aishwaryanr
b939582394
* Restructure navigation into journeys and topics; backfill research and refresh courses - Add Use/Build/Understand journey pages and topic pages with a 101/201/301 catalog, surfaced through a Journey x Level grid in the README - Redistribute the free-course and notebook lists into the new navigation; add 2025-2026 courses and remove paid or dead entries - Backfill monthly best-papers lists from March 2025 through June 2026 - Extend the RAG, AI evaluation, and agentic search research tables to mid-2026 - Archive the 2024 course and paper material with banners - Fix the citation block and drop stale calls to action * Add all-free-courses-by-topic index; use numerals for numbers - Add courses.md: every free course grouped by topic, linked from the README router and the browse-by-topic section - Write counts as numerals across the navigation (10 not ten, 3-day not three-day) * Redesign the LLM foundations, agents, and RAG roadmaps for 2026 - Foundations roadmap: reorder so agents and evaluation are core days and fine-tuning becomes an optional advanced day; refresh all resources - Agents roadmap: rebuild around the model-plus-harness mental model, tools, context and memory, MCP and multi-agent, and agent evaluation - RAG roadmap: retrieval foundations, building a RAG app, agentic and advanced RAG - Point to current LevelUp materials and verified 2025-2026 resources * Refresh Agents 101 for 2026 and apply LevelUp Labs branding - Rewrite the Agents 101 guide around the model-plus-harness model, MCP, reasoning models, real-world agents (coding/computer-use/deep-research), and modern agent evaluation; drop the BabyAGI-era example and stale benchmarks - Rebrand references to LevelUp Labs and link the team to levelup-labs.ai * Archive the 2024 multimodal guide with a pointer to current material * Point each topic page to the canonical course list in courses.md * Add Harness Engineering path and enrich fine-tuning material - New Harness Engineering path: agent = model + harness, from using Claude Code, Cursor, and Codex to assembling and evaluating your own harness; wired into the Build journey's named paths - Fine-tuning topic: add current 2025-2026 material (post-training courses, the RLHF book, Hugging Face TRL and the LLM course chapter, Unsloth, Axolotl, and a practical 2025 fine-tuning guide) * Add role-based interview prep guide - New Role-Based Interview Prep: maps AI/LLM Engineer, ML/Fine-tuning Engineer, Applied Scientist, AI Product Manager, and Solutions Architect roles to what each interview tests and the repo material to prepare with; anchored on the 60 questions - Linked from the Interview Prep path and the README * Add branded roadmap headers and a real role-based interview question bank - Add LevelUp Labs branded headers for the LLM foundations and AI agents roadmaps (white background, blue, credited), wired into the guides - Rewrite role-based interview prep as an actual question bank with answers for AI/LLM Engineer, ML/Fine-tuning Engineer, Applied Scientist, PM, and Solutions Architect, rather than a navigation index * Add branded 3-Day RAG Roadmap header * Update RAG roadmap header with the branded 3-Day RAG image * Add deep role-based interview prep hub (AI Engineer, AI PM, FDE, AI Strategist) - Full folder per role: overview, interview rounds, a large answered question bank (210 questions across roles), verified free resources and courses, and a prep plan - Grounded in 2025-2026 research on how each role is actually interviewed at named companies; external links verified, cross-links to repo content - Replace the earlier shallow role summary with the hub and per-role folders
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Topic: Multimodal
📚 Full course list: the complete, always-current set of free courses on this topic lives in All free courses: Multimodal. The entries below are organized by journey and level.
Models that work across text, images, audio, and video: diffusion models, vision-language models, and multimodal application patterns. A thin subject in the repo today, covered mainly by external courses plus a 2024 guide.
Tags: Format 📖 Read / 🎥 Video / 🛠️ Notebook / 📝 Practice · Source ⭐ LevelUp Labs original / 🌐 External · year.
🏗️ Build 101
- Multimodal LLMs Guide ⭐ 📖 (2024) 🔴 stale: an introduction to multimodal models (pre native-multimodal-model era).
- How Diffusion Models Work 🌐 🎥 by DeepLearning.AI
- How to Use Midjourney, AI Art and ChatGPT to Create an Amazing Website 🌐 🎥 by Brad Hussey
🏗️ Build 201
- 11-777: Multimodal Machine Learning 🌐 🎥 by Carnegie Mellon University
- Prompt Engineering for Vision Models 🌐 🎥 by DeepLearning.AI
Related topics: Foundations · Prompting. Journeys: Build. Back to the repository index.