인프런 - 라이프타임 커리어 플랫폼

Easy, powerful, always-on data analysis! Orange 3: Simple, no coding!

Financial data such as stocks, exchange rates, coins, real estate, and bonds are easily accessible and provide us with opportunities to make money, but most people miss valuable opportunities because they do not know their characteristics and how to handle them. Through this lecture, you can learn how to understand the meaning of various financial data and how to analyze them using Python.

Data analysis is complete with this one tool. Get started with Orange AI data analysis without coding!

I will guide non-majors and beginners to quickly pass the Big Data Analysis Engineer practical exam! Theory lightly, practice thoroughly. Even without complex background knowledge, focusing on past questions, we intensively study only the points sure to appear on the exam.

Unlike existing lectures, this course has been newly designed based on the instructor's initial failures in learning machine learning, enabling easy understanding and application to real-world problems.

Learn how to process big data from a Silicon Valley software engineer & how to develop big data code with Apache Spark using Python. I am a 14-year software developer who handles everything from web applications to big data and SRE & DevOps with Python. Don't miss this opportunity to learn about Apache Spark, which is essential for big data professionals, in an easy and in-depth way using Python!

From the basics of machine learning & deep learning! Creating and utilizing classification/regression/clustering/artificial neural networks with Python

Learn a systematic approach to S&P 500 pair trading with Python. Lay the foundation for an investment strategy that excludes emotions through professional data analysis.

A course to understand and practice machine learning that efficiently performs complex analysis and prediction! Machine learning, which seemed difficult and complicated, can be easily and enjoyably learned in its core with Maso Campus' <Python Machine Learning>.

Make AI data analysis and modeling results into a Web Program.

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence.

SSIS, SSAS, MachineLearning, BI, ETL. You can learn important technologies that cannot be found in domestic books, YouTube, lectures, blogs, and academies. I also recommend it to those who are interested in employment at domestic large companies, American large companies, and American state funding agencies.

The automotive and parts manufacturing industry is a field where innovation is essential amid fierce global competition and complex supply chains. This course focuses on how AI technology can be applied in the field, explaining actual cases including production efficiency improvement, quality inspection automation, equipment predictive maintenance, and supply chain optimization. From the foundational understanding needed for AI implementation to strategies and risk management considerations for field application, this course covers topics step by step, providing knowledge and insights that practitioners and managers can immediately utilize.

From building analysis models to applying them with Orange! Learn easily and quickly! Master the core skills of data science without coding!

A process to upgrade from a beginner in Python to a Python practitioner! Learn about data analysis and data visualization using Python, and increase your ability to use it for company work through real-world projects.

Even if you don't know how to code, Excel is enough! This course covers everything from statistics to machine learning and Power Query, and even non-majors can use Excel to analyze data.

ADsP Certification All-In-One Course! Ultra-Short Completion! Reference Book: "Everyone's ADsP Cheat Sheet" https://wikidocs.net/book/18829

Do you want to become a data analytics expert of the future? Grab your chance now! This is a unique opportunity to explore infinite possibilities and learn how to derive powerful insights through cutting-edge artificial intelligence technology and big data.

This is a basic Python course for starters who want to grow as data analysts. - Those who want to do data analysis but don't know Python - Those who want to learn machine learning with Python - Those preparing for the Big Data Analytics Engineer practical exam - Those who want to develop machine learning-based applications with Python

This course covers how to leverage AI in the food and pharmaceutical manufacturing industry to enhance productivity and quality. Through real-world case studies, you'll learn how AI is applied in key stages such as raw material management, production processes, quality inspection, and regulatory compliance, while understanding defect rate reduction and efficient operational strategies. Through this course, learners will master ▲characteristics of the food and pharmaceutical industry and the necessity of AI adoption ▲data-driven quality management ▲predictive maintenance and equipment optimization ▲regulatory compliance monitoring and risk management ▲analysis of domestic and international implementation cases, gaining strategies and insights that can be immediately applied in the field.