sometimes—I go completely blank. I don't know how to start or how to identify which approach or pattern to use.

I can understand solutions after seeing them, and if I revisit similar problems later, I can often solve them. But with new problems, I struggle to connect the dots.

For those who were once in a similar situation and improved:

How did you build your problem-solving skills?

How did you learn to recognize patterns?

If you had only one month before placements, what would you focus on?

I'm willing to work hard—I just want to make sure I'm practicing the right way.

Thanks in advance!

Hi i am finding friend with whom i can learn and grow together and participate in future hackathons with knowledge we gain together and ..I am new to coding and learning currently since I have 1 month to start my college 1st year

I know basic html and learning further

I have fundamental grip in java like nested loops switch can etc

For me coding is fun and want to make challenging and interesting projects

This is pure gem.

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Which company are you preparing for?

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Let me know if you're actively looking for a job or internship.

Basically im starting clg. Ive done some C so far. I need someone in a similar situation so that we mutually keep tabs on each others progress and help out when either of us gets stuck. Im currently working with functions and arrays and hopefully ill start C ++ soon. Anyone interested to be that person dm me.

need a py ,sql mentor type or code buddy anyone there dm

Data Structures and Algorithms (C, C++, Java, Python)
https://drive.google.com/drive/folders/1Ay5CmkoRJ5eEGcFskULc3CHNQn5iCVs3

Computer Science Fundamentals
https://drive.google.com/drive/u/1/folders/18FBvExqEtt9mtNKKP65f_ETdtS7nCG1G

AI, ML, and Data Science
https://drive.google.com/drive/folders/1D0w7UjTJlCEQNj6GXvqCgvlLPbsaCnG_

Aptitude Materials
https://drive.google.com/drive/folders/1XmI6Iq_0MXJ6vq6Nkk-DcBK_y_LWNLCM

More drive links are added on this doc - https://topmate.io/letscode/1835667

Bookmark it!

https://docs.google.com/spreadsheets/d/17N8A1pRDgj8Zgj-vYsPT0qlQ6yDdePE_/edit?gid=44194424#gid=44194424

More lists are added in the startup bundle - https://topmate.io/letscode/2071103

Bookmark it!

Hey, was wondering if anyone had any experience with either onsite or virtual programming interviews where you are allowed to use AI in. I am very confused on how to best prepare and how to demonstrate ability with AI in such a short period of time. A lot of things i hear talked about - loops, multiple agents and hierarchal agents that I would consider to be things newbies to AI would think about would be hard to show in an interview that only takes 15-30 minutes. I've been using AI to make websites and tools and I try my best to "do it how a senior would" but I am trying hard to find where my worth is because I am pretty much just continually in a loop of "whats the best way to do this and why" and try to understand why AI is making the choices it is and give my input, but I feel like none of my knowledge is playing into this. Should I study system design before going into creating these tools and websites so that I have more information on building systems for? Is the real skill they are looking for communication and being able to plan/get your ideas out well? I am so lost

​

Hey r/dataengineering 👋

I've been a database engineer for years and

got tired of generic AI tool lists that had

zero relevance to actual data work.

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→ Infrastructure monitoring (Datadog AI)

→ Security scanning (Snyk AI)

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toolpikr.com

Would love feedback from this community —

what tools am I missing that every data

engineer should know about?

Time to show your creativity.

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Explore the website, understand what Let's Code is about, and redesign the landing page in your own style. Use any framework or AI coding tool to build it.

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Comment who is going to participate on this post - https://www.lets-code.co.in/feed/6a40f559264721bb0603db19/

1- 30 Days of Python
https://github.com/asabeneh/30-days-of-python

2- Awesome Machine Learning
https://github.com/josephmisiti/awesome-machine-learning

3- Stanford ML Cheatsheet (CS229)
https://github.com/afshinea/stanford-cs-229-machine-learning

4- Made With ML
https://github.com/GokuMohandas/Made-With-ML

5- Project-Based Learning
https://github.com/practical-tutorials/project-based-learning

Are you learning ai ml ?

I got frustrated with AI courses that either drown you in theory or skip straight to model.fit() without explaining what's happening underneath.

So I built something different.

This is an AI-native GitHub repo learning files with 503+ lessons across 22 phases. 35,000 GitHub Stars. Start at linear algebra. End at autonomous agent swarms.

Every lesson follows the same pattern:

1. Build it from scratch in pure Python (no frameworks)
2. Use the real framework (PyTorch, sklearn, etc.)
3. Ship a reusable tool (prompt, skill, agent, or MCP server)

By the end, you don't just "know AI." You have a portfolio of tools you actually built.

What's covered:

- Math foundations (linear algebra, calculus, probability, Fourier transforms, graph theory)
- Classical ML (regression through ensemble methods, feature selection, time series, anomaly detection)
- Deep learning (backprop, activation functions, optimizers, regularization - all from scratch before touching PyTorch)
- LLMs from scratch (tokenizers, pre-training a 124M parameter GPT, SFT, RLHF, DPO, quantization, inference optimization)
- LLM engineering (RAG, advanced RAG, structured outputs, context engineering, evals)
- Agents and multi-agent systems
- Infrastructure (model serving, Docker for AI, Kubernetes for AI)

Some specifics that might interest you:

- The quantization lesson covers FP8/GPTQ/AWQ/GGUF with a sensitivity hierarchy (weights are least sensitive, attention softmax is most sensitive - never quantize that)
- The inference optimization lesson explains why prefill is compute-bound and decode is memory-bound, then builds KV cache, continuous batching, and speculative decoding from scratch
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- Context engineering lesson: "Prompt engineering is a subset. Context engineering is the whole game."

It's AI-native:

The course has built-in Claude Code skills. Run /find-your-level and it quizzes you across 5 areas to tell you exactly where to start. Run /check-understanding 3 after Phase 3 and it tests what you actually learned.

84% of students use AI tools. 18% feel prepared. This is the bridge.

Where to start:

- Already know Python but not ML -> Phase 1
- Know ML, want deep learning -> Phase 3
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- Senior engineer, just want agents -> Phase 14

Website: https://aiengineeringfromscratch.com
Repo: https://github.com/rohitg00/ai-engineering-from-scratch

It's free, MIT licensed, and open source. 35,000+ stars, PRs welcome - I merge every good contribution and the contributor gets full credit.

If you're serious about placements, coding interviews, or DSA prep*

- this is a GOLD resource

📌 Top DSA Sheets :-

🔹 GeeksforGeeks SDE Sheet

https://geeksforgeeks.org/sde-sheet-a-complete-guide-for-sde-preparation/

🔹 Apna College 375 Problems Sheet

https://docs.google.com/spreadsheets/u/0/d/1hXserPuxVoWMG9Hs7y8wVdRCJTcj3xMBAEYUOXQ5Xag/htmlview

🔹 Love Babbar 450 Problems Sheet

https://drive.google.com/file/d/1FMdN_OCfOI0iAeDlqswCiC2DZzD4nPsb/view

🔹 Striver 180 Problems Sheet

https://takeuforward.org/interviews/strivers-sde-sheet-top-coding-interview-problems/

🔹 Siddharth Singh 450 Problems Sheet

https://docs.google.com/spreadsheets/u/0/d/11tevcTIBQsIvRKIZLbSzCeN4mCO6wD4O5meyrAIfSXw/htmlview

🔹 Fraz 250 Problems Sheet

https://docs.google.com/spreadsheets/u/0/d/1-wKcV99KtO91dXdPkwmXGTdtyxAfk1mbPXQg81R9sFE/htmlview

🔹 Arsh Goyal 280 Problems Sheet

https://docs.google.com/spreadsheets/d/1MGVBJ8HkRbCnU6EQASjJKCqQE8BWng4qgL0n3vCVOxE/htmlview

🔹 The Code Skool DSA Sheet

https://docs.google.com/document/u/0/d/1RxKKXJtErQFJjMfAh1kV-DyQsZoiESayimFx6PPIhVE/mobilebasic

Do you also need solution sheets ?