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| // Version: v5 | |
| const msftCourseTopics = [ | |
| { category: "MSFT - Leveraging Generative AI for Business Applications", topics: [ | |
| { name: "MSFT - W1 - Navigating the GenAI & Agentic Landscape", amount: 6000 }, | |
| { name: "MSFT - W2 - Driving Business Value with Effective Prompting", amount: 6000 }, | |
| { name: "MSFT - W3 - Python for Prompt Engineering [Code Track]", amount: 6000 }, | |
| { name: "MSFT - W4 - Leveraging LLMs for Business Intelligence & Automation", amount: 6000 }, | |
| { name: "MSFT - W5 - Project 1 - Financial News Reporting System (Code)", amount: 6000 } | |
| ]}, | |
| { category: "MSFT - Building Intelligent Systems with RAG & Agents", topics: [ | |
| { name: "MSFT - W7 - Enhancing AI solutions with Retrieval Augmented Generation (Code Track)", amount: 6000 }, | |
| { name: "MSFT - W8 - Advanced RAG for Business Applications & Performance Evaluation (Code Track)", amount: 6000 }, | |
| { name: "MSFT - W9 - Deploying a Generative AI-powered App (Code Track)", amount: 6000 }, | |
| { name: "MSFT - W10 - Automating Tasks with Agentic Systems (Code Track)", amount: 6000 }, | |
| { name: "MSFT - W11 - Project 2 - Market Competitor Intelligence System (Code Track)", amount: 6000 } | |
| ]}, | |
| { category: "MSFT - Operational Excellence with LLMOps", topics: [ | |
| { name: "MSFT - W13 - Foundations of LLMOps (Code Track)", amount: 6000 } | |
| ]} | |
| ]; | |