Business Data Analysis Part 2 - Basic Statistics

In this course, you will learn how to develop web application Front End using Angular JS. Angular JS is currently attracting attention as a next-generation web application development method along with React JS.

"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.

"From environment setup to practical business projects, a data science journey to find revenue answers through data (39 lectures in total)." Go beyond simply learning how to use libraries and learn how to cook real-world e-commerce data through the data science process. Starting from development environment setup and Numpy/Pandas basics to data preprocessing, statistical analysis, visualization, and business scenario-based RFM segmentation and hypothesis testing! Systematically master the core competencies of a data scientist through practical projects.

This course will teach you the basics of VueJS and practical development methods through mini-projects. Applying VueJS makes web application development easier and reduces the burden on the server, making it a trendy development method. If you learn this course, you will be able to develop using the web development method that is widely used these days.

Introduction to C language, the foundation language for software development

This course covers everything from JSP basics to completing a vehicle purchase shopping mall project, enabling you to carry out real-world projects immediately upon completion. (Please note that this course does not provide a Q&A service.)

Unity3D Practical Project Game Development by Genre Part 01 Defense game.

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

: "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 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.

"From environment setup to practical business projects, a data science journey to find revenue answers through data (39 lectures in total)." Go beyond simply learning how to use libraries and learn how to cook real-world e-commerce data through the data science process. Starting from development environment setup and Numpy/Pandas basics to data preprocessing, statistical analysis, visualization, and business scenario-based RFM segmentation and hypothesis testing! Systematically master the core competencies of a data scientist through practical projects.

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.

Do you have the data but feel overwhelmed about how to read and process it in Python? Don't worry. You can handle it with the magic of Pandas. Pandas is the most powerful, efficient, and useful data processing library. Skill-UP your data preprocessing with Pandas! Get instant insights!

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.

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.

Revolutionize your stock investing with AI! In this course, you will directly build a functional AI automated trading system targeting the top 25 Nasdaq stocks. We provide a special opportunity to gain experience and know-how through mock trading using the Korea Investment & Securities API, and then transition to AI automated trading with a real account. Even stock market beginners will have no problem. We explain basic stock concepts and the reasons why you should invest in US stocks in an easy-to-understand way, while providing all source codes and even remote support. From now on, investing is essential for the next 60 years of our lives. Create your own AI investment partner to join you on this journey!

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

"Big Data + AI Full Stack Development" - The process of building big data that breathes life into AI is carried out in the form of a pilot project. We identify requirements, configure the platform step by step, and perform smart car data exploration and analysis.

The most definitive way to build the backbone of your data No more fragmented knowledge. From DAsP (Data Architecture Semi-Professional) certification to practical modeling skills, this is the single most perfectly structured masterclass. "Are you still relying on piecemeal memorization for data modeling?" The ability of an 'architect' to translate complex business requirements into clear data structures is the most irreplaceable weapon in the IT ecosystem. This course goes beyond simply passing a certification; it provides practical insights to see through the enterprise-wide data flow.

Through this lecture, students are expected to be able to check actual materials such as big data contests and self-introduction essays and determine the direction of their studies and job preparation.

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.

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.

"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.

Through detailed lectures and hands-on practice on the core elements of SQL, we will provide you with a solid foundation to grow into a SQL analysis expert.

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.

If you want to properly learn OCR technology that's truly used in practice, this one course is all you need! Aiming for over 98% accuracy even with unstructured documents and complex layouts, based on the latest SOTA models and real-world know-how, we build enterprise-level OCR projects together.

You will learn about the four stages of big data processing [data collection ▶ data storage ▶ data analysis ▶ expression] in a more fun and systematic way through a code lab method consisting of 30% theory + 70% practice 🧑🏻‍🏫

Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!

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

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