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Most quant resources teach pricing. Very few teach what actually matters on desks: Why money was made or lost. PnL attribution is not accounting. It is forensic analysis. When a book loses money, desks don’t ask what moved. They ask: Which assumption broke? Which hedge stopped working? Which parameter lied? Is this noise, or is the model structurally wrong? This guide formalizes what is normally learned only after years on a trading or risk desk. It shows how professionals reverse-engineer PnL to diagnose: Model failure vs market movement Hedging breakdowns vs liquidity effects Correlation collapses hidden inside “delta-neutral” books Theta bleed caused by mis-specified dynamics Residual PnL as an early warning system When traders are wrong, when models are wrong, and how to prove it How desks size model reserves before losses appear How stress regimes change the meaning of Greeks How to replay PnL under frozen vs recalibrated surfaces How risk, front-office, and model validation teams interpret the same losses differently The structure follows the real desk workflow: Clean vs dirty PnL decomposition Hedge-slippage triage (execution vs liquidity vs model) Correlation diagnostics using eigenvalues Residual PnL statistical testing Stress-event failure sequencing Governance, reserves, and escalation logic Real case studies written as forensic reports Interview-grade diagnostic frameworks and pressure questions This is not another pricing book. It is a model-agnostic survival manual for: Front-office quants Risk strategists Model validation teams Senior analysts And candidates who want to think like desks, not textbooks If pricing tells you what something is worth, PnL attribution tells you whether your understanding of the world is wrong. That skill compounds faster than any model. Coupon code PNL10 – Get 10% off Disclaimer This material is for educational purposes only. It does not constitute investment advice, trading advice, or a recommendation to buy or sell any financial instrument. Examples and case studies are illustrative and simplified to explain concepts. Market behavior, model performance, and risk outcomes vary over time and across institutions. The author and publisher accept no responsibility for trading losses, investment decisions, or actions taken based on this material. All content is proprietary and protected by copyright. Redistribution or commercial use without permission is prohibited

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Join our Salesforce program. Takeaways- -Unlimited Live Projects to Practice -One to One mentorship -Project Presentation and Implementations using sprints. Get exposure to different methodologies. -Mock Interviews with scenarios and listen from the experts in the industry about the interview questions. Get important interview questions for future reference. -Soft Skills Training to improve your communication as it plays a vital role in clearing your interviews

Observability/APM tools provide valuable insights into system behavior, performance, and availability. However, they often include extensive features that may not align with specific business needs. This template allows you to evaluate and compare APM and observability platforms based on your unique requirements. By scoring tools against critical criteria, you can identify the solution that offers the necessary capabilities without paying for unnecessary extras. Quantify must-have features, prioritize beneficial capabilities, and factor in pricing to choose the ideal observability tool that delivers value for your use case. With this template's guided scoring system, you can cut through promotional claims and benchmark solutions against your observability needs. Focus spending on the platform that best fits your needs, rather than overpaying for unused capabilities.

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Docker & Kubernetes: Learn from Scratch [2023 Edition] ( Videos + Notes + PDFs ) Learn Docker, Docker Compose, Multi-Container Projects, Deployment and all about Kubernetes from the ground up! 🔥 Get it full 24hrs videos at Rs.99/- INR only 💥 - English Content - Direct Gdrive Link Provided to Download Yourself - Permanent Access for Videos - Unlimited Downloads for lifetime - Lifetime Help support provided Videos Detailed Content: Welcome to the Course What Is Docker? Why Docker & Containers? Virtual Machines vs Docker Containers Docker Setup - Overview Docker Setup - macOS Docker Setup - Windows Docker Setup - Docker Toolbox for Older Systems An Overview of the Docker Tools Installing & Configuring an IDE Getting Our Hands Dirty! Course Outline How To Get The Most Out Of This Course Module Introduction Images & Containers: What and Why? Using & Running External (Pre-Built) Images Our Goal: A NodeJS App Building our own Image with a Dockerfile Running a Container based on our own Image Images are Read-Only! Understanding Image Layers A First Summary Managing Images & Containers Stopping & Restarting Containers Understanding Attached & Detached Containers Entering Interactive Mode Deleting Images & Containers Removing Stopped Containers Automatically A Look Behind the Scenes: Inspecting Images Copying Files Into & From A Container Naming & Tagging Containers and Images Time to Practice: Images & Containers - Problem Time to Practice: Images & Containers - Solution Sharing Images - Overview Pushing Images to Docker Hub Pulling & Using Shared Images Module Summary Module Introduction Understanding Data Categories / Different Kinds of Data Analysing a Real App Building & Understanding the Demo App Understanding the Problem Introducing Volumes A First, Unsuccessful Try Named Volumes To The Rescue! Getting Started With Bind Mounts (Code Sharing) Combining & Merging Different Volumes A NodeJS-specific Adjustment: Using Nodemon in a Container Volumes & Bind Mounts: Summary A Look at Read-Only Volumes Managing Docker Volumes Using "COPY" vs Bind Mounts Don't COPY Everything: Using "dockerignore" Files Working with Environment Variables & ".env" Files Using Build Arguments (ARG) Module Summary Module Introduction Case 1: Container to WWW Communication Case 2: Container to Local Host Machine Communication Case 3: Container to Container Communication Analysing the Demo App Creating a Container & Communicating to the Web (WWW) Making Container to Host Communication Work Container to Container Communication: A Basic Solution Introducing Docker Networks: Elegant Container to Container Communication How Docker Resolves IP Addresses Module Summary Module Introduction Our Target App & Setup Dockerizing the MongoDB Service Dockerizing the Node.js Moving the React SPA into a Container Adding Docker Networks for Efficient Cross-Container Communication Adding Data Persistence to MongoDB with Volumes Volumes, Bind Mounts & Polishing for the NodeJS Container Live Source Code Updates for the React Container (with Bind Mounts) Module Summary Module Introduction Docker-Compose: What & Why? Creating a Compose File Diving into the Compose File Configuration Docker Compose Up & Down Working with Multiple Containers Adding Another Container Building Images & Understanding Container Names Module Summary Module Introduction & What are "Utility Containers"? Utility Containers: Why would you use them? Different Ways of Running Commands in Containers Building a First Utility Container Utilizing ENTRYPOINT Using Docker Compose Module Summary Module Introduction The Target Setup Adding a Nginx (Web Server) Container Adding a PHP Container Adding a MySQL Container Adding a Composer Utility Container Creating a Laravel App via the Composer Utility Container Launching Only Some Docker Compose Services Adding More Utility Containers Docker Compose with and without Docker files Bind Mounts and COPY: When To Use What Module Introduction From Development To Production Deployment Process & Providers Getting Started With An Example Bind Mounts In Production Introducing AWS & EC2 Connecting to an EC2 Instance Installing Docker on a Virtual Machine Pushing our local Image to the Cloud Running & Publishing the App (on EC2) Managing & Updating the Container / Image Disadvantages of our Current Approach From Manual Deployment to Managed Services Deploying with AWS ECS: A Managed Docker Container Service More on AWS Updating Managed Containers Preparing a Multi-Container App Configuring the NodeJS Backend Container Deploying a Second Container & A Load Balance Using a Load Balancer for a Stable Domain Using EFS Volumes with ECS Our Current Architecture Databases & Containers: An Important Consideration Moving to MongoDB Atlas Using MongoDB Atlas in Production Our Updated & Target Architecture Understanding a Common Problem Creating a "build-only" Container Introducing Multi-Stage Builds Building a Multi-Stage Image Deploying a Standalone Frontend App Development vs Production: Differences Understanding Multi-Stage Build Targets Beyond AWS Module Summary Module Introduction Images & Containers Key Commands Data, Volumes & Networking Docker Compose Local vs Remote Deployment Module Introduction More Problems with Manual Deployment Why Kubernetes? What Is Kubernetes Exactly? Kubernetes: Architecture & Core Concepts Kubernetes will NOT manage your Infrastructure! A Closer Look at the Worker Nodes A Closer Look at the Master Node Important Terms & Concepts Module Introduction Kubernetes does NOT manage your Infrastructure Kubernetes: Required Setup & Installation Steps macOS Setup Windows Setup Understanding Kubernetes Objects (Resources) The "Deployment" Object (Resource) A First Deployment - Using the Imperative Approach kubectl: Behind The Scenes The "Service" Object (Resource) Exposing a Deployment with a Service Restarting Containers Scaling in Action Updating Deployments Deployment Rollbacks & History The Imperative vs The Declarative Approach Creating a Deployment Configuration File (Declarative Approach) Adding Pod and Container Specs Working with Labels & Selectors Creating a Service Declaratively Updating & Deleting Resources Multiple vs Single Config Files More on Labels & Selectors Liveness Probes A Closer Look at the Configuration Options Summary Module Introduction Starting Project & What We Know Already Kubernetes & Volumes - More Than Docker Volumes Kubernetes Volumes: Theory & Docker Comparison Creating a New Deployment & Service Getting Started with Kubernetes Volumes A First Volume: The "emptyDir" Type A Second Volume: The "hostPath" Type Understanding the "CSI" Volume Type From Volumes to Persistent Volumes Defining a Persistent Volume Creating a Persistent Volume Claim Using a Claim in a Pod Volumes vs Persistent Volumes Using Environment Variables Environment Variables & ConfigMaps Module Summary Module Introduction Starting Project & Our Goal Creating a First Deployment Another Look at Services Multiple Containers in One Pod Pod-internal Communication Creating Multiple Deployments Pod-to-Pod Communication with IP Addresses & Environment Variables Using DNS for Pod-to-Pod Communication Which Approach Is Best? And a Challenge! Challenge Solution Adding a Containerized Frontend Deploying the Frontend with Kubernetes Using a Reverse Proxy for the Frontend Module Summary Module Introduction Deployment Options & Steps AWS EKS vs AWS ECS Preparing the Starting Project Diving Into AWS Creating & Configuring the Kubernetes Cluster with EKS Adding Worker Nodes Applying Our Kubernetes Config Getting Started with Volumes Adding EFS as a Volume (with the CSI Volume Type) Creating a Persistent Volume for EFS Using the EFS Volume A Challenge! Challenge Solution You Learned A Lot! Related Topics You Could Explore Next Steps! Note: All Videos are latest and are UpToDate.

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Course Structure SQL Training (Sessions 1-12) Introduction to SQL Basics of SQL and its role in data analytics Understanding databases and tables DDL and DML Commands Creating, modifying, and managing database structures (DDL) Manipulating data with INSERT, UPDATE, DELETE (DML) Clauses in SQL Filtering data with WHERE, ORDER BY, and LIMIT clauses Inbuilt Functions Using built-in functions for data manipulation and analysis Group By and Having Grouping data and filtering groups using the HAVING clause Joins Combining data from multiple tables using INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN Self Joins Understanding self joins and their applications Subquery and CTE Using subqueries and Common Table Expressions (CTE) for complex queries Case When Conditional logic in SQL queries using the CASE WHEN statement Set Operators Combining query results with UNION, INTERSECT, and EXCEPT Window Functions Advanced data analysis with window functions Analytical Window Functions and Problem-Solving Sessions Deep dive into analytical window functions Real-world problem-solving sessions Performance Tuning Optimizing SQL queries for better performance Additional Features Assignments Regular assignments to reinforce learning and practice skills Interview Asked Questions Preparation for common interview questions related to SQL Scenario-Based Questions Training on real-world scenarios to enhance problem-solving skills On-Call Doubt Resolution Personalized support to resolve any doubts or questions on the go One-to-One Project for SQL Hands-on projects to apply your learning in practical situations Contact me at +919870896958 at Whatsapp for more Details about the Program. Starting Date and Time is decided by the Person who booked the Course Accordingly.

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