Python in Practice

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The start of smart work - work intelligently anywhere, mobile or PC! Go beyond the limits of content creation with the most advanced Google AI tools available today.

A complete roadmap for obtaining the Big Data Analysis Engineer certification! We provide a systematic learning process for passing the exam, from data analysis beginners to experts.

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The Latest Trend in Generative AI, AI Agents! How to Stay Ahead with Cursor, which handles all development tasks, and MCP, which expands functionality!

Master the nationally certified data analysis associate specialist qualification exam in 2 weeks! Acquire the core theories and background knowledge of data, and learn advanced knowledge of data analysis using R, a statistical analysis tool.

Claude AI First Steps: Get It Right from the Start, Directly Applicable in Practice! Want to use it smarter? Start with Claude AI.

From controlling your PC to advanced research and app development A guide to building your own 'AI work assistant' ready for immediate deployment

Midjourney, the premier tool for image-generating AI! From basic usage to real-world application through practical design projects, all in one go!

Now is the time to answer based on data rather than experience! If you quantify the reliability with statistical knowledge and present it as evidence, your persuasiveness will increase infinitely!

Understand machine learning concepts, AI learning principles, and mathematical principles for model implementation to fully utilize deep learning!

Even if you don't know how to code, Excel is enough! This is a lecture that teaches automation through automation so that even non-majors can easily merge, edit, organize, and handle large amounts of data with Excel.

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Apply the latest trends of Generative AI directly to your work! The bible of Prompt Engineering lectures, packed with essentials

This course is designed so that even those who are unfamiliar with statistics or are not confident in statistics can easily perform data analysis using R. Understand the basic grammar and data structure of R that can be easily overlooked, and develop your data analysis skills through various examples and practice!

If you've ever thought... "I wish I had JARVIS, Iron Man's perfect assistant"?! Complete everyone's JARVIS to help with your smart work management!

From understanding SQL to using actual functions, Complete preparation for SQLD certification with the latest past exam questions!

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Write meeting minutes, build apps, and even create videos all on one platform. Become an AI multiplayer with Google AI Studio!

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We will cover the major Python libraries that you must learn to become a data analysis expert.

The Intermediate Python course is designed to deepen your understanding of Python by covering advanced topics such as functional programming, metaprogramming, exception handling, and object-oriented programming.

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>.

Leverage Python to create your own indicators and a convenient tool for securities analysis!

Now display Python results as web pages! You can create your own web page using only Python. This is an opportunity to create an Interactive Dashboard that allows you to check results created with Python, such as data analysis and machine learning, on a web page!

In Part 3 of Creating a Python Trading Room for Quant Investment, you will learn about portfolio theory and concepts necessary for real investment, as well as how to implement them with code. In Parts 1 & 2, you mainly learned about code implementation methods for analyzing financial data, and in Part 3, you will learn about 'portfolios', which are an important part of quantitative investment. With the question of why you should create a portfolio, you will learn portfolio theory, implement it in Python, and practice the code necessary for real portfolio investment. I hope this lecture will be helpful for your own portfolio investment.

I want to create an algorithm trading bot that makes unlimited money and run it automatically. Where should I start?

With Python Quant Investment, you can create investment strategies based on data and invest according to the strategy. You can implement various asset allocation strategies and ultimately create your own investment strategy.

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.

AI that thinks and adapts? Now you can build it yourself. Master the core of reinforcement learning with intuitive explanations and code, not complex theories, and grow into a 'practical developer' through finance and industry projects.

Finally, the Probability and Statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice. Reference book "Probability and Statistics for Everyone" https://wikidocs.net/book/18165

Based on the instructor's own failed experiences when first learning machine learning, this is a newly designed course that differs from existing lectures, making it easy to understand machine learning and apply it to real-world problems

🚀 Practical AI Anomaly Detection with Databricks! 💡 Stop using expensive and slow models! From large-scale data optimization to real-time deployment, complete an anomaly detection AI that can be used immediately in corporate practice.

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.

In this class, you will learn techniques for retrieving (crawling) and processing data from various operating sites using Python, and apply them directly to various examples that you may encounter in the field. Through this, you will learn techniques that focus on solving practical problems based on an understanding of the basic principles of how the web works, rather than one-dimensional task automation by copying and pasting given codes, and accordingly, you will be able to collect and process data from any site in the future. You will also learn how to resolve various exceptions that occur in this process with code, and ultimately, you will be able to solve and automate various problems that occur in daily life with programming thinking.

This course aims to acquire Python-based web crawling technology to collect data from web pages and improve data collection and analysis capabilities at work based on this.

You can learn the skills and know-how needed to improve work efficiency by utilizing Open API and Python.

Revolutionize your stock investments with AI! In this lecture, you will directly build a real, working AI automated trading system targeting the top 25 NASDAQ stocks. We provide a special opportunity to gain experience and know-how through simulated investments with the 한국투자증권 API, and to perform AI stock automated trading with a real account. Even stock beginners will have no problem. We will easily explain basic stock concepts and why you should invest in US stocks, and provide all source code and remote support. From now on, investment is essential for the next 60 years of our lives. Create your own AI investment partner that will be with you!

We guide non-majors and beginners to quickly obtain the Big Data Analytics Engineer practical certification! Theory lightly, practice thoroughly - even without complex background knowledge, we focus on learning only the essential points that appear on the exam, centered around past exam questions.

Through this course, you can learn SQL and database fundamentals, SQL syntax, database design for practical applications, database utilization through programming, and data analysis use cases.