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Il y a 2 modules dans ce cours
Optimize LLM Costs & Streamline Processes is an intermediate course for machine learning practitioners and AI professionals looking to bridge the gap between technical execution and operational excellence. You will learn two critical, in-demand skills: cost optimization for Large Language Models (LLMs) and process streamlining for ML workflows. First, you will dive into the financial side of MLOps, learning to dissect compute-spend reports, pinpoint the models driving up costs, and propose concrete technical optimizations like INT8 quantization to make a measurable financial impact. Next, you will master the principles of lean management by applying Value-Stream Mapping (VSM) to complex ML pipelines. Through hands-on labs using tools like Miro and spreadsheets, you will learn to visualize workflows, identify hidden waste like manual bottlenecks and wait times, and design streamlined, automated future-state processes. By the end of this course, you will be equipped to not only build powerful models but also to deploy and manage them in a way that is cost-efficient, fast, and aligned with business goals.
In this module, you will learn to translate financial data from compute-spend reports into actionable technical strategies. You will dissect these reports to pinpoint high-cost models, explore optimization techniques like quantization, and learn to propose solutions that directly impact the bottom line.
Inclus
2 vidéos1 lecture2 devoirs
Afficher les informations sur le contenu du module
2 vidéos•Total 11 minutes
LLM Costs Spiral Out of Control•6 minutes
Propose Model Optimization with Quantization•5 minutes
1 lecture•Total 9 minutes
Dissecting Compute-Spend Report•9 minutes
2 devoirs•Total 25 minutes
Hands-On Learning (HOL): Analyzing a Compute-Spend Report for Optimization•15 minutes
Draft a Cost-Reduction Pitch•10 minutes
Streamlining ML Processes with Value-Stream Mapping
Module 2•1 heure à terminer
Détails du module
This module introduces lean management principles through Value-Stream Mapping (VSM). You will learn to visualize an end-to-end ML pipeline, systematically identify and classify waste, and design a streamlined future-state process that leverages automation to shorten cycle times and increase efficiency.
Inclus
2 vidéos1 lecture2 devoirs
Afficher les informations sur le contenu du module
2 vidéos•Total 9 minutes
Eliminating Hidden Waste: Boosting Your ML Team's Velocity•5 minutes
Create a Current and Future-State Value Stream Map (VSM) •5 minutes
1 lecture•Total 8 minutes
The Core Principles of Value-Stream Mapping •8 minutes
2 devoirs•Total 45 minutes
Project: Optimization and Redesign Proposal•20 minutes
Hands-On Learning (HOL): Mapping a Sample ML Release Pipeline•25 minutes
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