AI for Data Scientists Training

This Introduction to Generative AI (GenAI) training is tailored for Machine Learning (ML) and Data Science professionals who want to gain a practical understanding of Generative AI and large language models (LLMs).

This Intermediate Generative AI (GenAI) course is for Machine Learning and Data Science professionals who want to learn advanced GenAI and LLM techniques like fine-tuning, domain adaptation, and evaluation. Participants learn how to leverage popular tools and frameworks, including Python, Hugging Face Transformers, and open-source LLMs.

This Comprehensive Generative AI (GenAI) course is for Machine Learning and Data Science professionals who want to dive deep into the world of GenAI and Large Language Models (LLMs). This course covers various topics, from the foundations of LLMs to advanced techniques like fine-tuning, domain adaptation, and evaluation. Participants gain hands-on experience with popular tools and frameworks, including Python, Hugging Face Transformers, and open-source LLMs.

This advanced Machine Learning (ML) course is designed for Data Science and ML professionals who want to master designing and implementing enterprise-grade ML applications. Attendees learn how to evaluate advanced LLM architectures and dive into advanced topics, such as fine-tuning and quantization techniques, LLM-powered recommender systems, model evaluation, and debugging, as well as ethical considerations and responsible AI practices for enterprise-grade LLMs.

This AI Computer Vision course gives attendees a deep understanding of computer vision concepts, techniques, and applications. The course covers everything from image processing fundamentals and feature extraction to advanced deep learning architectures and object detection. Participants gain hands-on experience implementing computer vision algorithms and building end-to-end applications using popular frameworks and libraries.

This Generative AI (GenAI) training teaches attendees the fundamentals of Deep Learning and GenAI, with participants building the skills to apply these powerful technologies to real-world scenarios. The course introduces attendees to key concepts, tools, and frameworks like TensorFlow and Keras, as well as neural network architectures like CNN, RNN, and Transformers. Students learn about large language models (LLMs), GANs, and diffusion models, and their applications in diverse domains.

In this AI Solutions course, participants learn how to fine-tune large language models (LLMs) like Chat-GPT to build custom AI solutions tailored to specific use cases and domains. This course covers fine-tuning fundamentals, including data preparation, model selection, and training best practices. Participants will also learn how to evaluate and optimize fine-tuned models for improved performance, fairness, and safety. 

This ChatGPT Advanced Data Analysis (ChatGPT ADA) course teaches attendees to leverage ChatGPT's advanced data analysis features to clean and preprocess data, generate insightful reports, create dynamic visualizations, and build predictive machine learning models. Students learn how to prepare, upload, and process a variety of data formats such as CSV, Excel, PDF, and multimedia files. Participants explore practical use cases across business analytics, social media insights, and scientific and market research.