Generative AI

An introductory course designed to provide an overview and understanding of AI concepts such as Machine Learning, Deep Learning, GPT models, and AGI. The course content includes AI concepts, core services, security, architecture, and support.

For those at intermediate-level, this course is designed to enable learners to upskill their technical expertise in development using AI technologies and Auto-GPT. In addition, LangChain and its integration with AI technologies is also covered.

Delving into more advanced topics with latest research, such as fine-tuning GPT and AUTO-GPT models, this course aims to provide an understanding of transformer architecture and how to use LangChain and Pandas to undertake complex tasks.

An introduction to LangChain, this course empowers learners at all levels to navigate the intricacies of LangChain components. Learners will be guided through building powerful, personalized applications such as chatbots, personal assistants and document querying tools.

Using GPT and AUTO-GPT models, this course brings learners through the best approaches for effective prompt design. From how to tailor prompts through to the achieving the desired outcome and mitigation for model biases.

This practical course empowers learners to use raw data to extract actionable insights while using new technologies including anomaly and outlier detection, predictive analytics, deep learning and neural networks. It also covers interpreting and communicating results of data analysis. From beginners through to expert level analysts, this course is a valuable investment at all levels to keep at pace with the new technologies that are taking data analysis to new levels.

Using AI, AGI Models, AUTO-GPT Outputs, and Vector Database Outputs, this course empowers learners to understand AI language, harness it to its full potential, and take AI insights into real-world, practical solutions.

Take expertise to the next level with Large Language Models (LLMs). Learners will master the intricacies of training and fine-tuning these powerful tools while harnessing their full potential for data analysis tasks.

Learn how to analyse AI-driven text using Natural Language Processing (NLP), using GPT, AUTO-GPT, and Pandas. This practical course brings learners through how to perform tasks such as text classification, sentiment analysis, and named entity recognition.

With a focus on how AI and AGI technologies can be integrated into DevOps practices, learners will uncover how AI can be used for code review, automated testing and predictive system maintenance.

In this course learners will discover how to utilize AI, AGI Models, AUTO-GPT Outputs, and Vector Database Outputs for practical purposes.

This course covers how to deploy and scale AI models, including GPT, AUTO-GPT, LLMs. It also includes managing vector databases in a production environment.