AI A-Z [2026]: Agentic AI, Gen AI, Prompt Engineering and RL
What you'll learn
- Understand the theory behind Artificial Intelligence
- Build 12 different AIs for 12 different applications
- Master the State of the Art AI models
- Solve Real World Problems with AI
- Prompt Engineering
- Generative AI
- Image Generation
- Foundation Models Fine-Tuning
- Retrieval-Augmented Generation (RAG)
- Agentic AI
- Q-Learning
- Deep Q-Learning
- Deep Convolutional Q-Learning
- A3C (Asynchronous Advantage Actor-Critic)
- PPO (Proximal Policy Optimization)
- SAC (Soft Actor-Critic)
- LLMs
- Transformers
- Low-Rank Adaptation (LoRA) and Quantization (QLoRA)
- Responsible AI
Requirements
- High School Maths
- Basic Python knowledge
Description
Welcome to Artificial Intelligence A-Z!
This course is structured in 10 parts:
Part 1 - Prompt Engineering: Prompt Engineering & Prompt Templates, Prompt Engineering Techniques, The 4 Elements of a (good) prompt, Inference Parameters
Part 2 - Generative AI: Fundamentals of Generative AI, Image Generation, Foundation Models Overview, Foundation Models Lifecycle, Data Selection, Foundation Models Selection, Training vs. Inference, Context Window, Tokens and Embeddings, Transformers, Foundation Models Training, Foundation Models Fine-Tuning, Foundation Models Evaluation, Retrieval-Augmented Generation (RAG) for Cooking Assistance
Part 3 - Agentic AI: AI Agents, Building a Cloud-powered AI Agent for Business Assistance
Part 4 - Fundamentals of Reinforcement Learning: Q-Learning Intuition, Q-Learning Implementation
Part 5 - Deep Q-Learning: Deep Q-Learning Intuition, Deep Q-Learning Implementation for Moon Landing
Part 6 - Deep Convolutional Q-Learning: Deep Convolutional Q-Learning Intuition, Deep Convolutional Q-Learning Implementation for Pac-Man
Part 7 - A3C: A3C Intuition, A3C Implementation for Kung Fu
Part 8 - PPO and SAC: Proximal Policy Optimization, Soft Actor-Critic, Build and Train the PPO & SAC models for Self-Driving Cars
Part 9 - LLMs: The Ingredients of an LLM, Who invented LLMs, How LLMs generate text, Understand what's inside an LLM, The LLM Parameters, The LLM Context Window, How to Fine-Tune LLMs for Medical Assistance
Part 10 - Responsible AI: Features of Responsible AI, Guardrails in Generative AI, Legal Risks of Generative AI, AWS Tools for Responsible AI, Amazon SageMaker Clarify and Monitor, Amazon Augmented AI [Amazon A2I], Interpretability vs. Explainability, SageMaker Model Cards
All along this journey, you will learn key AI concepts with intuition lectures to get you quickly up to speed with all things AI and practice them by building 12 different AIs:
Build a ChatBot App that speaks like Master Yoda in 5 Minutes.
Build a Movie Script Generator by leveraging advanced Prompt Engineering.
Build Your Custom LLM with Amazon Bedrock, Databricks, and Hugging Face.
Build a RAG-powered Generative AI application with Amazon Bedrock and Knowledge Bases.
Build an AI Agent with a Foundation Model (LLM) for business assistance, all powered by the Cloud.
Build an AI with a Q-Learning model and train it to optimize warehouse flows in a Process Optimization case study.
Build an AI with a Deep Q-Learning model and train it to land on the moon.
Build an AI with a Deep Convolutional Q-Learning model and train it to play the game of Pac-Man.
Build an AI with an A3C (Asynchronous Advantage Actor-Critic) model and train it to fight Kung Fu.
Build an AI with a PPO (Proximal Policy Optimization) model and train it for a Self-Driving Car.
Build an AI with a SAC (Soft Actor-Critic) model and train it for a Self-Driving Car.
Build an AI by fine-tuning a powerful pre-trained LLM (Llama by Meta) with Hugging Face and re-train it to chat with you about medical terms. Simply put, we build here an AI Doctor Chatbot.
Some of these AIs will be built in AWS, and the others will be built in Python and PyTorch.
But that's not all... Once you complete the course, you will get 3 extra AIs: DDPG, Full World Model, and Evolution Strategies & Genetic Algorithms. We build these AIs with ChatGPT for a Self-Driving Car and a Humanoid application. For each of these extra AIs you will get a long video lecture explaining the implementation, a mini PDF, and the Python code.
Besides, you will get a free 3-hour extra course on Generative AI and LLMs with Cloud Computing as a Prize for completing the course.
And last but not least, here is what you will get with this course:
1. Complete beginner to expert AI skills: Learn to code self-improving AI for a range of purposes. In fact, we code together with you. Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.
2. Hassle-Free Coding and Code templates: We will build all our AIs in Google Colab, which means that we will have absolutely NO hassle installing libraries or packages because everything is already pre-installed in Google Colab notebooks. Plus, you’ll get downloadable Python code templates (in .py and .ipynb) for every AI you build in the course. This makes building truly unique AI as simple as changing a few lines of code. If you unleash your imagination, the potential is unlimited.
3. Intuition Tutorials: Where most courses simply bombard you with dense theory and set you on your way, we believe in developing a deep understanding for not only what you’re doing, but why you’re doing it. That’s why we don’t throw complex mathematics at you, but focus on building up your intuition in AI for much better results down the line.
4. Real-world solutions: You’ll achieve your goal in not only one AI model but in 5. Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any environment in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.
5. In-course support: We’re fully committed to making this the most accessible and results-driven AI course on the planet. This requires us to be there when you need our help. That’s why we’ve put together a team of professional Data Scientists to support you in your journey, meaning you’ll get a response from us within 48 hours maximum.
So, are you ready to embrace the fascinating world of AI?
Come join us, never stop learning, and until then, enjoy AI!
Who this course is for:
- Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning
Instructors
Hadelin is one of Udemy’s top instructors and a recognized leader in AI education. He has taught AI to over 2.6 million learners worldwide and is a frequent guest speaker at prominent industry events. Hadelin has created more than 30 top-rated courses on topics such as AI, Machine Learning, Deep Learning, Blockchain, and Cloud Computing, empowering learners around the globe to upskill in cutting-edge technologies.
In addition to his partnership with Udemy, Hadelin is the co-founder of CloudWolf and SuperDataScience. He is passionate about education and is on a mission to make complex technologies simple, practical, and widely accessible to all.
As a side activity, he is also an actor who acted in seven films, and a movie producer of two films (Indian and French).
My name is Kirill Eremenko and I am super-psyched that you are reading this!
Professionally, I come from the Data Science consulting space with experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and since starting on Udemy I have passed on my knowledge to thousands of aspiring data scientists.
From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. One of the strongest sides of my teaching style is that I focus on intuitive explanations, so you can be sure that you will truly understand even the most complex topics.
To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!
Hi there,
We are the SuperDataScience team. You will hear from us when new SuperDataScience courses are released, when we publish new podcasts, blogs, share cheat sheets, and more!
We are here to help you stay on the cutting edge of Data Science and Technology.
See you in class,
Sincerely,
SuperDataScience Team!
Meet Luka Anicin, an internationally recognized expert in AI and Machine Learning. He kickstarted his career as a Computer Vision Researcher and quickly became a leading Machine Learning Engineer at BlueLife AI. His entrepreneurial spirit led him to launch Scooby AI in 2020, and later sell it. Luka had an amazing opportunity to work in Photomath creating OCR algorithm for scanning mathematical tasks, that currently benefits over 280 million students worldwide.
Luka founded Datablooz, a global technical project consultancy, helping businesses harness the power of AI. As a passionate educator, he's guided over 500,000 students across 197 countries in understanding complex technical topics. Recognized by Google among the top 150 machine learning experts, Luka is a powerhouse of AI, focused on leveraging technology to transform businesses.
Let him be a part of your journey into the realm of AI and Machine Learning.
Join 3.8M+ learners who study with Ligency.
With a 4.6 instructor rating, >1.1 M reviews, and 126 courses in 12 languages, we help engineers, leaders, and teams master the skills that power today’s AI revolution - then ship real results.
We start where the real world starts: with large language models and the products they power. You’ll learn the foundations of AI and Generative AI (gen AI), then ship production-grade systems - chatbots, copilots, automations, and AI agents. We go deep on LLM engineering: retrieval (RAG), evaluation, observability, safety, and the patterns teams use to run agentic systems at scale.
Our stack is practical and current. You’ll prototype fast with Python, LangChain, and LangGraph; explore models from OpenAI, Gemini, and Claude (including Claude Code); fine-tune and serve with Hugging Face and Ollama; and take it to production on AWS - from Bedrock to event-driven services. Need automation? We wire it together with n8n, clean interfaces, and CI/CD. Along the way you’ll master prompt engineering that holds up under load.
Where this leads: roles that ship. AI Engineer and LLM Engineer for those who love building; platform and MLOps paths for those drawn to reliability at scale; product and leadership tracks for the people moving Agentic AI from slide decks to business outcomes. The through-line is the same: learn fast, build faster, measure everything, iterate.
Start with our best selling course:
AI Coder: Complete Claude Code & Coding Agents Course - build complete products at speed with AI coding agents like Claude Code, Cursor, Copilot and Codex, no coding background required.
AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents - a hands-on path from your first prompt to production patterns: 20+ models, RAG, QLoRA fine-tuning, and agents with LangChain/LangGraph.
AI Engineer Agentic Track: The Complete Agent & MCP Course - design, orchestrate, and deploy robust AI agents across OpenAI Agents SDK, CrewAI, LangGraph and MCP.
AI Engineer Production Track: Deploy LLMs & Agents at Scale - scaling patterns for pipelines, monitoring, and enterprise rollout on AWS with Bedrock, Google Cloud Platform, Azure and MLOps.
AI Builder: Create Agents, Voice Agents & Automations in n8n - wire up low-code AI agents, voice agents and business automations in n8n with ElevenLabs, RAG and MCP.
Practical Guide to AI Agents & Agentic AI with Claude Cowork - build six working no-code AI agents on your real tools (Gmail, Slack, Notion, Calendar) with Claude Cowork and MCP.
AI Leader: Generative AI & Agentic AI for Leaders & Founders - a concise playbook for strategy, governance, and ROI with Generative AI and agents.
If your goal is to level up quickly and ship something real, join us. Learn the concepts, touch the tools, build the thing - then take it to users. That’s the Ligency way.