Business Data Analysis Part 1 - Python and Descriptive Statistics

: "From Mathematical Foundations to the Latest Models, Completing the Deep Learning Pipeline with PyTorch (44 Lectures in Total)" The era of simply learning how to call model.fit() is over. From the very basics of artificial neural networks—differentiation and gradient descent—to essential PyTorch techniques used in the industry, and CNN/RNN for handling image and time-series data! We will help you systematically master the entire process of deep learning. Go beyond analyzed data and step into the amazing world of deep learning, where artificial intelligence mimicking the human brain learns and makes decisions on its own.

"From the basics to 7 domain projects, completing the A to Z of deep learning (41 lectures in total)." Go beyond simply calling models and learn how to build clean, efficient deep learning pipelines using PyTorch Lightning, the current industry trend. Grow into a confident AI engineer capable of handling any data by directly implementing 7 projects, ranging from stock price prediction to generative AI, medical imaging, and sound analysis.

Introduction to C language, the foundation language for software development

We have captured the entire experience of instructor Kim Young-sam, who is active as an emoticon creator on Kakao and LINE, in this lecture—covering everything from emoticon design to creating, submitting, and generating revenue on KakaoTalk and LINE.

Easy explanations and examples are provided so that you can apply them directly to your work.

You can learn all about JavaScript, including an overview of the JavaScript language, basic grammar, and provided libraries.

: "From environment setup to 7 practical projects, a deep learning full-stack journey across data domains (35 lectures in total)" Go beyond simply following example code and learn how to cook various types of real-world data using deep learning. Starting from building CPU/GPU development environments, you will cover waste sorting classification (Image), stock price prediction (Time-series), ECG anomaly detection (AE), animation stylization (GAN), medical image segmentation (U-Net), and sound classification (Audio)! Systematically master core deep learning algorithms through hands-on projects.

: "From Mathematical Foundations to the Latest Models: Completing the Deep Learning Pipeline with TensorFlow (44 Lectures Total)" The era of simply learning how to call model.fit() is over. From the very foundations of artificial neural networks—differentiation and gradient descent—to the essential use of TensorFlow and Keras in the industry, and even CNN/RNN for handling image and time-series data! We will help you systematically master the entire process of deep learning. Go beyond analyzed data and enter the amazing world of deep learning, where artificial intelligence mimicking the human brain learns and makes decisions on its own.

"Beyond Data Analysis: Mastering Predictive Modeling with 5 Real-World Projects (45 Lectures Total)" Have you finished learning data analysis but feel stuck when it's time to actually build a model? Beyond simply learning how to call libraries, this course will help you fully master the inner workings of algorithms and optimal model validation strategies—ranging from Titanic survival prediction to spam text classification. Systematically conquer projects that wield the most power in the industry, from linear models to the latest ensemble algorithms and the basics of Natural Language Processing (NLP). Step into the world of AI modeling and start predicting the future based on analyzed data.

"Beyond Data Analysis: From Predictive Model Design to Optimization (29 Lectures in Total)" Have you finished your data analysis but feel stuck when it actually comes to building a model? We help you fully master not just how to call libraries, but the working principles of each algorithm and optimal model validation strategies.

* 100% Practical Curriculum: Focused on hands-on data handling rather than grammar-based learning * Essential Machine Learning Prep: A complete summary of data preprocessing techniques required before AI training * Data Analysis Tool Mastery: Conquer core functions of Numpy (numerical operations) and Pandas (data manipulation) * Deriving Visualization Insights: Transferring data visualization skills using Matplotlib and Seaborn * Building Statistical Foundations: Learning basic statistics and group analysis techniques to identify data characteristics

Currently, Android development can be done using both Java and Kotlin. You can develop the same Android applications regardless of which language you choose. This course covers most aspects of Android application development, from basics to advanced topics, and all code is written using Kotlin starting from the fundamentals. Additionally, it utilizes Google's latest UI library, Material 3. This course involves completing three projects throughout the entire Android curriculum. By working on these projects, you can master advanced techniques actually used in the industry, such as Hilt, Retrofit, Room Database, and MVVM. Furthermore, you can increase productivity using AI by performing "vibe coding" with Gemini within the Android development tools. Soft Campus will always strive to provide the most up-to-date lectures.

Android can be developed using the Java and Kotlin languages. You can develop the same Android application regardless of which language you use. This course covers most aspects of Android application development, from basic to advanced levels, and all code is written using the Kotlin language starting from the basics. Additionally, it utilizes Google's latest UI library, Material 3. This course primarily focuses on the action bar, data management, resource management, sensors, and networking within the overall Android development process.

Currently, Android can be developed using the Java and Kotlin languages. You can develop the same Android applications regardless of which language you use. This course covers most aspects of Android application development, from basics to advanced levels, and all code is written using the Kotlin language starting from the fundamentals. Furthermore, it utilizes Google's latest UI library, Material 3. This course primarily focuses on menus, Android application components, threads, and fragments within the overall Android curriculum, and more in-depth topics will be covered in the next course. Soft Campus will always strive to provide the latest lectures. Thank you.

You can create hybrid casual games using Unity 6.

Learn C# in the Unity environment. Learning C# will help you naturally learn the Unity development environment, which will be very beneficial for beginner developers.

This is the Android 15 App Development Part 1: UI Programming course featuring the latest Material 3 library.

With the latest version in 2024 and a running time of 17 hours and 48 minutes, you can completely conquer Kotlin with this one course.

This course teaches you how to develop front-end web using React. You will learn the core JavaScript grammar for React, CDN-based React development, and NPM-based React development methods.

Using Unity based on the C# language, you will learn how to create a defense game step by step.

If you could draw graphs but couldn't explain the data, this course is a process for building the "ability to read and explain" data. In PART 3, we perform Exploratory Data Analysis (EDA) focusing on real-world cases. ✔ Checking data distribution ✔ Analyzing relationships between variables ✔ Outlier detection and visualization interpretation You will learn the analysis structure using the Titanic and Iris datasets, and through a project utilizing TMDB 5000 movie data, you will directly experience the entire analysis process: Data cleaning → Setting analysis topics → Visualization interpretation. By the end of this course, you will possess the analytical capability to read and explain data.

The [Customized Basic Python for Data Analysis] course that even non-majors have easily completed! Learn the basics of using ChatGPT alongside it to create a "starting point" for data analysis and AI utilization. From essential prerequisites for data analysis to customized learning from a "Data Analysis Instructor," you can build deep foundational skills while learning quickly. This course instills the courage and confidence needed for coding and provides a roadmap for your future data analysis studies.

This course focuses on developing immediately applicable visualization skills by utilizing Seaborn, a core tool for data visualization, and Plotly/Dash for building interactive dashboards. Through various hands-on exercises, you can simultaneously improve your ability to create insight-driven visual materials and implement web-based dashboards.

* 100% Practical Curriculum: Focused on hands-on data handling rather than grammar-based learning * Essential Machine Learning Prep: A complete summary of data preprocessing techniques required before AI training * Data Analysis Tool Mastery: Conquer core functions of Numpy (numerical operations) and Pandas (data manipulation) * Deriving Visualization Insights: Transferring data visualization skills using Matplotlib and Seaborn * Building Statistical Foundations: Learning basic statistics and group analysis techniques to identify data characteristics

This course is a practical Airflow master program designed to help you understand "why Airflow works this way" and enable you to design and debug data pipelines on your own. It covers everything from Apache Airflow's core mechanisms to detailed theory and hands-on practice involving DAGs, Operators, Hooks, Scheduling, Timezones, Idempotency, and Templates.

A course to understand and practice machine learning for efficiently conducting complex analysis and predictions! Even machine learning, which may seem difficult and complex, can be easy and fun to master with Masocampus's <Python Machine Learning>.

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.

"From the basics to 7 domain projects, completing the A to Z of deep learning (41 lectures in total)." Go beyond simply calling models and learn how to build clean, efficient deep learning pipelines using PyTorch Lightning, the current industry trend. Grow into a confident AI engineer capable of handling any data by directly implementing 7 projects, ranging from stock price prediction to generative AI, medical imaging, and sound analysis.

Students who want to learn Hadoop and Big Data will celebrate the amazing advancements in experiencing the world of Big Data through this course!

This course focuses on developing practical visualization skills that can be immediately applied in the workplace by utilizing Seaborn, a core tool for data visualization, and plotly/Dash for building interactive dashboards. Through various hands-on exercises, you can enhance both your ability to create insight-driven visual materials and implement web-based dashboards.

We explored the essential Python syntax necessary for big data analysis and, through various examples, presented methods such as big data file processing and visualization.

You will learn Apache Airflow, the most widely used Orchestrator for creating software data pipelines.

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

What do you learn in the 'Management Information Visualization Professional' certification course? This certification course focuses on developing the ability to analyze data effectively, visualize it for easy understanding, and communicate necessary information clearly and efficiently for important decision-making within companies or organizations. In simple terms, it is a process of learning the skills to not just look at data, but to uncover hidden meanings within it and express them through charts, tables, and graphs so they can be easily explained to others. Through this course, you will: Develop the power of strategic thinking through data, build practical skills that can be applied immediately to real-world tasks, and enhance your professional expertise and competitiveness. Through this lecture, cultivate the ability to connect management with data and take a step forward as an expert who understands and explains data.

Here are some key competencies that are often overlooked by others in the fiercely competitive and complex semiconductor process job market.

"Why does my automated trading collapse in a bear market?" I have also deeply pondered this same question. Most automated trading logics on the market seem to generate profits during a bull market, but they lose their ability to respond the moment the market sentiment changes. To solve this problem, I have combined the know-how I researched myself over the past two years with the latest AI technology. In this course, you will learn how to directly design a 'Transformer-based deep learning model' that simultaneously reads macroeconomic trends and individual stock flows, and how to automatically train and deploy it in a free GPU environment. In particular, we will introduce sophisticated data normalization techniques at the hedge fund level to build an 'Intelligent Comprehensive Scoring System' that goes beyond simple indicators to incorporate news sentiment. To this, we add an 'AI Safety Gate' that implants the insight of a trader with 20 years of experience on Wall Street, adding a final layer of confidence from a human trader's perspective right before a purchase. Beyond simple buying and selling functions, you will directly implement the entire process of an institutional-grade algorithmic system by adding dynamic take-profit and stop-loss logic, eight self-recovery mechanisms, and real-time Slack reports.

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.

In this class, you will learn about the principles and methods of analyzing and processing various types of financial data using Python's Pandas library, apply them to situations you may encounter in the real world, and ultimately learn how to implement backtesting based on financial statement data (based on Kang Hwan-guk's book, "You Can Do Quant Investment"). As a result, you can break away from being a "passive investor" who simply follows what others say without verifying or basing the investment logic, and become a "self-directed and active investor" who can freely extract various elements necessary for strategy implementation from data and quantitatively analyze them using Python and Pandas.

Learn NoSQL technology for handling big data, one of the fundamental skills in full-stack and data science technologies used by modern startups. MongoDB is the easiest and fastest NoSQL technology to utilize. In this course, you will learn the basics of MongoDB in a short time and master the skills to handle and utilize MongoDB with Python.

This is a special lecture that can lay the theoretical foundation to simultaneously prepare for the Microsoft AZ-900 certification, and as the latest content reflecting the scope of questions as of May 2025, by providing content related to core data concepts, Azure's relational data, Azure's non-relational data, and Azure's analytical workloads in a form combining theory and practice, it can be utilized as a meaningful educational opportunity to not only obtain the certification but also take the first step towards becoming a data professional.