Description

Become a Modern AI Engineer & Build Real-World AI Systems (GenAI + LLMs + Agents)Unlock the power of Artificial Intelligence and Generative AI by learning how to build real-world, production-ready AI systems used in today’s industry.The ProblemAI Engineers are in extremely high demand, but most learners struggle to break into this field because:* AI is taught in disconnected topics (ML, DL, NLP, LLMs separately)* Many courses focus only on theory or basic tools like ChatGPT* There is no clear roadmap from beginner to advanced* Building real-world AI applications feels overwhelmingEven after learning concepts, connecting everything into real systems is where most people get stuck.The SolutionThis course is designed as a complete, structured AI Engineer Bootcamp.Instead of teaching isolated topics, this course takes you step-by-step through a clear roadmap:Python → Machine Learning → Deep Learning → NLP → LLMs → RAG → AI Agents → Real ProjectsYou won’t just learn AI — you will build real AI systems.What You Will LearnFoundations of AI & Python* Python for AI (NumPy, Pandas, Data Visualization)* Data analysis and EDA (Exploratory Data Analysis)* Core AI concepts and real-world applicationsMachine Learning (Core)* Regression, classification, clustering* Model evaluation (accuracy, precision, recall)* Overfitting vs underfittingProjects:* House Price Prediction* Spam Email Classification* Customer SegmentationDeep Learning* Neural networks and backpropagation* CNNs for image data* RNNs and LSTMs for sequences* Introduction to TransformersNatural Language Processing (NLP)* Text preprocessing* TF-IDF vs embeddings* Word embeddings and BERTProject:* Sentiment Analysis SystemGenerative AI & LLMs* Understanding Large Language Models (LLMs)* Tokens and context windows* GPT, Claude, LLaMA differences* Open vs closed modelsTransformers & Hugging Face* Self-attention and transformer architecture* Encoder vs decoder* Using Hugging Face models and tokenizersPrompt Engineering* Zero-shot and few-shot prompting* Chain-of-thought reasoning* Prompt templatesBuild Real AI SystemsRetrieval Augmented Generation (RAG)* Chunking strategies* Embeddings and similarity search* Retrieval + generation pipelinesProject:* PDF Question Answering SystemAI Agents (LangChain & LangGraph)* Tools, memory, and planning* Single-agent and multi-agent workflowsProject:* AI Research AgentBonus Topics* Fine-tuning LLMs (LoRA, PEFT)* Computer Vision basics* Diffusion Models (Stable Diffusion)* Build UI apps using Streamlit and GradioHands-On ProjectsThis is a project-based course where you will build:* EDA Notebook* Machine Learning models* NLP systems* CNN image classifier* RAG-based AI assistant* LLM chatbot* AI agent systemWho This Course Is For* Developers who want to become AI Engineers* DevOps / Cloud engineers moving into AI* Students looking for a structured roadmap* Anyone interested in Generative AI and LLMs* Professionals who want hands-on AI skillsBy the End of This CourseYou will be able to:* Build end-to-end AI applications* Work with LLMs and modern AI tools* Create AI agents and automation systems* Design real-world AI solutions* Apply for roles like AI Engineer, GenAI Engineer, and ML EngineerWhat You Get* Complete AI Engineer Bootcamp* Hands-on real-world projects* Lifetime access and future updates* Certificate of completionFinal NoteAI is not the future — it’s already here.The real question is:Will you just use AI tools… or build them?Start your journey today and become a job-ready AI Engineer.