760.1K
NOComment Excel to get the document in your DM.
#datascience #dataanalytics #excel #codebasics #9to5
@noodle.brain_
#Codebasics
Schauen Sie sich 3.5K Reels-Videos über Codebasics von Menschen aus aller Welt an.
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CHHere are the recommendations that were given to me by you:
1. YT playlist: Code with Aryan Mittal
2. YT playlist: LLD Basics to Advanced by Shrayansh Jain (members only, I have taken the subscription for a month)
3. GitHub repo: awesome lld
4. Website: refactoring guru
5. Course: Educative.io system design
6. Other YT channels: Gaurav Sen, Hello Interview and byte byte go (not LLD specific)
I started with Shrayansh Jain’s YT playlist last week for the following reasons:
1. Designed for Java developers
2. Design patterns and practice problems are structured together instead of one after another.
3. I have taken a paid subscription for a month so that I actually push myself to complete it before that.
LLD is all about practice so I am not sticking to one resource and will be practicing using ChatGPT as well.
Let me know if I missed out on anything :)
#buildinpublic #softwaredeveloper #javadeveloper #engineering #study
@chubbytoday
11.5K
AN📩roadmap
This is from Krish naik’s 6 month road map:
1) start with PYTHON. Resources: krish naik playlist/ sentdex playlist / Corey Schafer playlist.
Sub part -> Flask. Resources: Corey Schafer/ Krish Naik.
2) next, STATS. Resources: Statsquest / Abhinandan Sarkar - great learning on YouTube / Krish Naik
3) EDA - resources: I followed krish naik, I don’t really know anyone else. You can just check up “EDA projects” as well.
4) FEATURE ENGINEERING. Resources: Krish Naik/ Code Basics (this one is a resource for other concepts too!)
5) DATABASES. Resources: trendy tech insights/ kudvenkat/ Ankit Bansal. LEETCODE!!!!
6) Machine Learning & Deep Learning. haven’t started this yet, but I plan on learning it from either Krish Naik, Andrew Ng, code basics, or sentdex. Haven’t decided yet😗
Data Science is a(random?) FOREST. And it can be difficult to navigate through, but if you’re just getting started, here’s a tip for you: pick one resource, ANY resource, and just start. Be consistent, because doing something everyday has a compounding effect that pays in the future. And finally, if you feel overwhelmed, remember - one step at a time. One day at a time. One concept at a time.
All the best!
@anushka.ipynb
471.3K
SAWhat is an API? 🤯
How do APIs work?👾
How can APIs save developers huge amount of time? 🚀
Prepare for your next interview starting from the basics. Mastering the basics and not taking shortcuts will give you a solid ground to build your knowledge on.
Software engineers should know this as it is the bread and butter of building complex systems 🫡
The simplest explanation of an API you will find online 👾
#code #softwareengineering #computerscience
@sayed.developer
145.4K
WT🚀 Got placed in 3 months. No connections. No shortcuts.
Here’s the exact roadmap 👇
---
📅 Month 1 – Build Foundation
- Pick ONE tech stack (Web Dev / App Dev / Data)
- Learn basics (HTML, CSS, JS OR your domain)
- Start DSA daily (arrays, strings)
- Start core subjects (OOP basics)
- Build 1 small project
- Code 2–4 hrs daily
---
📅 Month 2 – Build Proof
- Learn intermediate (APIs, DB, frameworks)
- Build 2–3 real-world projects
- Push everything on GitHub
- DSA (linked list, stack, queue, recursion)
- Core subjects (DBMS basics + OS intro)
- Start posting your journey (LinkedIn / Insta)
---
📅 Month 3 – Get Opportunities
- Improve resume (ATS friendly)
- Apply to 20–30 jobs/internships DAILY
- DSA (trees, graphs, DP basics)
- Practice interview questions daily
- Core subjects (OS, DBMS, CN basics)
- Cold DM & network on LinkedIn
---
⚡ Truth:
- You don’t need perfect skills
- You need consistency + proof of work
---
💬 Comment “ROADMAP” for resources & templates
#placement #dsa #tech
@wtf.rupesh
304
COWe asked Aamod, our Data Science Academic, to share his Top 3 go-to resources, the ones he actually follows to stay sharp in the fast-moving world of data! Here are his all-time favourite YouTube channels to podcasts that break down real-world ML and AI trends
* Tina Huang @hellotinah
* Code Basics @codebasicshub
* Date Science at Home Podcast @datascienceathome
Whether you're just starting out or deep in the field, these are worth checking out.
👇 Got a favourite data science podcast or YouTube channel? Drop it in the comments, we’re always down to discover more!
@coder_academy
798.0K
HUFor a very long time I kept complicating life, not knowing everything else starts working out when you fix the basics.
Somewhere along the way I forgot how to simplify & forgot what to prioritise, but this stayed constant.
Life truly changes when your habits change!
@muscleblaze | Code: NIHARIKAMB
[workout, fitness, mindset, growth, hobbies, mental health, success, growth mindset, sports]
@humaninsane__
146
CRUI Sketch to Code Basics 🚀
Tech Project: Planteva
From understanding the idea…
to sketching the UI…
to slowly turning it into real code.
This is how real tech projects begin —
not perfect, but clear and structured.
No shortcuts.
Just raw learning + real execution.
Follow @crack_front_end
we work on real client projects.
Learn with us:
• How we work on tech projects
• How we handle real clients
• How we prepare for jobs step by step
• Raw & real progress — no filters 🚀
@crack_front_end
38
TA🎓 Data Analyst Roadmap: How to Become a Data Analyst
🔗 https://www.takethiscourse.net/data-analyst-roadmap/
Only Data Analysts can Relate!
📊 Elevate Your Data Game! 🚀 As data analysts, we go beyond just sending reports; we're the backbone of informed decision-making! Here's a quick checklist to ensure our reports are nothing short of exceptional:
✅ Data Sources Listed: Transparency is key! Ensure your stakeholders know exactly where your data is coming from.
✅ Refresh Time Mentioned: Keep it current! Let your audience know when your data was last updated to make informed decisions.
✅ Currencies Mentioned: Money talks! Specify the currency to avoid any misinterpretations.
✅ Abbreviated Acronyms: No room for confusion! Spell out acronyms or provide a handy glossary.
✅ Exclusions/Filters Mentioned: What's in, what's out? Be crystal clear about any exclusions or filters applied in your analysis.
✅ New Formula Explanations: Decode the magic! If you're introducing new formulas, break them down for everyone to follow.
But wait, there's more! 🌐 Unlock your full potential with these top-notch courses from prestigious universities and instructors:
🎓 **Data Science: Visualization by HARVARD**
🔗 https://www.takethiscourse.net/best-free-data-visualization-courses/#Data-Science:-Visualization
🎓 **Mastering Data Analysis in Excel by Duke University**
🔗 https://www.takethiscourse.net/mastering-data-analysis-in-excel/
🎓 **Data Analysis with Python by IBM**
🔗 https://www.takethiscourse.net/data-analysis-with-python/
🎓 **Best Data Visualization Techniques**
🔗 https://www.takethiscourse.net/data-visualization-techniques/
Embark on a journey of continuous learning and stay ahead in the dynamic world of data analytics! 💡📈 #DataAnalytics #ContinuousLearning #DataDrivenDecisions #ProfessionalDevelopment
Video Credit: Code Basics
@takethiscourse
316.5K
TE🚀 Got placed in 3 months.
No connections. No shortcuts.
Here’s the exact roadmap👇
📅 Month 1 – Build Foundation
• Pick ONE tech stack (Web Dev / App Dev / Data)
• Learn basics (HTML, CSS, JS OR your domain)
• Start DSA daily (arrays, strings)
• Start core subjects (OOP basics)
• Build 1 small project
• Code 2–4 hrs daily
📅 Month 2 – Build Proof
• Learn intermediate (APIs, DB, frameworks)
• Build 2–3 real-world projects
• Push everything on GitHub
• DSA (linked list, stack, queue, recursion)
• Core subjects (DBMS basics + OS intro)
• Start posting your journey (LinkedIn / Insta)
📅 Month 3 – Get Opportunities
• Improve resume (ATS-friendly)
• Apply to 20–30 jobs/internships DAILY
• DSA (trees, graphs, DP basics)
• Practice interview questions daily
• Core subjects (OS, DBMS, CN basics)
• Cold DM & network on LinkedIn
⚡ Truth:
• You don’t need perfect skills
• You need consistency + proof of work
💬 Comment “ROADMAP” for resources & templates
#placementprep #DSA #tech #jobsearch career learning
@tech.ashishh
155.6K
SOData Science Course From Microsoft 😎
If you’re trying to get started in data science, what better place to start than from a course from Microsoft. This GitHub repository is completely free and starts from the absolute basics. Don’t know what data science even is? It explains that too!
Follow for more free coding resources ✅
#code #coding #tech #learntocode #datascience
@softwarewithnick
65.6K
DKComment “AI” to get the 2026 Vibe Coding Rules PDF 🚀
Everyone wants to vibe code…
but nobody shows how to not break your app ⚠️
This free guide explains the real non-negotiables every builder must understand in 2026:
.env security, npm run dev vs build, git basics, environment variables, authentication systems, and database schemas.
If you’re building SaaS, AI apps, automations, or side projects with Claude, Cursor, or other AI coding tools — this will save you from common beginner mistakes and production failures.
.
.
[ Learn how modern builders use vibe coding the right way — secure setup, clean deployments, proper auth, and database structure , so your AI-built app actually ships. ]
#VibeCoding #AICoding #BuildSaaS #IndieHacker #AI2026
@dk.mindset
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Was ist in #Codebasics im Trend? Die meistgesehenen Reels-Videos und viralen Inhalte sind oben zu sehen.
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