Follow this to optimise your linkedin profile 👇👇

Step 1: Upload a professional (looking) photo as this is your first impression

Step 2: Add your Industry and Location. Location is one of the top 5 fields that LinkedIn prioritizes when doing a key-word search. The other 4 fields are: Name, Headline, Summary and Experience.

Step 3: Customize your LinkedIn URL. To do this click on “Edit your public profile”

Step 4: Write a summary. This is a great opportunity to communicate your brand, as well as, use your key words. As a starting point you can use summary from your resume.

Step 5: Describe your experience with relevant keywords.

Step 6: Add 5 or more relevant skills.

Step 7: List your education with specialization.

Step 8: Connect with 500+ contacts in your industry to expand your network.

Step 9: Turn ON “Let recruiters know you’re open”

🔰 DevOps Roadmap for Beginners 2025

├── 🧠 What is DevOps? Principles & Culture
├── 🧪 Mini Task: Set up Local CI Pipeline with Shell Scripts
├── ⚙️ Linux Basics: Commands, Shell Scripting
├── 📁 Version Control: Git, GitHub, GitLab
├── 🧪 Mini Task: Automate Deployment via GitHub Actions
├── 📦 Package Managers & Artifact Repositories (npm, pip, DockerHub)
├── 🐳 Docker Essentials: Images, Containers, Volumes, Networks
├── 🧪 Mini Project: Dockerize a MERN App
├── ☁️ CI/CD Concepts & Tools (Jenkins, GitHub Actions)
├── 🧪 Mini Project: CI/CD Pipeline for React App
├── 🧩 Infrastructure as Code: Terraform / Ansible Basics
├── 📈 Monitoring & Logging: Prometheus, Grafana, ELK Stack
├── 🔐 Secrets Management & Security Basics (Vault, .env)
├── 🌐 Web Servers: Nginx, Apache (Reverse Proxy, Load Balancer)
├── ☁️ Cloud Providers: AWS (EC2, S3, IAM), GCP, Azure Overview

React with ♥️ if you want me to explain each topic in detail

#devops

Clean Code Tips

Here is a powerful 𝗜𝗡𝗧𝗘𝗥𝗩𝗜𝗘𝗪 𝗧𝗜𝗣 to help you land a job!

Most people who are skilled enough would be able to clear technical rounds with ease.

But when it comes to 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹/𝗰𝘂𝗹𝘁𝘂𝗿𝗲 𝗳𝗶𝘁 rounds, some folks may falter and lose the potential offer.

Many companies schedule a behavioral round with a top-level manager in the organization to understand the culture fit (except for freshers).

One needs to clear this round to reach the salary negotiation round.

Here are some tips to clear such rounds:

1️⃣ Once the HR schedules the interview, try to find the LinkedIn profile of the interviewer using the name in their email ID.

2️⃣ Learn more about his/her past experiences and try to strike up a conversation on that during the interview.

3️⃣ This shows that you have done good research and also helps strike a personal connection.

4️⃣ Also, this is the round not just to evaluate if you're a fit for the company, but also to assess if the company is a right fit for you.

5️⃣ Hence, feel free to ask many questions about your role and company to get a clear understanding before taking the offer. This shows that you really care about the role you're getting into.

💡 𝗕𝗼𝗻𝘂𝘀 𝘁𝗶𝗽 - Be polite yet assertive in such interviews. It impresses a lot of senior folks.

📊 Data Science Essentials: What Every Data Enthusiast Should Know!

1️⃣ Understand Your Data
Always start with data exploration. Check for missing values, outliers, and overall distribution to avoid misleading insights.

2️⃣ Data Cleaning Matters
Noisy data leads to inaccurate predictions. Standardize formats, remove duplicates, and handle missing data effectively.

3️⃣ Use Denoscriptive & Inferential Statistics
Mean, median, mode, variance, standard deviation, correlation, hypothesis testing—these form the backbone of data interpretation.

4️⃣ Master Data Visualization
Bar charts, histograms, scatter plots, and heatmaps make insights more accessible and actionable.

5️⃣ Learn SQL for Efficient Data Extraction
Write optimized queries (SELECT, JOIN, GROUP BY, WHERE) to retrieve relevant data from databases.

6️⃣ Build Strong Programming Skills
Python (Pandas, NumPy, Scikit-learn) and R are essential for data manipulation and analysis.

7️⃣ Understand Machine Learning Basics
Know key algorithms—linear regression, decision trees, random forests, and clustering—to develop predictive models.

8️⃣ Learn Dashboarding & Storytelling
Power BI and Tableau help convert raw data into actionable insights for stakeholders.

🔥 Pro Tip: Always cross-check your results with different techniques to ensure accuracy!

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DOUBLE TAP ❤️ IF YOU FOUND THIS HELPFUL!

WhatsApp is no longer a platform just for chat.

It's an educational goldmine.

If you do, you’re sleeping on a goldmine of knowledge and community. WhatsApp channels are a great way to practice data science, make your own community, and find accountability partners.

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ENJOY LEARNING 👍👍

Few common problems with lot of resumes:

1. 𝐈𝐫𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧.
I understand that there are a lot of achievements that we are personally proud of (things like represented school/clg in XYZ competition or school head/class head etc), but not all of them are relevant to technical roles. As a fresher, try to focus more on technical achievements rather than managerial ones.

2. 𝐋𝐚𝐜𝐤 𝐨𝐟 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬.
Many resumes have the same common projects, such as:
Creating just the front-end using HTML and CSS and redirecting all the work to an open-source API (e.g., weather prediction and recipe suggestion apps).

Most common projects are: -
Tic-tac-toe game.
Sorting algorithms visualizers.
To-do application.
Movie listing.

The codes for these projects are often copied and pasted from GitHub repositories.

Projects are like a bounty. If you are prepared well and have quality projects in your resume, you can set the tempo of the interview. It is one of the few questions that you will almost certainly be asked in the interview.

I don't understand why we can spend 2 years preparing for data structures and algorithms (DSA) and competitive programming (CP), but not even 2 weeks to create quality projects.
Even if your resume passes the applicant tracking system (ATS) and recruiter's screening, weak projects can still lead to your rejection in interviews. And this is completely in your hands.

I feel that this topic needs a lot more discussion about the type and quality of projects that one needs. Let me know if you want a dedicated post on this.

3. 𝐋𝐚𝐜𝐤 𝐨𝐟 𝐪𝐮𝐚𝐧𝐭𝐢𝐭𝐚𝐭𝐢𝐯𝐞 𝐝𝐚𝐭𝐚.
For technical roles, adding quantitative data has a big impact.
For example, instead of saying "I wrote unit tests for service X and reduced the latency of service Y by caching," you can say "I wrote unit tests and increased the code coverage from 80% to 95% of service X and reduced latency from 100 milliseconds to 50 milliseconds of service Y."

⌨️ JavaScript Array methods