# Need Help to get hands on Vizuara AI Courses **URL:** \ **Category:** Discussion & Solutions\ **Tags:** help\ **Created:** [August 11, 2026, 7:50pm UTC](https://onehack.st/t/need-help-to-get-hands-on-vizuara-ai-courses/324697 "2026-08-11T19:50:10Z")\ **Posts on this page:** 3\ **Page:** 1
**Author:** ![reaper](https://onehack.st/letter_avatar_proxy/v4/letter/r/f04885/32.png) [@reaper](https://onehack.st/u/reaper)\ **Post date:** [August 11, 2026, 7:50pm UTC](https://onehack.st/t/need-help-to-get-hands-on-vizuara-ai-courses/324697/1 "2026-08-11T19:50:10Z")
**Anyone in the 1Hack community have access to the Vizuara courses?** If you’ve taken or have the course materials, could you please share the resources with me? A **Google Drive, Mega, or other legitimate download link** would be appreciated. Thanks! ---
**Author:** ![reaper](https://onehack.st/letter_avatar_proxy/v4/letter/r/f04885/32.png) [@reaper](https://onehack.st/u/reaper)\ **Post date:** [August 12, 2026, 2:44pm UTC](https://onehack.st/t/need-help-to-get-hands-on-vizuara-ai-courses/324697/2 "2026-08-12T14:44:21Z")
Here is the link of courses : [https://courses.vizuara.ai/](https://courses.vizuara.ai/) ---
**Author:** ![SRZ](https://onehack.st/user_avatar/onehack.st/srz/32/146132_2.png) [@SRZ](https://onehack.st/u/SRZ)\ **Post date:** [August 14, 2026, 7:39pm UTC](https://onehack.st/t/need-help-to-get-hands-on-vizuara-ai-courses/324697/3 "2026-08-14T19:39:27Z")
![Build it yourself, free β€” open notebooks over a pirated course](https://onehack.st/uploads/default/original/3X/9/8/9890b5b96836df2420f1823d02c2bbeda11fa4d6.jpeg) ### πŸ“š Vizuara gives a lot away free β€” and the same build (LLM Β· RAG Β· agents Β· multimodal) is in free hands-on repos, no piracy needed A pirated course dump is the slowest way to learn this, and you don’t need one. **Vizuara itself puts a big chunk on GitHub and YouTube for free** , and the exact skills the paid track sells β€” building LLMs, RAG, agents and multimodal systems _from scratch_ β€” are covered by dozens of free, hands-on 2026 course repos, many of them deeper than a paid course. If you grab three: - 🧩 **[DeepSeek From Scratch](https://github.com/VizuaraAILabs/DeepSeek-From-Scratch)** β€” Vizuara’s _own_ chapter-by-chapter notebooks + videos, free. - πŸŽ“ **[Claude Certified Architect Prep](https://pods.vizuara.ai/courses/claude-certified-architect)** β€” a genuinely **free** full Vizuara course: 6 pods, 22 notebooks, a practice exam. - πŸ“¦ **[Zero to AI](https://github.com/PavanMudigonda/zero-to-ai/archive/refs/heads/main.zip)** β€” one 950-notebook archive (Python β†’ LLMs β†’ RAG β†’ agents β†’ MLOps) to study offline. > **🧩 Vizuara's OWN free stuff β€” the direct answer to your ask** > > You can get most of what you’re after straight from the source, no warez mirror: > > - **[VizuaraAILabs on GitHub](https://github.com/VizuaraAILabs)** β€” the official org; runnable code behind their public projects. > - **[DeepSeek From Scratch](https://github.com/VizuaraAILabs/DeepSeek-From-Scratch)** Β· **[nano-gpt-oss](https://github.com/VizuaraAILabs/nano-gpt-oss)** Β· **[truly-open-gpt-oss](https://github.com/VizuaraAILabs/truly-open-gpt-oss)** β€” build DeepSeek / GPT-OSS-style models from first principles. > - **[Agents 10-Day Bootcamp](https://github.com/VizuaraAILabs/Vizuara-Agents-10Day-Bootcamp)** β€” the code + industrial projects from their agents bootcamp. > - **[Modern Robot Learning](https://github.com/VizuaraAILabs/Modern-Robot-Learning)** Β· **[Transformers for Vision (book code)](https://github.com/VizuaraAI/Transformers-for-vision-BOOK)** β€” robotics + vision tracks. > - **[Computer Vision from Scratch (YouTube)](https://www.youtube.com/playlist?list=PLPTV0NXA_ZSgmWYoSpY_2EJzPJjkke4Az)** Β· **[Vizuara channel](https://www.youtube.com/@vizuara)** Β· **[AI Playground](https://vizuara-ai-learning-lab.vercel.app/)** β€” free lectures + interactive practice. ```auto ``` > **πŸ—οΈ Build an LLM from scratch β€” the skill the course is really selling** > > - **[rasbt/LLMs-from-scratch](https://github.com/rasbt/LLMs-from-scratch)** β€” the cleanest baseline: tokenizer β†’ attention β†’ GPT β†’ pretrain β†’ LoRA. Start here. > - **[llm-lab](https://github.com/AntonioGr7/llm-lab)** β€” 2026 from-scratch: data, pretraining, post-training, GRPO, FP8, eval, in runnable notebooks. > - **[Text-LLM-Training-from-scratch](https://github.com/Y0oshi/Text-LLM-Training-from-scratch)** β€” pure PyTorch: SFT, reward modeling, DPO, GRPO, RLVR, no high-level frameworks. > - **[Modern LLM Notebook](https://github.com/walkinglabs/modern-llm-notebook)** β€” compact: tokenizers, attention, MoE, RLHF, inference, distillation. > - **[Hands-On Large Language Models](https://github.com/HandsOnLLM/Hands-On-Large-Language-Models)** β€” Colab-ready companion notebooks. ```auto ``` > **πŸ”Ž RAG, done properly** > > - **[The RAG Cookbook 2026](https://github.com/FareedKhan-dev/rag-cookbook-2026)** β€” 40 chapters: late chunking, agentic workflows, multi-vector, graph indexes, eval. > - **[RAG & Agentic AI Course](https://github.com/slothlabsorg/rag-course)** β€” concept β†’ pure Python β†’ framework, so you see what LangChain hides. > - **[RAG Engineering](https://github.com/aarunbhardwaj/rag-engineering)** β€” 63 progressive notebooks, core retrieval β†’ enterprise context engineering. > - **[Production Agentic RAG](https://github.com/jamwithai/production-agentic-rag-course)** β€” LangGraph, Docker, FastAPI, Langfuse β€” an engineered service, not a demo. > - **[RAG from Scratch](https://github.com/marcharaoui/RAG-from-scratch)** β€” basic β†’ multimodal β†’ agentic RAG, each variant kept separate to study. ```auto ``` > **πŸ€– Agents from the inside β€” before you reach for LangGraph** > > - **[Build an AI Agent From Scratch](https://github.com/acebot712/agent-from-scratch)** β€” loops, tools, memory, planning, multi-agent, evals, as a tiny framework. > - **[Agent Zero to Hero](https://github.com/KeWang0622/agent-zero-to-hero)** β€” a Claude-Code-style CLI agent: ReAct, MCP, streaming, prompt caching. > - **[Agent Memory Techniques](https://github.com/NirDiamant/Agent_Memory_Techniques)** β€” 30 notebooks turning β€œmemory” from hand-waving into real designs. > - **[Complete Agentic AI Engineering Course](https://github.com/ed-donner/agents)** β€” 6 weeks across modern SDKs, LangGraph, CrewAI, MCP, multi-agent. > - **[GenAI Agents](https://github.com/NirDiamant/GenAI_Agents/)** β€” a grab-bag of agent recipes when you need a specific pattern fast. ```auto ``` > **πŸŽ₯ Multimodal, vision & voice** > > - **[S3 Multimodal Lab](https://github.com/zyziyun/s3-multimodal-lab)** β€” 12 notebooks: Visual RAG, ColPali, voice agents, video search, Whisper, eval + CI. > - **[Kubrick β€” Multimodal Agents Course](https://github.com/the-ai-merge/multimodal-agents-course)** β€” an MCP video agent: video, audio, images, tools, tracing, in one build. > - **[Multimodal LLMs course](https://github.com/emb-ai/mllm-course)** β€” recordings + notebooks: transformers, PEFT, VLMs, video, UI agents. > - **[Hands-On Multimodal System Design](https://github.com/lamhotsiagian/multimodal-system-design)** β€” local-first vision/audio/RAG/MoE, no cloud black boxes. > - **[Document AI: OCR β†’ Agentic Extraction](https://github.com/Ahmed-El-Zainy/Document-AI-From-OCR-to-Agentic-Doc-Extraction)** β€” the messy document side of multimodal. ```auto ``` > **βš™οΈ The systems layer + research agents β€” where courses usually stop short** > > **Serving & inference (why it’s fast/slow/cheap):** > > - **[LLM Inference Handbook](https://github.com/harshuljain/llm-inference-at-scale)** β€” KV-cache, memory bandwidth, speculative decoding, deployment tradeoffs. > - **[Efficient LLM Inference Serving](https://github.com/jiahongsigma/Efficient-LLM-Inference-Serving-Systems)** β€” vLLM, SGLang, PagedAttention, RadixAttention. > > **Research agents (beyond a chatbot demo):** > > - **[deepbrief-lab](https://github.com/zyziyun/deepbrief-lab)** β€” a production-minded Deep-Research agent: ReAct, MCP, A2A, LangGraph, Redis, human-in-the-loop. > - **[DeepResearch Agent](https://github.com/teguh407/deepresearch-agent)** β€” multi-agent long-chain research β†’ cited PDF reports with fact-checking. > - **[lit-review-council](https://github.com/Ravicha2/lit-review-council)** β€” multi-agent literature review with peer-review ensemble + anti-hallucination guardrails. ```auto ``` > **πŸ“¦ One-download curricula β€” grab, unzip, study offline** > > - **[Zero to AI (.zip)](https://github.com/PavanMudigonda/zero-to-ai/archive/refs/heads/main.zip)** β€” 950+ notebooks; the broadest single archive. > - **[AI Engineering from Scratch (.zip)](https://github.com/rohitg00/ai-engineering-from-scratch/archive/refs/heads/main.zip)** β€” 503-lesson first-principles path (math β†’ agents β†’ production). > - **[LLM Zoomcamp (.zip)](https://github.com/DataTalksClub/llm-zoomcamp/archive/refs/heads/main.zip)** β€” 10 weeks of practical LLM apps, no GPU needed. > - **[AI Bootcamp (.zip)](https://github.com/curiousily/AI-Bootcamp/archive/refs/heads/master.zip)** β€” compact applied GenAI: Ollama, LangChain, LangGraph, CrewAI. > - **[Microsoft GenAI for Beginners](https://microsoft.github.io/generative-ai-for-beginners)** β€” 21 lessons, Python + TypeScript, a steady reference baseline. * * * βœ… **Prefer to pay the creator?** Fair β€” the full paid set is at **[courses.vizuara.ai](https://courses.vizuara.ai/)** / the **[10-course bundle](https://complete-pathway.vizuara.ai/)** (lifetime access, notes, certificates), with a cheaper **[Pods](https://pods.vizuara.ai/pricing)** tier. But work through the free stack above first β€” you may find you never need it.