Python pyautogui for task automation, beautifulsoup crawling basics

This course is designed for beginners, students, and those who want to use Polars, aiming to acquire the necessary skills for data analysis, from basic concepts of the Python-based data analysis library Polars to simple data processing and exploratory data analysis (EDA).

This is a practical QGIS course where you can not only master both Python and GIS but also learn automation methods by using them together!

This is a practice-oriented course designed to increase work efficiency by automating repetitive Excel tasks with Python. You will learn how to automate the entire workflow—from opening files to data processing, inspection, consolidation, and saving—and will also be provided with practical automation code using pywin32.

Even office workers who know nothing about coding can easily learn the basic concepts and grammar of programming through practice, and learn file input/output, Excel data processing, automatic creation of MS-Word documents, graph drawing, web scraping, etc.

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 is a valuable course that will free you from simple repetitive tasks and teach you web crawling in 12 hours. Smart Talent Campus, a big data specialized education institute, has prepared an efficient and up-to-date curriculum for 2022 for those who want to collect data efficiently based on specialized education methods accumulated over many years!

This is a practice-oriented course designed to increase work efficiency by automating repetitive PowerPoint tasks using Python. You will learn how to automate the entire document creation process—from creating slides to entering text, inserting images, generating tables, controlling shapes, and saving files. Practical PowerPoint automation code using pywin32 is also provided.

Prepare perfectly for the Goorm environment—the biggest challenge of the Big Data Analysis Engineer practical exam—on Algorun’s practice platform. Repeatedly practice past Type 1, 2, and 3 problems in the same way as the actual exam environment, developing real exam-day proficiency rather than memorizing code. This is a hands-on, practice-focused course designed to train you to work instinctively even in an environment different from Colab or Jupyter.

Chatgpt is a program that reads and comments on posts written by my neighbors Lesson on developing marketing automation and neighbor management programs

We’ll guide non-majors and beginners to quickly earn the Big Data Analysis Engineer practical certification! Keep the theory light and the practical training solid. Even without complex background knowledge, you’ll focus on past exam questions and study only the key points that are sure to appear on the test.

Automate repetitive Excel, Word, Outlook, and PowerPoint tasks with AI—without writing code yourself.

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.

Even when using AI, the reason you’re still busy lies not in the tools, but in how the work is arranged. By asking four questions—roles, flow, handoffs, and exceptions—you can turn your work into a single blueprint, separate what can be handled by rules from what requires judgment, and reduce how often you need to call on AI in the first place. Use an Excel file containing 1,000 transactions to lock the standards into the tool and generate reports, break tasks down with sub-agents, and hand off what can’t be done to another AI, receiving only the results and carrying on. Finally, connect a messenger as the entry point and add four safety measures, completing the conductor’s role of calling on AI only where needed rather than handing everything over across eight installments, including the OT.

Based on the instructor’s experience of struggling when first learning machine learning, this course has been newly designed—unlike conventional courses—to help you understand machine learning easily and apply it to real-world problems.

ChatGPT-aided Python for Programming Dropouts.

From the basics of Python to applications, everything you can do with Python, including web, data analysis, crawling, business automation, GUI, and programming, is covered in one course.

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.

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.

This lecture is for beginners who are new to coding, as well as those who want to try out various uses of Python, covering basic concepts of Python, Numpy, Pandas, Plotly, Django, and crawling, as well as simple data analysis.

From analyzing the encryption mechanisms of ZIP, PDF, and MS Office files to hands-on dissection of the WannaCry ransomware, master static analysis tools and GPU-accelerated cracking techniques. This is a practical, security engineering-focused course that builds incident response capabilities through the development of next-generation malware analysis pipelines using OpenAI Codex and automated report generation.