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Tim Warner

OpenAI publishes several large language models (LLMs), each optimized for different use cases. This course teaches you how to select the right model to balance performance, accuracy, and cost.

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OpenAI publishes several large language models (LLMs), each optimized for different use cases. This course teaches you how to select the right model to balance performance, accuracy, and cost.

OpenAI offers customers access to their world-leading large language models and APIs via a straightforward REST interface. The developer's challenge lies in choosing the right model for the right use case. In this course, OpenAI Model Selection and Integrations, you’ll gain deep familiarity with the OpenAI model family and which to choose, when. First, you’ll differentiate the models themselves. Next, you’ll discover how to balance performance, accuracy, and cost. Finally, you’ll understand how context windows work and how to optimize your applications for the least cost and maximum effectiveness. When you’re finished with this course, you’ll have the skills and knowledge of the OpenAI models needed to provide generative AI power to your line-of-business solutions in a performant and cost-effective manner.

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What's inside

Syllabus

Course Overview
Choosing the Best OpenAI Model
Managing the Context Window

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by Tim Warner, who are recognized for their work in OpenAI
Examines OpenAI large language models, which are highly relevant to generative AI

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in OpenAI Model Selection and Integrations with these activities:
Review Context Window
Understand the concept of context windows to prepare for this course's content.
Show steps
  • Read a blog post or article about context windows.
  • Try out an online demonstration or tutorial on context windows.
  • Experiment with different context window sizes in your own code.
Show all one activities

Career center

Learners who complete OpenAI Model Selection and Integrations will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers use their expertise to create and implement machine learning solutions that drive business value. This course provides a foundation in the key concepts and techniques used in machine learning, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Machine Learning Engineer by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your applications for performance and cost-effectiveness.
AI Engineer
AI Engineers design, develop, and deploy AI systems. This course provides a foundation in the key concepts and techniques used in AI engineering, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as an AI Engineer by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your applications for performance and cost-effectiveness.
Data Scientist
Data Scientists use their skills in statistics, programming, and machine learning to extract insights from data. This course provides a foundation in the key concepts and techniques used in data science, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Data Scientist by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your applications for performance and cost-effectiveness.
Statistician
Statisticians use their skills in mathematics, statistics, and programming to analyze data and draw conclusions. This course provides a foundation in the key concepts and techniques used in statistics, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Statistician by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your analysis for performance and cost-effectiveness.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides a foundation in the key concepts and techniques used in software engineering, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Software Engineer by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your applications for performance and cost-effectiveness.
Data Analyst
Data Analysts use their skills in statistics, programming, and machine learning to analyze data and extract insights. This course provides a foundation in the key concepts and techniques used in data analysis, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Data Analyst by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your analysis for performance and cost-effectiveness.
Financial Analyst
Financial Analysts use their skills in mathematics, statistics, and programming to analyze financial data and make investment decisions. This course provides a foundation in the key concepts and techniques used in financial analysis, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Financial Analyst by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your analysis for performance and cost-effectiveness.
Product Manager
Product Managers are responsible for the development and launch of new products. This course provides a foundation in the key concepts and techniques used in product management, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Product Manager by providing you with the knowledge and expertise to select the right OpenAI model for your product and optimize your product for performance and cost-effectiveness.
Quantitative Analyst
Quantitative Analysts use their skills in mathematics, statistics, and programming to analyze financial data and make investment decisions. This course provides a foundation in the key concepts and techniques used in quantitative analysis, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Quantitative Analyst by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your analysis for performance and cost-effectiveness.
Actuary
Actuaries use their skills in mathematics, statistics, and programming to assess risk and make financial decisions. This course provides a foundation in the key concepts and techniques used in actuarial science, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as an Actuary by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your analysis for performance and cost-effectiveness.
Risk Manager
Risk Managers use their skills in mathematics, statistics, and programming to assess risk and make decisions. This course provides a foundation in the key concepts and techniques used in risk management, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Risk Manager by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your analysis for performance and cost-effectiveness.
Market Researcher
Market Researchers use their skills in data analysis and problem-solving to help businesses understand their markets. This course provides a foundation in the key concepts and techniques used in market research, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Market Researcher by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your research for performance and cost-effectiveness.
Econometrician
Econometricians use their skills in mathematics, statistics, and programming to analyze economic data and draw conclusions. This course provides a foundation in the key concepts and techniques used in econometrics, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as an Econometrician by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your analysis for performance and cost-effectiveness.
Business Analyst
Business Analysts use their skills in data analysis and problem-solving to help businesses make better decisions. This course provides a foundation in the key concepts and techniques used in business analysis, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as a Business Analyst by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your analysis for performance and cost-effectiveness.
Operations Research Analyst
Operations Research Analysts use their skills in mathematics, statistics, and programming to solve complex business problems. This course provides a foundation in the key concepts and techniques used in operations research, including model selection, context window management, and performance optimization. This course can help you build the skills needed to succeed as an Operations Research Analyst by providing you with the knowledge and expertise to select the right OpenAI model for your use case and optimize your analysis for performance and cost-effectiveness.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in OpenAI Model Selection and Integrations.
Provides a practical introduction to deep learning, covering the basics of neural networks, convolutional neural networks, and recurrent neural networks. It also includes a chapter on natural language processing, which is relevant to OpenAI's large language models.
Provides a comprehensive overview of speech and language processing, covering the basics of phonetics, phonology, morphology, syntax, semantics, and pragmatics. It also includes a chapter on natural language processing, which is relevant to OpenAI's large language models.
Provides a comprehensive overview of natural language processing with Python, covering the basics of natural language processing, as well as how to use Python for a variety of natural language processing tasks.
Provides a comprehensive overview of deep learning for natural language processing, covering the basics of deep learning, as well as how to train and use it for a variety of natural language processing tasks.
Provides a hands-on introduction to natural language processing, covering the basics of natural language processing, machine learning, and deep learning. It also includes a chapter on OpenAI's models.
Provides a comprehensive overview of machine learning with tree-based models, covering the basics of tree-based models, as well as how to train and use them for a variety of machine learning tasks. It also includes a chapter on natural language processing.
Provides a practical introduction to text mining with R, covering the basics of text mining, as well as how to use R for a variety of text mining tasks. It also includes a chapter on natural language processing.

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