TextEncoders

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

STARTS SOON ON TUESDAY, Jan 27, 2026!

  An eagerly awaited twelve-week course on fine-tuning large language models—with an emphasis on supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and production-grade MLOps. The last two weeks are reserved for capstone work and presentations. The course assumes familiarity with deep learning, basic transformer architectures, and Python. It does not assume prior experience with reinforcement learning. You will work in teams of 4-6 engineers in an environment that closely reproduces the innovation and development that is the quintessence of the Silicon Valley spirit. Each team will get a meeting room with a state-of-the-art multimedia setup and a powerful AI server with RTX4090 for exclusive use during the boot camp. These will also be accessible remotely so that the teams can continue to work on them during the workdays. You will also have unrestricted access to a massive 4-GPU AI server at the admin-privilege level for the three-month duration for this course on a time-shared basis.

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 SOON ON SATURDAY, Jan 31, 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 closely reproduces the innovation and development that is the quintessence of the Silicon Valley spirit. Each team will get a meeting room with a state-of-the-art multimedia setup and a powerful AI server with RTX4090 for exclusive use during the boot camp. These will also be accessible remotely so that the teams can continue to work on them during the workdays. You will also have unrestricted access to a massive 4-GPU AI server at the admin-privilege level for the sixteen week duration of this boot camp on a time-shared basis. Besides this, you will also benefit from the 10-gigabit networking and the large server cluster to take your projects to actual production. SupportVectors will let you use the compute resources for an additional four weeks if you need to finish any remaining aspects of your projects.