Understanding Data Literacy

Let's develop the ability to find rational decision-making models based on mathematical thinking by understanding various elements of AI and data, and solving real-world problems using ChatGPT and no-code programming!

Let's learn various data structures and algorithms and develop practical skills by implementing them through programming!

Let's build a solid foundation in Python and solve data analysis problems!

Basic manners, etiquette, and communication skills training to foster global leaders leading the era of the Fourth Industrial Revolution.

Let's become creators using ChatGPT and generative AI!

Let's build the skills to develop web applications using React and cultivate the capability to apply them in practice!

Let's practice learning how to translate real-life and major-related problems into actual computer programs and utilizing Python-based AI tools!

Understand and learn about Artificial Intelligence and AI ethics, and strengthen your AI digital capabilities by integrating them with your own field of study!

Let's collect and refine data through public data, web scraping, and more, and perform exploratory data analysis!

Let's learn how to collect data from the web and create a supervised learning model for machine learning!

Let's acquire the Python coding skills necessary for artificial intelligence by learning the basics of the Python programming language!

Let's experience collaborative application development in a Linux shell and open-source software environment, and set up the development environment required for coding!

Let's understand the major algorithms of machine learning and deep learning, and get to know artificial intelligence!

Let's understand object-oriented concepts through Java programming and improve our program design and problem-solving skills!

Let's build a solid foundation in MATLAB and apply and understand the basic concepts of programming!

Java Programming Based on Object-Oriented Concepts for Computer Science Majors

Are you a digital talent interested in data? Get started with data analysis through Orange3!

Let's design, implement, and develop while learning the basic and object-oriented concepts of the C++ language!

Learn machine learning techniques using Python and improve your ability to extract information from real-world data and develop predictive models!

Let's understand machine learning and deep learning model algorithms by using Keras!

This content provides basic instructions on how to visualize data using Tableau Public. It is designed to be easily accessible for non-data majors to follow along, and it guides you on how to create effective reports through visualization charts that can be applied immediately in practice.

"Have you given up on data analysis after only studying the tools?" PMs at large corporations only need to look at the data already implemented by the analysis team. However, PMs at startups or side projects are different. They must build the 'foundation' themselves—from designing logs and labeling them to collecting the data. "Everyone says data is important, but what exactly should I implement and where in my service?" Stop getting lost in abstract concepts. Checking login history is the true beginning of Data-Driven Decision Making (DDDM).

Data Visualization Storytelling That's Perfectly Achievable with Excel Alone

Learn the problem definition and hypothesis formulation process, core competencies for data analysis!

I have packed this with everything I want to tell junior PMs/POs who are struggling due to a lack of good mentors. I will generously share various techniques and mental models used by high-performing PMs/POs.

We explain 32 data visualization techniques very quickly and easily from a non-expert's perspective!

In the era of AI and Big Data, are you utilizing your organization's data effectively? This course builds essential capabilities for reading and interpreting data, covering everything from the foundations of statistical thinking to the core principles of machine learning and deep learning. Grow into a practical leader capable of discovering patterns amidst volatility and making data-driven decisions.

This is a replay of the eleventh webinar on how to use the free data visualization tool 'HEARTCOUNT' that requires no coding. Instead of spending time learning data or learning tools, spend it finding the information you need from your data for your work.

Learn various features of Looker Studio (formerly Google Data Studio) using GA4 demo data. This includes explanations and hands-on practice for Looker Studio's visualization elements. In particular, marketers or planners who are not familiar with SQL can learn easy ways to connect and use BigQuery data with Looker Studio. You can learn methods to create dashboards using Looker Studio.

* 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

If you ask an AI to "build a model with this data," the first few lines might look plausible, but as soon as things get slightly complex, it starts using the wrong columns, introduces data leakage, and results in a model that performs worse despite a higher score. This course does not teach you better prompts. Instead, it covers how to directly design a loop (harness) where an agent understands data, plans, writes code, validates its own results, and backtracks when wrong. After manually walking through the five-piece loop of DS-STAR, you will assemble components one by one, from data profile cards, hooks, and skill hierarchies to independent validators and ablation.

Repetitive pipeline management in Data Warehouses (DW), now free yourself from that painful cycle with dbt! Building on the efficiency provided by dbt, become a data analytics engineer who creates higher value through business-centric data modeling, effective data lifecycle management, and more.

Analyzing customers, markets, and revenue patterns—you no longer need to learn it yourself. Just ask AI, and expert-level analysis and strategies are completed in an instant!

Data Analysis that Determines Online MD Performance! Learn essential data analysis and strategy formulation techniques necessary for MDs to maximize sales and profit in the e-commerce market.

Let's use the R language, which processes data easily and conveniently, to help even non-computer science majors develop their skills in utilizing computer programs related to their own fields!

Through a systematic curriculum of 40 lectures, you will learn everything from the basic theories of AI to the applied AI technologies of each algorithm. Through mathematical intuition and R coding algorithm learning and practice, you will develop immediately applicable AI model development capabilities, covering everything from designing algorithm models for data analysis, machine learning, and their application tools to selecting and utilizing them.

🚀 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.

This is a Python basics 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 is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is necessary to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence.

Let's learn how to collect data from the web and create a supervised learning model for machine learning!