Syed Luqman Quadri

Kafka Architecture Explained In A Nutshell : - Producers: Send data (logs, events) to topics. - Topics: Categories for storing and publishing data streams. - Consumers: Subscribe to topics and process incoming data. - Partitions: Scalable units within a topic for concurrent processing. - Brokers: Manage message storage and delivery across a cluster for fault tolerance. - Replicas: Backups of partitions to prevent data loss. - Zookeeper: Oversees the cluster, tracking topics and nodes. - Push/Pull: Producers push data, consumers pull at their own pace. -------------------------------------------------------------- 📌 Save this post for later and follow Hina Arora for more insightful information.

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25 Papers That Completely Transformed the Computer World.    1. Dynamo - Amazon’s Highly Available Key Value Store  2. Google File System: Insights into a highly scalable file system  3. Scaling Memcached at Facebook: A look at the complexities of Caching  4. BigTable: The design principles behind a distributed storage system  5. Borg - Large Scale Cluster Management at Google  6. Cassandra: A look at the design and architecture of a distributed NoSQL database  7. Attention Is All You Need: Into a new deep learning architecture known as the transformer  8. Kafka: Internals of the distributed messaging platform  9. FoundationDB: A look at how a distributed database  10. Amazon Aurora: To learn how Amazon provides high-availability and performance  11. Spanner: Design and architecture of Google’s globally distributed databas  12. MapReduce: A detailed look at how MapReduce enables parallel processing of massive volumes of data  13. Shard Manager: Understanding the generic shard management framework  14. Dapper: Insights into Google’s distributed systems tracing infrastructure  15. Flink: A detailed look at the unified architecture of stream and batch processing  16. A Comprehensive Survey on Vector Databases  17. Zanzibar: A look at the design, implementation and deployment of a global system for managing access control lists at Google  18. Monarch: Architecture of Google’s in-memory time series database   19. Thrift: Explore the design choices behind Facebook’s code-generation tool  20. Bitcoin: The ground-breaking introduction to the peer-to-peer electronic cash system  21. WTF - Who to Follow Service at Twitter: Twitter’s (now X) user recommendation system  22. MyRocks: LSM-Tree Database Storage Engine  23. GoTo Considered Harmful  24. Raft Consensus Algorithm: To learn about the more understandable consensus algorithm  25. Time Clocks and Ordering of Events: The extremely important paper that explains the concept of time and event ordering in a distributed system    Over to you: I’m sure we missed many important papers. Which ones do you think should be included? -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://bit.ly/bbg-social   #systemdesign #coding #interviewtips  .

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LeetCode has 3374 problems But Most PBCs repeat these 20 🔻 1. 𝐀𝐫𝐫𝐚𝐲𝐬 & 𝐇𝐚𝐬𝐡𝐢𝐧𝐠 (Google, Amazon, Meta, Microsoft) → Two Sum, Longest Consecutive Sequence, Subarray Sum Equals K 2. 𝐒𝐥𝐢𝐝𝐢𝐧𝐠 𝐖𝐢𝐧𝐝𝐨𝐰 & 𝐓𝐰𝐨 ��𝐨𝐢𝐧𝐭𝐞𝐫𝐬 (Google, Meta, Amazon) → Longest Substring Without Repeating Characters, Container With Most Water, Minimum Window Substring 3. 𝐒𝐭𝐚𝐜𝐤 & 𝐌𝐨𝐧𝐨𝐭𝐨𝐧𝐢𝐜 𝐒𝐭𝐚𝐜𝐤 (Google, Amazon, Facebook) → Valid Parentheses, Largest Rectangle in Histogram 4. 𝐁𝐢𝐧𝐚𝐫𝐲 𝐒𝐞𝐚𝐫𝐜𝐡 (Google, Amazon, Meta) → Search in Rotated Sorted Array, Median of Two Sorted Arrays 5. 𝐋𝐢𝐧𝐤𝐞𝐝 𝐋𝐢𝐬𝐭 (Google, Amazon, Meta) → Merge Two Sorted Lists, Detect Cycle in Linked List 6. 𝐓𝐫𝐞𝐞𝐬 & 𝐆𝐫𝐚𝐩𝐡𝐬 (Google, Meta, Amazon) → Lowest Common Ancestor, Word Ladder, Number of Islands 7. 𝐃𝐲𝐧𝐚𝐦𝐢𝐜 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 (Google, Amazon) → Climbing Stairs, Longest Palindromic Substring, Coin Change 8. 𝐇𝐞𝐚𝐩𝐬 & 𝐏𝐫𝐢𝐨𝐫𝐢𝐭𝐲 𝐐𝐮𝐞𝐮𝐞𝐬 (Amazon, Google, Meta) → Kth Largest Element, Merge K Sorted Lists Remember, you don’t need to solve thousands of problems to crack your target company. A focused, strategic approach on key topics works best. And you can get exactly this by connecting with senior SDEs from top PBCs. 🔥 Just connect with them for FREE here: https://lnkd.in/gqfsRHDS They’ll guide you through in-depth DSA concepts, help you recognize common patterns, and teach company-specific coding practices. With mock interviews and real-time feedback, you'll be ready to crack DSA interviews and land your dream job. 💪 PS: Sometimes, stepping back and asking for help is the smartest move. #dsaquestions #dsatopics #collab #preplacedcollab #interviewprep #techinterviews #interviewtips

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Ever Wondered How Netflix Works So Well? Here's the Secret! Netflix brings your favorite shows and movies right to your screen, but how does it do that? Here’s a look at the cool tech behind it: 1. Microservices Architecture Netflix uses something called "microservices," which means instead of one big computer doing everything, there are lots of small computers working together. This helps Netflix run smoothly and fix problems quickly. 2. AWS Cloud Netflix uses a service called AWS (Amazon Web Services) to store all its data and run everything online. It’s like Netflix's superpower that helps it work from anywhere in the world. 3. Open Connect Netflix has its own special system, called Open Connect, to send shows and movies quickly to everyone, no matter where they are. 4. Programming Languages Netflix uses different computer languages like Java, Python, and Node.js to build both the backend (stuff happening behind the scenes) and the front end (stuff you see on the screen). 5. Big Data & AI Netflix uses tools like Apache Kafka and Apache Spark to understand what you like to watch and recommend new shows and movies just for you! 6. Security Netflix makes sure your personal information is safe by using strong security systems, kind of like a digital lock for your data. 7. Chaos Engineering Netflix even uses a fun-sounding thing called Chaos Monkey! It randomly tests Netflix to make sure it can keep working even if something goes wrong. Netflix’s tech helps it stay fast, smart, and fun. It's like a magic trick behind the scenes that makes watching easy for us! ------------------------------------------------ 👉 👉 Follow Hina Arora for more such content. #NetflixTech #Innovation #Technology

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Self hosting and Managing PostgreSQL at scale is a bottleneck for Ops Engineers 😟 So, PostgreSQL is one of the most widely used open-source, object-relational database management systems (ORDBMS). However, self-hosting comes with a lot of challenges. ⭕ Horizontal Scaling can be complex and requires manual sharing and replication. ⭕ Zero downtime updates and upgrades is a myth in self-hosted systems. ⭕ Uptime of the system. ⭕ Periodic backups. ⭕ Configuring firewalls, user permissions and encryption is quite tedious. Honestly, I have also experienced this in the past and explored managed PostgreSQL service by cloud providers. While they are good, they are deeply integrated with the cloud provider and restricts engineers to that cloud provider ecosystem. Last week I tried Aiven for PostgreSQL which is a fully managed and hosted database service with an Object-Relational Database Management System. Unlike the other solutions, Aiven for PostgreSQL is cloud agnostic. You can choose between the cloud providers. Not only that, Aiven for PostgreSQL offers: ✅ Aiven AI Database Optimizer to solve Postgres performance issues in minutes with AI-driven performance insights and optimization suggestions.  ✅ SQL rewrite recommendations to write performant code 100x faster. ✅ Automatic updates and upgrades to significantly reduce the ops team's effort. ✅ Secure and complaint (ISO 27001:2013, SOC2, GDPR, HIPAA, and PCI/DSS). ✅ 99.99 % uptime. ✅ 100 % human support in case of any help. ✅ No hidden networking costs. ✅ Point-In-Time-Recovery. Aiven is currently offering 100 USD credit for referrals who sign up through my link. ❗Don’t miss the opportunity (100 USD on free sign up) https://fnf.dev/3HiiOsP Thanks to Aiven for sponsoring this post and giving away credits to the signups.

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🚀 Instagram's Architecture: The Backbone of a Global Platform With over 2 billion users, Instagram stands as a giant in the social media landscape. Its success is driven by a scalable, high-performance architecture that ensures seamless user experience worldwide. Let’s break it down: 🏗️ Microservices for Scalability Instagram follows a microservices architecture, allowing independent development and scaling of services as needed. This approach enhances flexibility, reliability, and efficiency. 🌍 Global Content Delivery Network (CDN) A powerful CDN ensures that images, videos, and other media load quickly by caching frequently accessed content at geographically distributed edge locations, reducing latency and enhancing performance. 🔥 Tech Stack Powering Instagram Instagram uses a diverse technology stack to handle various functionalities: 🔹 Frontend: React (UI), GraphQL (API), Swift (iOS), Kotlin (Android) 🔹 Backend: Django (framework), Gunicorn (web server) 🔹 Data Storage: PostgreSQL (relational DB), Cassandra (NoSQL for scalability), CockroachDB (distributed SQL), Memcached (caching) 🔹 Messaging & Streaming: Apache Kafka (real-time data streaming), Scuba (internal messaging) 🔹 Data Processing: Apache Spark (big data processing), Presto (ad-hoc queries), Scuba (internal pipelines) 🔹 DevOps & Monitoring: Kubernetes (orchestration), Docker (containers), ELK Stack (logging), Prometheus (monitoring) Instagram’s robust infrastructure ensures that billions of users enjoy a smooth, fast, and engaging experience every day. Its blend of cutting-edge technologies, microservices, and scalable storage solutions makes it one of the most efficient social media platforms. 💬 What are your thoughts on Instagram’s architecture? Drop a comment below! Follow Aarchi Gandhi for more such tech insights :)

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After interviewing with companies like Red Hat, Intuit , Nutanix , Autodesk etc Here are the frontend topics that have come up repeatedly and are super important for interviews :- 𝟏. 𝐒𝐭𝐚𝐭𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 (𝐑𝐞𝐚𝐜𝐭): Context API vs Redux – when to use, pros/cons, and how to overcome limitations 𝟐. 𝐀𝐬𝐲𝐧𝐜 𝐢𝐧 𝐉𝐚𝐯𝐚𝐒𝐜𝐫𝐢𝐩𝐭: Callbacks vs Promises vs async/await. Avoiding callback hell, retry patterns, parallel API calls 𝟑. 𝐏𝐫𝐨𝐦𝐢𝐬𝐞 𝐀𝐏𝐈: all, allSettled, race, any – use cases and error handling 𝟒. 𝐏𝐨𝐥𝐲𝐟𝐢𝐥𝐥𝐬: Write polyfills for map, bind, call, Promise.all, etc. 𝟓. 𝐑𝐞𝐚𝐜𝐭 𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐥𝐬: Virtual DOM, reconciliation, re-renders, and performance tips 𝟔. 𝐇𝐨𝐨𝐤𝐬 𝐃𝐞𝐞𝐩 𝐃𝐢𝐯𝐞: Using useMemo, useCallback, useRef, and custom hooks in real projects 𝟕. 𝐉𝐒 𝐑𝐮𝐧𝐭𝐢𝐦𝐞 & 𝐄𝐯𝐞𝐧𝐭 𝐋𝐨𝐨𝐩: Microtasks vs macrotasks – real examples that impact async behavior 𝟖. 𝐂𝐨𝐝𝐞 & 𝐃𝐞𝐛𝐮𝐠𝐠𝐢𝐧𝐠: JS questions with this, closures, hoisting, and fixing broken code snippets #Note: Knowing the concepts isn't enough. Interviewers want to see your thought process - like why you'd choose Context API over Redux, or how you'd debug a closure issue. I underestimated this, and it took me multiple failed attempts to improve. But you can avoid this by preparing with senior SDEs on interview panels. They'll help you justify design decisions and discuss trade-offs with confidence. ✅ Just connect with them for FREE here: https://lnkd.in/gG4Z5Hin With real interview-style feedback, you'll learn to highlight the right details and stand out in the hiring process. From upskilling and resume building to referrals and interview prep, they'll support your entire job search journey. Give it a try! 💪 #javascript #interviewtopics #paidpartnership #techinterviews #frontend

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🏗️ Top 25 System Design Interview Q&A – Build Big, Think Smart!🧠 Prepare for high-level technical interviews with this curated list of 25 essential system design questions and answers, covering topics like scalability, load balancing, database design, caching, microservices, and fault tolerance. A must-have for backend and full-stack developers! 🔁 Repost & Share with others to help them upskill! 📢 Follow Sakshi Singh Kushwaha for more such content. #SystemDesign #TechInterviews #SoftwareArchitecture

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𝗝𝗪𝗧 (𝗝𝗦𝗢𝗡 𝗪𝗲𝗯 𝗧𝗼𝗸𝗲𝗻) is an open standard for securely exchanging JSON data between parties. This data is verifiable and trustworthy due to its digital signature. JWTs consist of three parts: 𝗛𝗲𝗮𝗱𝗲𝗿: Specifies the token type and signing algorithm. 𝗣𝗮𝘆𝗹𝗼𝗮𝗱: Contains claims, key-value pairs representing entity data. 𝗦𝗶𝗴𝗻𝗮𝘁𝘂𝗿𝗲: Verifies the integrity of the message and ensures that it has not been tampered with. Implementing JWT authentication in your API is straightforward and enhances the security of your endpoints. To learn more about JWT Authentication, check out my blog post: https://lnkd.in/dJ9wkHiB Share your thoughts in the comments below.👇 If you find this content helpful, consider following me for more daily insights! Feel free to repost to share the knowledge. ♻

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🔧 System Design isn’t just about code — it’s about engineering thinking. Thinking of cracking that FAANG interview or designing systems that actually scale? Then you need more than Leetcode. You need architecture intuition. 📘 I recently came across “System Design for FAANG” by Ravi Tandon — and it’s one of the most well-structured, realistic, and practically useful guides out there. Here’s what makes it a must-read: ➡️ Breaks down what FAANG really looks for in system design interviews ➡️ Covers trade-offs like CAP theorem, latency vs consistency, and vertical vs horizontal scaling ➡️ Explains key components — Load Balancers, CDNs, caching layers, sharding, queues, and more ➡️ Real-world use cases — think URL shorteners, rate limiters, notification engines, and more ➡️ Whether you're: Aiming for FAANG Moving into Senior/Architect roles Or just curious how scalable systems really work... This guide helps you think like a systems engineer — not just a coder. 💡 It's not theory. It's insight + real-world application. 👇 Drop a like if you want more such reads in your feed! #SystemDesign #FAANG #ScalableSystems #SoftwareArchitecture #EngineeringMindset #CareerGrowth #TechLeadership

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🌟 Master Kafka & Build Scalable Real-Time Systems! Apache Kafka is a powerful, distributed event streaming platform used by companies like LinkedIn, Netflix, and Uber to handle massive amounts of real-time data. Let's break it down: 1. What is Kafka? Apache Kafka is an open-source system designed for: ✅ Messaging – Sending and receiving real-time data ✅ Streaming – Processing data as it arrives ✅ Distributed Storage – Storing data across multiple servers It is used for applications that need fast, scalable, and fault-tolerant data processing. 2. How Kafka Works? Kafka follows a Pub-Sub (Publish-Subscribe) model where: 🔹 Producers → Send messages to Kafka 🔹 Topics → Organize messages into categories 🔹 Brokers → Store and distribute data across servers 🔹 Consumers → Receive and process messages Think of Kafka as a giant message queue where producers send data, and consumers pick it up whenever needed. 3. Key Kafka Concepts ✅ Broker → A server that handles Kafka requests ✅ Topic → A category where messages are stored ✅ Partition → A way to split topics for scalability ✅ Offset → The unique ID of each message ✅ Consumer Group → A set of consumers that work together 🔹 Example: Netflix uses Kafka to track user actions (like watching a movie). Every time you play, pause, or stop, Kafka sends this data to different services for recommendations, analytics, and more. 4. Why Use Kafka? 🔹 High Throughput → Handles millions of messages per second 🔹 Scalability → Easily adds new servers 🔹 Fault Tolerance → Data is replicated across brokers 🔹 Real-Time Processing → Instant insights from data Use Cases: ✅ Log Monitoring (Elasticsearch, Splunk) ✅ Fraud Detection (Banking, FinTech) ✅ Chat Applications (WhatsApp, Slack) ✅ Real-Time Analytics (Stock Markets, IoT Devices) 5. Kafka vs. Traditional Messaging Queues Kafka is ideal for large-scale data streaming, while traditional MQs are better for smaller workloads. Follow Suraj Dubey for your daily dose of web development insights. 💡 What’s your favorite Kafka use case? Drop a comment below! 👍 Found this helpful? Like it! 🔁 Share it with your network. 🔖 Save for quick reference. 📤 Forward to a friend or colleague. 💬 Join the discussion in the comments! 📝 Credit: BigData P.S.: Kafka is the heartbeat of real-time data—learn it before your competitors do!

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𝗧𝗼𝗽 𝟱𝟬 𝗦𝗗𝗘 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 🔥 Over the past weeks, I am looking for a list of the Top 50 Most Asked SDE Interview Questions (Easy → Medium → Hard) & yes, here you go. These aren’t random, I have talked with one of my friend in Microsoft and he told, they’re the very problems that companies like MAANG, Microsoft, and top product firms ask again and again. Here’s how I suggest you use this guide: 1️⃣ Start with Easy problems → build rhythm. 2️⃣ Move to Mediums → focus on techniques like sliding window, binary search, recursion. 3️⃣ Take on Hards → practice under timed conditions, simulate interviews. 4️⃣ Track progress → Don’t just solve, review and re-solve. 5️⃣ Pair it with mock interviews → confidence comes from simulation. 📚 This resource covers classic problems like: - Longest Substring Without Repeating Characters - Zigzag Conversion - Search in Rotated Sorted Array - Edit Distance - Trapping Rain Water …and 45 more! PDF credit: HeyCoach Follow Arijit Ghosh for more roadmaps Comment 'SDE' and I will DM you this document directly to your inbox. ⏰ Don't wait - your dream job interview could be next week! #interview #maang

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I breakdown complex concepts/use cases here in LinkedIn almost everyday. Here are 6 posts from the past 2 weeks that you might have missed: ✅ How Zomato uses Apache Flink at scale? https://lnkd.in/dQEfwzsX ✅ OpenAI operates on a single unsharded PostgreSQL instance supported by numerous read replicas https://lnkd.in/dEKqsrjZ ✅ DeDuplicate Data in a Lakehouse. https://lnkd.in/dGEgxcwV ✅ Streaming ETL with Apache Flink + Apache Hudi https://lnkd.in/d7Gi3vnn ✅ Lakehouse Cost - With & Without Index 💵 https://lnkd.in/dneyr_W6 ✅ Apache Parquet Optimizations - Statistics, Dictionary and Bloom Filter! https://lnkd.in/dwMqHuWJ LMK what else within lakehouse, database & distributed systems interests you. Happy reading! #dataengineering #softwareengineering

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I got multiple offers and these are the most asked repeatedly String + Array Interview Questions list String-Based Questions 1. Reverse a string — without using built-ins. 2. Is it a palindrome? Let's find out. 3. Remove duplicates from a string — efficiently. 4. First non-repeating character — who stands alone? 5. Count how many times each character appears. 6. Flip the words in a sentence, not the letters. 7. Are two strings anagrams? Prove it. 8. Longest substring without repeats — sliding window style. 9. Build your own atoi — string to integer. 10. Compress strings with run-length encoding. 11. Most frequent character — who dominates? 12. List all possible substrings of a string. 13. Is one string a rotation of another? 14. Strip all white spaces from a string. 15. Is this a valid shuffle of two strings? 16. Convert text to Title Case — properly. 17. Find the longest common prefix among words. 18. Break a string into a char array — without confusion. 19. Replace spaces with %20 — classic URL trick. 20. Turn full sentences into acronyms. 21. Check if the string is all digits — no alphabets allowed. 22. Count how many words are in the string. 23. Remove a specific character — cleanly. 24. Find the shortest word in a sentence. 25. Longest palindromic substring — two-pointer style. Array-Based Questions 26. Reverse an array in-place. 27. Find the largest and smallest element. 28. Check for duplicates in an array. 29. Remove duplicates — return only unique values. 30. Find the missing number from 1 to N. 31. Move all zeros to the end — keep order. 32. Rotate the array left/right by K positions. 33. Find the Kth largest/smallest element. 34. Merge two sorted arrays — without using extra space. 35. Find the intersection of two arrays. 36. Sort 0s, 1s, and 2s without using sort(). 37. Find subarrays with a given sum. 38. Detect if a subarray sums to 0. 39. Find the longest increasing subsequence. 40. Kadane’s Algorithm — maximum subarray sum. 41. Check if array is sorted and rotated. 42. Rearrange array in max-min order alternately. 43. Find leaders in an array (no greater element to the right). 44. Calculate frequency of all elements in O(n). 45. Product of all elements except self.

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80% of system design concepts and interview questions stem from just 20% of core problems 1️- Scalability & Performance 🌐Load Balancing (LB algorithms, HAProxy, Nginx) 🌐 Caching Strategies (LRU, Write-Through, Write-Back) 🌐 Database Sharding vs. Partitioning 🌐 Indexing & Query Optimization 🌐 CDN & Edge Computing 🌐 Asynchronous Processing (Queues, Event-driven architecture) 2️- Data Storage & Databases 🌐 SQL vs NoSQL (When to use what) 🌐 CAP Theorem PACELC Theorem & Trade-offs 🌐 Data Replication Strategies 🌐 Indexing & Query Optimization 🌐 Multi-Region Deployment 🌐 Time-Series & Event-Driven Databases 3️- High Availability & Fault Tolerance 🌐 Leader Election and Consensus Protocols (Paxos, Raft) 🌐 Replication & Failover Mechanisms 🌐 Distributed Transactions (2PC, Saga Pattern) 🌐 Rate limiting, Circuit Breakers & Retries 🌐 Chaos Engineering & Failure Testing 4️- API Design & Communication 🌐 REST vs. GraphQL vs. gRPC 🌐 Rate Limiting & API Gateway 🌐 WebSockets & Long Polling 🌐 Service Discovery & Load Balancing 🌐 Message Queues (Kafka, RabbitMQ, SQS) 🌐 Idempotency & API Versioning 5️- Security & Compliance 🌐 Authentication & Authorization (OAuth, JWT) 🌐 Rate Limiting & DDOS Protection 🌐 Data Encryption (AES, TLS, HMAC) 🌐 Role-Based Access Control (RBAC) 🌐 Attribute-Based Access Control (ABAC) 🌐 Audit Logging & Monitoring 6️- Microservices & Distributed Systems 🌐 Monolith vs. Microservices vs. Serverless 🌐 Event-Driven Architectures 🌐 Saga Pattern for Distributed Transactions 🌐 Service Mesh (Istio, Linkerd) 🌐 API Gateway & BFF Pattern 🌐 Kubernetes & Container Orchestration 7️- Logging, Monitoring & Observability 🌐 Centralized Logging (ELK, Loki) 🌐 Distributed Tracing (Jaeger, OpenTelemetry) 🌐 Metrics & Dashboards (Prometheus, Grafana) 🌐 Real-time Alerts & Anomaly Detection 🌐 Service Health Checks 🌐 Log Aggregation & Storage Strategies – P.S: System design interviews are a critical evaluation point for mid-to-senior engineers, as they assess your ability to navigate trade-offs, manage competing constraints, and design systems that scale effectively. #systemdesign #soheib #webinarfarsi

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7 Free APIs for Your Next Project 1. OpenWeatherMap – Get real-time weather data and forecasts for any location. 2. NewsAPI – Stay updated with headlines from major news sources worldwide. 3. CurrencyFreaks – Convert and track exchange rates for 170+ currencies. 4. Unsplash API – Access high-quality, royalty-free images for your UI. 5. JokeAPI – Lighten up your app with programming and general jokes. 6. REST Countries – Fetch country data like population, flags, and geography. 7. SpaceX API – Explore rocket launches, past missions, and future plans. Perfect for web, mobile, or fun side projects! Never pay for online courses ever again. Let me explain... 🔵Join my telegram for regular job updates, free coding resources and premium notes: https://lnkd.in/dX2yMhH3 Google & Microsoft are offering FREE online courses with certification. This enables you to not just refine your skills and knowledge but also guarantees prudent decision-making regarding your finances. 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 𝐲𝐨𝐮 𝐰𝐢𝐥𝐥 𝐫𝐞𝐠𝐫𝐞𝐭 𝐧𝐨𝐭 𝐭𝐚𝐤𝐢𝐧𝐠 𝐢𝐧 𝟐𝟎𝟐5: 1. Microsoft Azure Data Scientist Associate 🔗https://lnkd.in/gC6p5fsx 2. Microsoft Cybersecurity Analyst Professional 🔗https://lnkd.in/gkSXinrs 3. Microsoft Power BI Data Analyst Professional 🔗https://lnkd.in/gxNtptGG 4. Microsoft Azure Data Engineering Associate (DP-203) Professional 🔗https://lnkd.in/gXTfmVFW 5. Microsoft Azure Developer Associate (AZ-204) Professional 🔗 https://lnkd.in/gCtvX26F 6. Microsoft Azure Security Engineer Associate (AZ-500) Professional 🔗https://lnkd.in/g33JAMuF 7. Advanced Google Analytics 🔗https://lnkd.in/gCu57Qjw 8. Google Project Management 🔗https://lnkd.in/gT2vj_9J 9. Agile Project Management 🔗https://lnkd.in/g7N_Hk8X 10. Project Execution: Running the Project 🔗https://lnkd.in/gfBXMKTN 11. Foundations of Project Management 🔗https://lnkd.in/gVE6UjP4 12. Project Initiation: Starting a Successful Project 🔗https://lnkd.in/g_vJnbPp 13. Project Planning: Putting It All Together 🔗https://lnkd.in/gxm3s-mq 14. Google Data Analytics: 🔗https://lnkd.in/gDJxRNMc 15. Get Started with Python 🔗https://lnkd.in/gw78DpKq 16. Crash Course on Python 🔗 https://lnkd.in/gaHzgN9g 17. Data Analysis with R Programming 🔗 https://lnkd.in/ghXCHCgf Credit pdf : respective owner 👉Follow Bharti Saini for more such content. #freecourses #freecertification #freeeducation #linkedinlearning #smartlearning #googlecertification #microsoftcertified

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