Vijit's Project Management Portal

Introduction Think of Artificial Intelligence (AI) as a quick and flexible digital team member that can read, write, summarize, plan, and brainstorm with you. It’s not magic; it’s software that learns patterns from large amounts of data and can generate helpful answers, drafts, and ideas when you need them. The “ Build Your Own AI in 30 Days ” playlist is meant to take you from “I’m curious, but this seems too technical” to “I can confidently use AI for my work and projects” through small daily steps. You don’t need to write code, know algorithms, or become a data expert; you just need to understand what AI can do, how to communicate with it, and how to integrate it into your daily tasks. Days 1–5: What Is AI and Where Does It Fit in Your Work? The first few videos answer a simple question: what is AI and where are you already using it, often without realizing? It provides everyday examples like email auto-complete, spam filters, recommendation systems, and language tools...

  Customer support is often treated as a cost center. A  department that reacts to problems and measures success one ticket at a time. But the highest-performing support organizations operate like a well-engineered project: with defined goals, structured workflows, measurable milestones, and a relentless focus on continuous improvement. The integration of project management (PM) disciplines into customer support is not a theoretical exercise. It is a proven strategy that leading companies from Zendesk to Freshworks, from HubSpot to Salesforce have used to radically improve First Response Time (FRT), Customer Satisfaction (CSAT), Net Promoter Score (NPS), and ticket resolution efficiency. This article explores how PM principles map to customer support operations, backed by real-world examples and measurable outcomes. 1. The Problem: Support Teams Without a Project Management Backbone Most support teams run on instinct and firefighting. Agents triage tickets informally, ma...

    Learning Python can transform project managers from coordinators into strategic, data-savvy leaders. It brings automation, analytics, and integration capabilities directly into day-to-day project work, reducing manual effort and improving decision quality. Project management revolves around information: schedules, budgets, risks, resources, and stakeholder updates. Python is a general-purpose language with rich libraries that handle exactly these kinds of data tasks: retrieving, processing, analyzing, and synthesizing information from multiple sources. Because Python’s syntax is readable and high level, it is accessible even to professionals without a formal programming background. Research on project managers who learn programming shows that while there is an initial learning effort, the same code can be reused across projects, leading to long-term time savings. As data volumes grow and tools diversify, Python becomes a flexible “glue” that connects spreadsheets, database...