인프런 - 라이프타임 커리어 플랫폼

Natural Language Processing (NLP) is one of the fastest growing areas of artificial intelligence. This course covers a wide range of topics, from the basics of NLP to the latest NLP techniques using deep learning. In particular, it provides an in-depth understanding of cutting-edge generative models such as ChatGPT.

Do you want to take your first step into the world of data? Learn machine learning and deep learning, the core technologies of AI, with Python. This course will guide you step by step, from the basics of machine learning and deep learning to practical applications. Traditional machine learning and deep learning are based on many of the same principles and technical systems. Therefore, this course does not separate the two into separate subjects, but rather organizes them into one connected course so that beginners can increase their understanding of machine learning as a whole.

From the basics of deep learning natural language processing to the latest models such as Transformer and BERT, learn the principles and utilization methods of deep learning natural language processing (NLP) through various examples and practical code implementations.

This is a lecture that studies the physical information neural network, one of the next-generation innovative technologies of deep learning, and implements it directly using Pytorch. Let's learn the next-generation innovative technology of artificial intelligence with me!

This is a basic LangChain lecture that extracts the key points from official documents for the price of a cup of coffee. Get familiar with LangChain grammar before you start developing!

LLM: A pro quickly delivers core content, from essentials to practical tips!

This lecture covers RAG (Retrieval-Augmented Generation) system fundamentals and implementation using LangChain. Participants will understand RAG's core principles and learn to build and evaluate systems using LangChain.

Create your own AI chatbot using Python's basic syntax and libraries. Learn through a step-by-step process of completing 5 projects, including PDF document-based RAG, and deploy them as web services.

You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.

When researching AI or conducting a project using it, basic paper implementation is essential. Let's upgrade our practical skills by implementing an actual paper through this lecture!

All the recent amazing achievements in the field of artificial intelligence have been announced in the field of reinforcement learning. We have covered reinforcement learning technology, which is revolutionizing true artificial intelligence technology such as robots, autonomous driving technology, and human-like machines, from the basics to the advanced level, in an easy-to-understand way for beginners.

This lecture is designed to give you a general understanding of AI without overwhelming you with difficult topics like mathematical formulas. It's perfect for learning with a light and easy mindset.

Make your own AI autonomous vehicle! This is a course where you can learn about AI and reinforcement learning in the most fun and fastest way. This course was produced by the developer ranked #1 in DeepRacer Korea.

This is a lecture where you easily learn important mathematical concepts used in games. People who know math well take that knowledge for granted, so they cannot teach under the assumption that you know nothing. I will explain from a beginner's perspective, truly treating you as someone with no prior knowledge.

This course provides essential knowledge needed to understand the structure and operating principles of various artificial neural networks and create good models.

We will introduce how to create deep learning models and CNN models using artificial neural network algorithms.

AI Era-Proof Silicon Valley Internship & 30 Big Tech System Design & Open Source Practical Contribution Complete Course Mission Submission All students can apply for a US Palo Alto local AI startup internship, with document screening exemption and interview opportunities provided, and this is a course where you design and scale 30 practical system designs using big tech cases like Netflix, Tesla, Meta, Tinder, etc. At the end, you design your own service from architecture → DB → scaling, contribute to an actually operating open source AI coding agent project (achieving 1.8k downloads per week), complete your portfolio, and finalize your resume.

Through this lecture, you'll be able to learn about the AI graduate school admission process and preparation methods from start to finish! I'll also share some great tips to increase your chances of getting accepted!

Implementing a Retrieval-Augmented Generation (RAG) Intelligent AI Agent with LangGraph! From theory to practice, this is a hands-on tutorial that even beginners can easily follow.

This course teaches the “core concepts” of deep learning required to work in the deep learning field and the practical skills required to perform actual deep learning projects through hands-on training using PyTorch.