Specialization

(If you are paying by Check or Zelle upfront, then you get the discounted rate of $3600)

STARTS SOON ON SATURDAY, June 6, 2026!

  This is the eagerly awaited hackathon-style, coding-centered BootCamp centered around real-world, exciting projects. The goal is to make you profoundly confident and fluent in applying LLMs to solve an extensive range of real-world problems in vector embeddings, semantic AI search, retrieval-augment generation, multi-modal learning, video comprehension, adversarial attacks, computer vision, audio-processing, natural language processing, tabular data, anomaly and fraud detection, healthcare applications, and clever techniques of prompt engineering. You will work in teams of 4–6 engineers in an environment that reflects the innovation-driven spirit of Silicon Valley. Participants will have access to a state-of-the-art AI training datacenter featuring 20+ GPU servers and 40+ NVIDIA GPUs, including RTX PRO 6000 Blackwell, RTX 5090, and RTX 4090 systems. SupportVectors will let you use the compute resources for an additional four weeks if you need to finish any remaining aspects of your projects.

STARTS SOON — DATE TBD!

  Elevate your fine-tuning expertise with our immersive hands-on course designed for AI practitioners. Begin with the foundational concepts of transfer learning and pre-trained models, then dive into fine-tuning methodologies for transformers and other state-of-the-art architectures. Explore open-source libraries such as Hugging Face, LoRA, and PEFT for scalable and efficient fine-tuning. Master techniques like prompt tuning, adapter tuning, and hyperparameter optimization to tailor models for domain-specific tasks. Learn strategies for low-resource fine-tuning, including few-shot and zero-shot learning, and address overfitting with advanced regularization methods. Discover fine-tuning approaches for diverse modalities, including text, images, and multimodal data, while exploring domain-adaptation strategies for out-of-distribution datasets. Implement advanced training strategies like quantization-aware training, curriculum learning, and differential privacy. By the end of the course, you’ll have the practical knowledge to fine-tune models for real-world applications, ensuring optimal performance and efficiency tailored to your unique datasets.

(If you are paying by Check or Zelle upfront, then you get the discounted rate of $3200)

STARTS TBD

  This course is designed to introduce students to the foundational and advanced concepts of artificial intelligence, with a focus on neural networks, large language models, and generative AI. Through a combination of lectures, hands-on coding exercises and project work, students will gain a deep understanding of the mathematical and technical underpinnings of AI technologies. They will explore the theory behind neural networks, delve into various architectures, and understand the applications and implications of AI in the real world.