- AI School
- Complete AI Engineer Bootcamp 2026: Python, NLP, LLMs, LangChain & Hugging Face
Complete AI Engineer Bootcamp 2026: Python, NLP, LLMs, LangChain & Hugging Face
Master the Full AI Engineering Stack — From Python Fundamentals to Production-Ready LLM Applications with Transformers, RAG, and Real-World APIs
Go from absolute beginner to production-ready AI Engineer This is the most comprehensive AI Engineering course of 2026 — a single path that takes you from Python basics to deploying production LLM applications, covering...
What you'll learn
- The AI Engineering Landscape in 2026
- Python Foundations for AI Engineers
- Data Processing and Feature Engineering for NLP
- Natural Language Processing from Scratch
- Deep Learning and Neural Networks for NLP
- The Transformer Architecture Deep Dive
+ 4 more chapters below
Engr. Mejba Ahmed
Course Instructor
100% Free
40 lessons · certificate · no card
About This Course
Go from absolute beginner to production-ready AI Engineer
This is the most comprehensive AI Engineering course of 2026 — a single path that takes you from Python basics to deploying production LLM applications, covering every layer of the modern AI stack instead of a single tool.
You'll start with the landscape and career map, then build a rock-solid Python foundation for AI — core syntax, NumPy and Pandas, and working with APIs, JSON, and file I/O for real pipelines.
What you'll master:
- NLP from the ground up — text preprocessing, tokenization, vectorization (TF-IDF, embeddings), sentiment analysis, classification, NER with spaCy, and topic modeling
- Deep learning for NLP — neural network foundations, PyTorch, RNNs/LSTMs, and the attention mechanism
- The Transformer architecture — a complete technical breakdown, plus BERT, GPT, and choosing encoder vs decoder models
- The Hugging Face ecosystem — pipelines and the Model Hub, fine-tuning with the Trainer API, and sentence transformers for semantic search
- LLMs in practice — working with OpenAI, Anthropic, and open-source models, prompt engineering, function calling, and evaluation
- LangChain & LangGraph — chains and LCEL, conversational memory, autonomous agents, and stateful workflows
- Vector databases, RAG & deployment — embeddings and indexing, production RAG, and deploying AI APIs with FastAPI plus monitoring
Who this is for: beginners and career switchers who want the complete AI Engineering skill set, built through hands-on projects. By the end you'll understand the full stack — from tokenization to a deployed RAG API — and have the portfolio to prove it.
Who this course is for
No prior experience required — you'll start from the fundamentals and build up.
Course Curriculum
2 lessons available to preview
Your Instructor
Engr. Mejba Ahmed
AI Developer · Software Engineer · Entrepreneur
I build production AI systems and full-stack applications for a living, and I teach the exact workflows I use in real projects — not theory. Over 8+ years I've shipped 1,500+ projects, founded Ramlit Limited, and now build agentic AI tooling with Claude, GPT and open models. AI School is where I share that hands-on playbook so you can build and ship real work.
FAQ
Frequently asked questions
Yes. AI School is Open Access — enter your email once to unlock all 40 lessons instantly. No credit card and no trial.
No prior experience required — you'll start from the fundamentals and build up.
Yes. Complete every lesson to earn a verifiable certificate of completion you can add to your LinkedIn profile and CV.
Forever. Learn at your own pace on any device — your progress is saved automatically as you go.
Engr. Mejba Ahmed — an AI developer and software engineer with 8+ years of hands-on production experience.
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