인프런 - 라이프타임 커리어 플랫폼

Learn about job analysis related to Data Science (DS) and Artificial Intelligence (AI) and the learning and employment roadmap for building a career in related jobs.

Through AI corporate reviews, we examine various cases to see how AI technology will change our present and future. Prepare for the upcoming AI Transformation by examining the elements necessary to carry out AI projects.

Let's explore LLM-based applications and web services.

Find your way through the ocean of data and explore the future of artificial intelligence. This course explores two huge technological trends, big data and artificial intelligence (AI), and how they are revolutionizing our lives and work.

This course is a hands-on curriculum for instructors who are new to AI coding education. You will learn step by step from Python basics to simple AI models and prompt engineering.

A complete summary of approximately 130 ML/AI engineer interview questions and answers learned through approximately 20 interviews

Artificial intelligence, AI, agents… Looks grand, but once tried, it's simpler than you'd expect. Through practical projects usable in companies, you'll directly experience diverse use cases, and learn to utilize and apply AI agents.

**"AI Philosophy - Ethics and Challenges in the Age of Artificial Intelligence"** is a topic that deals with the ethical and philosophical exploration of the development of artificial intelligence (AI) and its impact on human society and culture. This topic goes beyond simple technological development and delves into how AI affects human life and what ethical decisions we should make accordingly.

This is a general education lecture for the general public that can help them get rid of the vague fear of artificial intelligence. We will learn through specific examples what it means for artificial intelligence to learn. We will also learn through specific examples what the brain structure of artificial intelligence looks like and how it thinks.

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!

The AWS Certified AI Practitioner past exam question solving course is a core summary course for passing the certification. First, you will quickly review the basic concepts of AI/ML and generative AI, and learn the functions and use cases of key AWS AI services frequently appearing on the exam (e.g., SageMaker, Rekognition, Polly, etc.). Based on this, you will practice determining which AI solution is suitable for various real-world problem situations, and also cover topics related to the responsible use of AI models and data security. Finally, you will learn solution strategies for each type of past exam question and prepare for the exam through a practical mock test. Through this course, you can efficiently prepare for the exam in a short period of time.

This lecture was created to help those who are new to DS/AI and want to study it. It will explain the concept of DS/AI and what fields there are, and tell you what to study and how to study it.

You will understand the present and future of AI technology, experience the testing process of AI models such as machine learning, and learn the role of a tester. You will comprehensively learn everything from establishing AI-based system test strategies to designing and executing test cases, and even methods for utilizing AI to support testing. This course is conducted based on ISTQB's AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

An Artificial Intelligence introductory course tailored to the level of planners and PMs! From data to generative AI, core concepts for successful AI planning are easily organized. The goal is practical understanding to the level of being able to ask questions and explain, rather than creating AI.

This is a machine learning lecture written like a story in easy-to-understand language without formulas, tailored to the level of liberal arts students!

Why this course is special: Key Advantages • Intuitive Visualization: Directly observe algorithm operations in real-time with Pygame 2D simulations • Practical Implementation Experience: Go beyond theory and internalize autonomous driving algorithms by coding directly • Master Core Algorithms: Focused learning of essential algorithms such as Dijkstra, Pure Pursuit, ICP, etc. • Step-by-step Advanced Learning: Systematic difficulty progression from basics to SLAM • Lidar-based SLAM: Practical map building and localization in unknown environments

<How to Use Chat GPT 200%> is a hands-on content focused on ‘How to ask Chat GPT to get the answer you want?’ This course uses the free version of Chat GPT as the base and, depending on the content, also practices some paid versions, so that learners can practice in an environment that suits their needs. Through this course, learners will learn how to ask good questions to Chat GPT and use various extension programs to increase their work efficiency.

Deep learning is a technology that learns data through neural networks composed of combinations of complex functions. In this lecture, we will mathematically understand the core concepts of deep learning and analyze them from the perspective of matrix operations. In particular, utilizing Python's NumPy library, we will visually examine how parameters are updated by directly implementing the forward and backward propagation processes of deep learning. Even the seemingly complex neural network structure becomes clear when analyzed with matrix operations. This lecture focuses more on understanding concepts than coding and is suitable for students who wish to intuitively grasp the principles of deep learning mathematically.

We will create an AI judge by combining CrewAI, knowledge graphs, and inference systems, enabling LLM-based multi-agent technology.