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After teaming up with OpenAI for the ‘ChatGPT Prompt Engineering for Developers’ course in May, Andrew Ng’s DeepLearning.AI has unveiled three new courses on generative AI. Besides Isa Fulford of OpenAI, LangChain’s cofounder and chief Harrison Chase and Lamini’s cofounder and chief Sharon Zhou are joining as instructors. The courses are free-of-charge for a limited period.
Building Systems with the ChatGPT API
“Building Systems with the ChatGPT API” is a concise course that teaches the automation of complex workflows using chain calls to a powerful language model. Led by Isa Fulford and Andrew Ng, this one-hour program covers topics such as creating interactive prompts, utilising Python code and developing a customer service chatbot. Practical applications include query classification, safety evaluation, and multi-step reasoning. The course provides hands-on examples and Jupyter notebooks for experimentation. In collaboration with OpenAI, this beginner-friendly course offers the latest best practices for maximizing the performance of LLM models responsibly. Suitable for those with basic Python knowledge and ML engineers seeking prompt engineering skills for LLMs.
How Diffusion Models Work
In this How Diffusion Models Work course, one will learn how to build and optimise diffusion models, gaining a deep understanding of their inner workings. Taught by Sharon Zhou (CEO, Co-founder, Lamini), the free-of-cost one-hour intermediate-level course equips you with practical coding skills and hands-on labs for creating personalised diffusion models. With a focus on generative AI, you’ll explore the diffusion process, build neural networks for noise prediction, and enhance image generation with contextual information. By the end of the course, you’ll have a solid foundation to explore diffusion models for your own applications. Prior knowledge of Python, Tensorflow, or Pytorch is recommended.
LangChain for LLM Application Development
LangChain for LLM Application Development is a beginner-friendly, short one-hour course instructed by Harrison Chase (Co-Founder and CEO at LangChain) and Andrew Ng and requires basic Python knowledge. The program will enable you to apply LLMs to your data, and build personalised assistants and chatbots. It will also explore agents, chained calls, and memories to enhance the utility of LLMs. The course provides comprehensive instruction and hands-on experience in crucial topics such as Models, Prompts, and Parsers. You will gain expertise in invoking LLMs, supplying prompts, and parsing responses. Additionally, you will explore memory implementation, chain construction, leveraging LLMs for Question Answering over Documents, and the frontier of LLMs as reasoning agents. By the end of the course, you will have a model to kickstart your independent exploration of diffusion models for your own applications. LangChain for LLM Application Development is beginner-friendly and requires basic Python knowledge.
LangChain is an important Python framework for large language models (LLMs) that has gained significant attention in the developer ecosystem over time as it simplifies the integration of LLMs into applications, making them more accessible. With support from multiple model providers and hosting platforms, LangChain has raised substantial funding and is valued at $200 million. It enables the creation of AI agents through command chaining and offers access to advanced LLMs from providers like Hugging Face. So if you want to up your game, enrol for this course now.
