Mastering Generative AI and LLMs: An 8-Week Hands-On Journey&nbsp;Accelerate your career in AI with practical, real-world projects led by industry veteran Ed Donner. Build advanced Generative AI products, experiment with over 20 groundbreaking models, and master state-of-the-art techniques like RAG, QLoRA, and Agents.&nbsp;What you’ll learn&nbsp;• Build advanced Generative AI products using cutting-edge models and frameworks.• Experiment with over 20 groundbreaking AI models, including Frontier and Open-Source models.• Develop proficiency with platforms like HuggingFace, LangChain, and Gradio.• Implement state-of-the-art techniques such as RAG (Retrieval-Augmented Generation), QLoRA fine-tuning, and Agents.• Create real-world AI applications, including:• A multi-modal customer support assistant that interacts with text, sound, and images.• An AI knowledge worker that can answer any question about a company based on its shared drive.• An AI programmer that optimizes software, achieving performance improvements of over 60,000 times.• An ecommerce application that accurately predicts prices of unseen products.• Transition from inference to training, fine-tuning both Frontier and Open-Source models.• Deploy AI products to production with polished user interfaces and advanced capabilities.• Level up your AI and LLM engineering skills to be at the forefront of the industry. About the Instructor&nbsp;I’m Ed Donner, an entrepreneur and leader in AI and technology with over 20 years of experience. I’ve co-founded and sold my own AI startup, started a second one, and led teams in top-tier financial institutions and startups around the world. I’m passionate about bringing others into this exciting field and helping them become experts at the forefront of the industry.&nbsp;Projects:Project 1: AI-powered brochure generator that scrapes and navigates company websites intelligently.Project 2: Multi-modal customer support agent for an airline with UI and function-calling.Project 3: Tool that creates meeting minutes and action items from audio using both open- and closed-source models.Project 4: AI that converts Python code to optimized C++, boosting performance by 60,000x!Project 5: AI knowledge-worker using RAG to become an expert on all company-related matters.Project 6: Capstone Part A – Predict product prices from short descriptions using Frontier models.Project 7: Capstone Part B – Fine-tuned open-source model to compete with Frontier in price prediction.Project 8: Capstone Part C – Autonomous agent system collaborating with models to spot deals and notify you of special bargains.&nbsp;Why This Course?&nbsp;• Hands-On Learning: The best way to learn is by doing. You’ll engage in practical exercises, building real-world AI applications that deliver stunning results.• Cutting-Edge Techniques: Stay ahead of the curve by learning the latest frameworks and techniques, including RAG, QLoRA, and Agents.• Accessible Content: Designed for learners at all levels. Step-by-step instructions, practical exercises, cheat sheets, and plenty of resources are provided.• No Advanced Math Required: The course focuses on practical application. No calculus or linear algebra is needed to master LLM engineering.&nbsp;Course Structure&nbsp;Week 1: Foundations and First Projects&nbsp;• Dive into the fundamentals of Transformers.• Experiment with six leading Frontier Models.• Build your first business Gen AI product that scrapes the web, makes decisions, and creates formatted sales brochures.&nbsp;Week 2: Frontier APIs and Customer Service Chatbots&nbsp;• Explore Frontier APIs and interact with three leading models.• Develop a customer service chatbot with a sharp UI that can interact with text, images, audio, and utilize tools or agents.&nbsp;Week 3: Embracing Open-Source Models&nbsp;• Discover the world of Open-Source models using HuggingFace.• Tackle 10 common Gen AI use cases, from translation to image generation.• Build a product to generate meeting minutes and action items from recordings.&nbsp;Week 4: LLM Selection and Code Generation&nbsp;• Understand the differences between LLMs and how to select the best one for your business tasks.• Use LLMs to generate code and build a product that translates code from Python to C++, achieving performance improvements of over 60,000 times.&nbsp;Week 5: Retrieval-Augmented Generation (RAG)&nbsp;• Master RAG to improve the accuracy of your solutions.• Become proficient with vector embeddings and explore vectors in popular open-source vector datastores.• Build a full business solution similar to real products on the market today.&nbsp;Week 6: Transitioning to Training&nbsp;• Move from inference to training.• Fine-tune a Frontier model to solve a real business problem.• Build your own specialized model, marking a significant milestone in your AI journey.&nbsp;Week 7: Advanced Training Techniques&nbsp;• Dive into advanced training techniques like QLoRA fine-tuning.• Train an open-source model to outperform Frontier models for specific tasks.• Tackle challenging projects that push your skills to the next level.&nbsp;Week 8: Deployment and Finalization&nbsp;• Deploy your commercial product to production with a polished UI.• Enhance capabilities using Agents.• Deliver your first productionized, agentized, fine-tuned LLM model.• Celebrate your mastery of AI and LLM engineering, ready for a new phase in your career.

LLM Engineering: Master AI, Large Language Models & Agents

Become a complete A.I., Data Scientist and Machine Learning engineer! Join a live online community of 900,000+ engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. Graduates of Andrei’s courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Meta, + other top tech companies.&nbsp;You will go from zero to mastery!&nbsp;Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know).This comprehensive and project based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real world projects to add to your portfolio. You will get access to all the code, workbooks and templates (Jupyter Notebooks) on Github, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on the job skills that employers want. The curriculum is going to be very hands on as we walk you from start to finish of becoming a professional Machine Learning and Data Science engineer.&nbsp;The course covers 2 tracks. If you already know programming, you can dive right in and skip the section where we teach you Python from scratch. If you are completely new, we take you from the very beginning and actually teach you Python and how to use it in the real world for our projects. Don't worry, once we go through the basics like Machine Learning 101 and Python, we then get going into advanced topics like Neural Networks, Deep Learning and Transfer Learning so you can get real life practice and be ready for the real world (We show you fully fledged Data Science and Machine Learning projects and give you programming Resources and Cheatsheets)! The topics covered in this course are:&nbsp;- Data Exploration and Visualizations- Neural Networks and Deep Learning- Model Evaluation and Analysis- Python 3- Tensorflow 2.0- Numpy- Scikit-Learn- Data Science and Machine Learning Projects and Workflows- Data Visualization in Python with MatPlotLib and Seaborn- Transfer Learning- Image recognition and classification- Train/Test and cross validation- Supervised Learning: Classification, Regression and Time Series- Decision Trees and Random Forests- Ensemble Learning- Hyperparameter Tuning- Using Pandas&nbsp;Data Frames to solve complex tasks- Use Pandas&nbsp;to handle CSV Files- Deep Learning / Neural Networks with TensorFlow 2.0 and Keras-&nbsp;Using Kaggle and entering Machine Learning competitions- How to present your findings and impress your boss- How to clean and prepare your data for analysis- K Nearest Neighbours- Support Vector&nbsp;Machines- Regression analysis (Linear Regression/Polynomial Regression)- How Hadoop, Apache Spark, Kafka, and Apache Flink are used- Setting up your environment with Conda, MiniConda, and Jupyter Notebooks- Using GPUs with Google Colab&nbsp;By the end of this course, you will be a complete Data Scientist that can get hired at large companies. We are going to use everything we learn in the course to build professional real world projects like Heart Disease Detection, Bulldozer Price Predictor, Dog Breed Image Classifier, and many more. By the end, you will have a stack of projects you have built that you can show off to others.&nbsp;Here’s the truth: Most courses teach you Data&nbsp;Science and do just that. They show you how to get started. But the thing is, you don’t know where to go from there or how to build your own projects. Or they show you a lot of code and complex math on the screen, but they don't really explain things well enough for you to go off on your own and solve real life machine learning problems.&nbsp;Whether you are new to programming, or want to level up your Data Science skills, or are coming from a different industry, this course is for you. This course is not about making you just code along without understanding the principles so that when you are done with the course you don’t know what to do other than watch another tutorial. No! This course will push you and challenge you to go from an absolute beginner with no Data Science experience, to someone that can go off, forget about Daniel and Andrei, and build their own Data Science and Machine learning workflows. Machine Learning has applications in Business Marketing and Finance, Healthcare, Cybersecurity, Retail, Transportation and Logistics, Agriculture, Internet of Things, Gaming and Entertainment, Patient Diagnosis, Fraud Detection, Anomaly Detection in Manufacturing, Government, Academia/Research, Recommendation Systems and so much more. The skills learned in this course are going to give you a lot of options for your career.You hear statements like Artificial Neural Network, or Artificial Intelligence (AI), and by the end of this course, you will finally understand what these mean!&nbsp;Click “Enroll Now” and join others in our community to get a leg up in the industry, and learn Data Scientist and Machine Learning. We guarantee this is better than any bootcamp or online course out there on the topic. See you inside the course!&nbsp;Taught By: Daniel Bourke: A self-taught Machine Learning Engineer who lives on the internet with an uncurable desire to take long walks and fill up blank pages.My experience in machine learning comes from working at one of Australia's fastest-growing artificial intelligence agencies, Max Kelsen.I've worked on machine learning and data problems across a wide range of industries including healthcare, eCommerce, finance, retail and more.Two of my favourite projects include building a machine learning model to extract information from doctors notes for one of Australia's leading medical research facilities, as well as building a natural language model to assess insurance claims for one of Australia's largest insurance groups.Due to the performance of the natural language model (a model which reads insurance claims and decides which party is at fault), the insurance company were able to reduce their daily assessment load by up to 2,500 claims.My long-term goal is to combine my knowledge of machine learning and my background in nutrition to work towards answering the question "what should I eat?".Aside from building machine learning models on my own, I love writing about and making videos on the process. My articles and videos on machine learning on Medium, personal blog and YouTube have collectively received over 5-million views.I love nothing more than a complicated topic explained in an entertaining and educative matter. I know what it's like to try and learn a new topic, online and on your own. So I pour my soul into making sure my creations are accessible as possible.My modus operandi (a fancy term for my way of doing things) is learning to create and creating to learn. If you know the Japanese word for this concept, please let me know.Questions are always welcome. &nbsp;Andrei&nbsp;Neagoie: Andrei is the instructor of the highest rated Development courses on Udemy as well as&nbsp;one of the fastest&nbsp;growing.&nbsp;His graduates have&nbsp;moved&nbsp;on to work for&nbsp;some of the biggest tech&nbsp;companies around the world like Apple, Google, Amazon, JP Morgan, IBM, UNIQLO etc...&nbsp;He&nbsp;has&nbsp;been working as a senior software developer in&nbsp;Silicon Valley and Toronto for many years,&nbsp;and&nbsp;is now taking all that he has learned,&nbsp;to teach&nbsp;programming skills and&nbsp;to help you&nbsp;discover the amazing career opportunities that being a developer allows in&nbsp;life.&nbsp;Having been&nbsp;a self taught programmer,&nbsp;he understands that there is an&nbsp;overwhelming number of online courses, tutorials and books&nbsp;that are overly verbose and inadequate at teaching proper skills.&nbsp;Most people feel paralyzed and don't know where to start when learning a complex subject matter, or even worse, most people don't have $20,000 to spend on a coding bootcamp.&nbsp;Programming skills should be affordable and open to all. An education material&nbsp;should teach real life skills that are current and&nbsp;they should not waste a student's valuable time.&nbsp;&nbsp; Having learned important&nbsp;lessons from working for Fortune 500 companies, tech startups, to even&nbsp;founding his own business, he is now dedicating 100% of his time to&nbsp;teaching others valuable&nbsp;software development skills&nbsp;in order to take control of their life and work in an exciting industry with infinite possibilities.&nbsp;Andrei promises you that there are no other courses out there as comprehensive and as well explained.&nbsp;He believes that in order to learn anything of value, you need to start with the foundation and develop the roots of the tree. Only from there will you be able to learn concepts and specific skills(leaves) that connect to the foundation. Learning becomes exponential when structured in this way.&nbsp;Taking his experience in educational psychology and coding, Andrei's courses will take you on an understanding of complex subjects that you never thought would be possible.&nbsp;&nbsp;See you inside the course!

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