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Welcome to NexSkill
4.9
Master 120+ in-depth topics across LLM fine-tuning, agentic swarms, computer vision, AI security & LLMOps.
Stop building toy demos. Start shipping production AI systems. A deep engineering specialization guided by Mian Ahmad Basit covering custom LLM fine-tuning with QLoRA/DPO, multi-agent swarms with MCP/A2A protocols, ColPali vision RAG, NeMo security guardrails, and Kubernetes LLMOps — from Python foundations to cloud-deployed enterprise AI.
120+
In-Depth Production AI Topics
Lifetime
Content Validity
2
Virtual Internship

Created by: NeXskill
Added Benefit
Gain hands-on experience with major AI tools and receive expert career guidance to boost your professional journey.
Unlock premium features and resources to accelerate your journey

Fine-tune DeepSeek-R1 & LLaMA-3.1 with QLoRA, DPO alignment, and Unsloth acceleration.

Build multi-agent swarms with LangGraph, MCP protocols, and n8n workflow automation.

Master ViT, CLIP, SigLIP, LLaVA, and ColPali vision RAG for multimodal AI systems.

Deploy NeMo guardrails, RBAC, prompt injection defense, and PII masking at scale.

Ship with Docker, Kubernetes, vLLM, LangSmith observability, and AWS/GCP/Azure.
Rated 4.9/5 by 47,715+ learners worldwide!
Programming & AI Foundations (Python, OOP, Async)
AI Foundations & Transformers 101
Prompts to Programs & Programmatic LLMs
KV Cache & Advanced Attentions
Finetuning Language Models & PEFT (QLoRA, DPO)
Mixture of Experts & Reasoning Models
Knowledge Distillation & Small Language Models
Multimodal Vision Systems & Image Understanding
Speech AI & Conversational Audio Systems
Representation Learning & Embedding Systems
Production RAG Systems & GraphRAG
Agentic Systems: Core Architectures & Foundations
Agents: Orchestration, Protocols & Production (MCP/A2A)
Context Engineering & Harness Engineering
LLMOps & Observability (LangSmith, Langfuse)
Production Infrastructure & Cloud Deployment
AI Security, Guardrails & RBAC
Programming & AI Foundations (Python, OOP, Async)
Module 1
AI Foundations & Transformers 101
Module 2
Prompts to Programs & Programmatic LLMs
Module 3
KV Cache & Advanced Attentions
Module 4
Finetuning Language Models & PEFT (QLoRA, DPO)
Module 5
Mixture of Experts & Reasoning Models
Module 6
Knowledge Distillation & Small Language Models
Module 7
Multimodal Vision Systems & Image Understanding
Module 8
Speech AI & Conversational Audio Systems
Module 9
Representation Learning & Embedding Systems
Module 10
Production RAG Systems & GraphRAG
Module 11
Agentic Systems: Core Architectures & Foundations
Module 12
Agents: Orchestration, Protocols & Production (MCP/A2A)
Module 13
Context Engineering & Harness Engineering
Module 14
LLMOps & Observability (LangSmith, Langfuse)
Module 15
Production Infrastructure & Cloud Deployment
Module 16
AI Security, Guardrails & RBAC
Module 17
📅 Schedule: 2 Interactive Sessions Per Week
Total Lectures: 120+ | Duration: 2 hours each
Python developers transitioning to production AI engineering
Software engineers building AI SaaS and automation products
ML engineers deepening LLMOps and deployment skills
Full-stack developers moving into agentic AI platforms
Data scientists seeking production RAG and fine-tuning expertise
Technical professionals targeting AI consulting and freelancing
Fine-tune LLMs with QLoRA, DPO, and production evaluation pipelines
Build multi-agent systems with LangGraph, MCP/A2A, and n8n automation
Deploy secure RAG pipelines with vector DBs, GraphRAG, and vision retrieval
Implement AI security guardrails, RBAC, and observability at scale
Ship cloud-native AI services on Kubernetes with vLLM and LLMOps tooling
Graduate with production repos, architecture blueprints, and instructor mentorship
Direct mentorship from Mian Ahmad Basit — Lead Instructor & CTO
120+ topics across 16 phases with zero omissions and full technical depth
Hands-on production repos, not toy demos or surface-level prompting
2 years LMS access with recordings, notebooks, and periodic updates
Career guidance for AI engineering, LLMOps, and AI consulting roles
Community support and live weekly sessions with code review checkpoints
6600 learners have created their portfolio websites
Check More Review on Youtube
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