Optimize LLM Costs & Streamline Processes

Overview

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.

Syllabus

Analyzing and Optimizing LLM Costs

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.

Streamlining ML Processes with Value-Stream Mapping

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.