Marketing Management: What Is It and Why Does It Matter?
January 22, 2025
Article
Instructors: Chris Fregly
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341,376 already enrolled
(3,136 reviews)
Recommended experience
Intermediate level
This is an intermediate course, so you should have some experience coding in Python to get the most out of it.
(3,136 reviews)
Recommended experience
Intermediate level
This is an intermediate course, so you should have some experience coding in Python to get the most out of it.
Gain foundational knowledge, practical skills, and a functional understanding of how generative AI works
Dive into the latest research on Gen AI to understand how companies are creating value with cutting-edge technology
Instruction from expert AWS AI practitioners who actively build and deploy AI in business use-cases today
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In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.
By taking this course, you'll learn to: - Deeply understand generative AI, describing the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection, to performance evaluation and deployment - Describe in detail the transformer architecture that powers LLMs, how they’re trained, and how fine-tuning enables LLMs to be adapted to a variety of specific use cases - Use empirical scaling laws to optimize the model's objective function across dataset size, compute budget, and inference requirements - Apply state-of-the art training, tuning, inference, tools, and deployment methods to maximize the performance of models within the specific constraints of your project - Discuss the challenges and opportunities that generative AI creates for businesses after hearing stories from industry researchers and practitioners Developers who have a good foundational understanding of how LLMs work, as well the best practices behind training and deploying them, will be able to make good decisions for their companies and more quickly build working prototypes. This course will support learners in building practical intuition about how to best utilize this exciting new technology. This is an intermediate course, so you should have some experience coding in Python to get the most out of it. You should also be familiar with the basics of machine learning, such as supervised and unsupervised learning, loss functions, and splitting data into training, validation, and test sets. If you have taken the Machine Learning Specialization or Deep Learning Specialization from DeepLearning.AI, you’ll be ready to take this course and dive deeper into the fundamentals of generative AI.
Generative AI use cases, project lifecycle, and model pre-training
17 videos7 readings1 assignment2 app items
Fine-tuning and evaluating large language models
10 videos3 readings1 assignment1 app item
Reinforcement learning and LLM-powered applications
21 videos7 readings1 assignment1 app item
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
DeepLearning.AI is an education technology company that develops a global community of AI talent. DeepLearning.AI's expert-led educational experiences provide AI practitioners and non-technical professionals with the necessary tools to go all the way from foundational basics to advanced application, empowering them to build an AI-powered future.
Since 2006, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 90 fully featured services for compute, storage, networking, database, analytics, application services, deployment, management, developer, mobile, Internet of Things (IoT), Artificial Intelligence, security, hybrid and enterprise applications, from 44 Availability Zones across 16 geographic regions. AWS services are trusted by millions of active customers around the world — including the fastest-growing startups, largest enterprises, and leading government agencies — to power their infrastructure, make them more agile, and lower costs. Coursera and AWS have been partners since 2017 providing learners and enterprises globally, the skills they need to succeed. Coursera builds on AWS servers to scale with student demand with confidence around capacity and elasticity and in partnership with AWS. In 2019, Coursera achieved Advanced Tier Partner status and further extended the partnership with AWS Educate, AWS EdStart and AWS Academy collaborations. Coursera's been able to make cloud skills more accessible with 8 AWS courses on the Coursera platform featuring top subject matter experts and the portfolio continues to grow. To learn more about AWS, visit https://aws.amazon.com.
University of Michigan
Course
Specialization
Google Cloud
Course
3,136 reviews
82.46%
14.35%
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Reviewed on Jan 28, 2024
Easily a five star course. You will get a combination of overview of advanced topics and in depth explanation of all necessary concepts. One of the best in this domain. Good work.
Thank you teachers!
Reviewed on Oct 12, 2024
Pretty good overview for Product Managers and leaders who are interested in learning about Generative AI with hands-on labs that are not too detailed, yet help you develop the intuition.
Reviewed on Nov 29, 2023
I really like the lab walk through here. It helps me so much on understand the code, especially good for someone new like me that doesn't have intro knowledge of all those LLM libraries.
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Developers who have a good foundational understanding of how LLMs work, as well the best practices behind training and deploying them, will be able to make good decisions for their companies and more quickly build working prototypes. This course will support learners in building practical intuition about how to best utilize this exciting new technology.
We recommend starting with a beginner course such as Machine Learning Specialization.
Yes! This course is perfect for anyone with a background in Python ready to dive deeper into large language models and generative AI.
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