Advanced RAG with Multi-Media RAG

Advanced AI-Evals & Monitoring

Intro RL & RLHF

RL & RLHF Framework

How RAG Finetuning and RLHF Fits in Production

In this bootcamp, we go beyond prompt engineering to give you the skills to design, build, and optimize advanced AI systems that can adapt and improve over time. You will learn to think like a systems engineer, mastering the underlying mechanics of modern models and the techniques that make them perform in real-world, high-stakes environments.

Over several intensive weeks, we combine: 

Deep technical instruction with hands-on coding projects to bridge the gap between theory and deployment. You’ll work directly with production-grade frameworks, simulate complex reasoning behaviors, and build AI pipelines that integrate multiple data types and modalities. Every concept is reinforced through practical exercises, live feedback, and real-world project reviews, ensuring that by the end, you can not only understand advanced AI architectures but also architect, deploy, and refine them for evolving enterprise needs. This program includes in-depth instruction, dedicated mentorship, and exclusive access to tools, templates, and a collaborative community to support your continued growth.

Your expert guides through this bootcamp are:

[Dr. Dipen Bhuva](https://www.linkedin.com/in/dipen-bhuva-21a296158/): Dr. Dipen is an AI/ML researcher with 150+ citations and 16 published research papers. He has 3 tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In his research journey, he has collaborated with NASA-Glenn Centre, Cleveland Clinic, and the US department of energy for his research papers. He was an official reviewer and has reviewed 100+ research papers from Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. He has a PhD from Cleveland State University with a focus on LLMs in cybersecurity. He also has a master's in informatics at Northeastern University.

[Zao Yang](https://www.linkedin.com/in/zaoyang/): Zao is the owner of Newline, a platform used by 150k professionals from companies like Salesforce, Adobe, Disney, and Amazon. Zao has a rich history in the tech industry, co-creating Farmville (200 million users, $3B revenue) and Kaspa ($3B market cap). Self-taught in deep learning, generative AI, and machine learning, Zao is passionate about empowering others to develop practical AI applications. His extensive knowledge of both the technical and business sides of AI projects will be invaluable as you work on your own.

With Dipen and Zao's guidance, you’ll gain practical insights into building and deploying advanced AI models, preparing you for the most challenging and rewarding roles in the AI field.

AI engineering in the enterprise

This advanced AI Bootcamp teaches you to design, debug, and optimize full-stack AI systems that adapt over time. You will master byte-level models, advanced decoding, and RAG architectures that integrate text, images, tables, and structured data. You will learn multi-vector indexing, late interaction, and reinforcement learning techniques like DPO, PPO, and verifier-guided feedback. Through 50+ hands-on labs using Hugging Face, DSPy, LangChain, and OpenPipe, you will graduate able to architect, deploy, and evolve enterprise-grade AI pipelines with precision and scalability.

AI bootcamp 2

Ability to architect and deploy advanced AI systems for enterprise and consulting, worth $100k in annual value ($1M over 10 years)

Skills in advanced RAG, RLHF, and RL-based fine-tuning that are rare and in high demand at top AI companies

Capability to build multimodal, feedback-driven AI pipelines that outperform vanilla retrieval and generation systems

Technical mastery to lead or consult on AI platform engineering, unlocking six-figure consulting opportunities

Portfolio of 50+ hands-on labs and multiple enterprise-grade AI projects to showcase to employers or clients

Direct code reviews, debugging help, and system design feedback from expert instructors

Future-proof understanding of AI system architecture, enabling you to adapt to new models and frameworks as they emerge

A competitive advantage in the AI job market, with potential to increase earnings by $50k+ annually

What You Will Gain

Master byte-level language models and advanced decoding strategies like top-k, nucleus, and speculative decoding

Design and optimize advanced Retrieval-Augmented Generation (RAG) pipelines that integrate text, images, tables, and structured data

Implement multi-vector indexing, late interaction methods, and metadata-aware query routing

Fine-tune retrievers and rerankers using contrastive loss, triplet loss, and hard-negative mining

Simulate and enhance reasoning in non-CoT models using feedback loops and model control patterns

Develop tool-using agents with multi-hop planning, disambiguation flows, and function-calling capabilities

Build feedback-driven evaluation pipelines using persona-based synthetic queries, regex/schema validators, and topic clustering

Learn and apply reinforcement learning techniques including DPO, PPO, GPRO, RLVR, and verifier-guided optimization

Integrate open-source frameworks like Hugging Face, DSPy, LangChain, OpenPipe, and Braintrust into production-grade systems

Deploy enterprise-ready AI systems with robust evaluation, monitoring, and continuous improvement loops

Architect modular, future-proof AI pipelines that can evolve with new models, tools, and retrieval methods

Learn

The newline Guide to Building Your First GraphQL Server with Node and TypeScript

Teach

Amelia Wattenberger

Author of Fullstack D3

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