AI and ML

This online instructor led training course provides the knowledge to better understand Aritificial Intelligence, AI. In this course students will learn key topics including how AI currently works, what the current limitations are, what are the trends, what languages are being utilized, what major players are currently leading the way, how math is utilized in AI, and more.

This online instructor led training course provides the knowledge to better understand deep learning algorithms. In this course students will learn key topics including how neural networks work, the different type of neural networks, how an auto encoder works, and more.

The OpenAI Playground is the next step beyond ChatGPT, and where you’ll go when working with integrating the LLMs into your platforms and crafting more sophisticated prompts. Through the playground you have control over which LLM you can use, the temperature, tokens. It can also facilitate the development of applications with examples of code from your prompts. This is a crash course in getting started in using the OpenAI playground.

AutoGPT is a new project that leverages the GPT4 (and GPT3) models from OpenAI to build an autonomous AI agent. Answer a few questions to send AutoGPT on its way to complete astounding projects that aren’t feasible within the confines of ChatGPT. This course offers a complete walkthrough to prepare Python IDE to run AutoGPT. It is intended to be used by non-coders who have an interest in working with AutoGPT. The IDE demonstrated is PyCharm, a popular development environment for Python.

Chatbots are a powerful application of the LLMs available from OpenAI. In this course we will see how to build your own chatbot leveraging OpenAI’s LLMs.

LangChain is a new project that is capable of extending the capability of OpenAI’s LLM, providing a means of stringing together complex behavior and outside systems. This course teaches how to make use of LangChain with OpenAI’s LLMs.

Incorporating the power of OpenAI’s offering so you can build capabilities of ChatGPT into your platform demands working with the OpenAI API. This course explores the process of building an application in Python using the OpenAI API.

Use of embeddings with a LLM allows you to feed your own information. If you need to load a large amount of information into the OpenAI system, use of embeddings it the established means of doing that. This course teaches how to work with the embeddings system.

Finetuning allows you to expose a LLM to new patterns. This course teaches how to use finetuning with the Davinci models from OpenAI.

The large language models (LLMs) from OpenAI have tremendous capability when it comes to processing and categorizing text. Need to sort through countless emails or comments and assign them to a category (i.e. high priority, positive/negative). The OpenAI API offers a powerful means of wrangling a complex task like text categorization or summarization. This course will explore how to design a prompt and leverage that in the API to distill something down to a few words.

ChatGPT is capable of preparing many components of a typical website, including HTML and CSS. This course explores the use of ChatGPT for web development as well as the caveats for its use.

Developers have found tremendous efficiencies using ChatGPT to accelerate their development in both Front-End and Back-End development languages. This course shows considerations for using ChatGPT to streamline your front-end development using ChatGPT.