Data Analysis Learned Through Python Code

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 become creators using ChatGPT and generative AI!

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

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

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

Modern C++ Programming based on Object-Oriented Concepts for Computer Science Majors

Let's find out how to automate tasks using Python!

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 cultivate professional expertise in programming, algorithms, and statistical analysis!

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

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

Let's look into how to deploy Abyss for non-majors!

Let's understand data analysis tailored for advanced retail businesses and learn how to use the tools utilized in the industry!

It improves logical thinking skills and cultivates the capacity to converge one's major with information and communication technology in the era of the Fourth Industrial Revolution.

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

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

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

It improves logical thinking skills, fosters the ability to understand how to use programming tools, and develops the capacity to design algorithms for problem-solving.

Let's develop data-driven administrative practical skills to empirically solve administrative and policy problems by analyzing public data with R and Python!

Have you studied Python syntax but felt lost when it came to actually handling data? You know you need to learn NumPy and Pandas, but if you've been wondering where to start and how to connect them, this PART 2 is the answer. In PART 2 of our 50-lecture data analysis curriculum, you will experience the step-by-step process of loading, cleaning, processing, and statistically interpreting real data. You won't just learn libraries and syntax; you will establish criteria for which tools to choose in specific situations. PART 2 is the turning point where you move from simply knowing Python code to actually being able to handle data.

From Python fundamentals to practical data analysis! You will learn practical Python skills for processing, visualizing, and analyzing data while solving business problems.

This is a course that offers extensive practice in Python's basic syntax. This is a course that provides practical exercises used in Machine Learning and Deep Learning, along with Python's syntax.

1. A practice-oriented lecture designed to help you pass the AICE Associate, Korea's only nationally recognized AI certification. 2. Learn to the level of performing data analysis and AI modeling based on Python.

Using pandas, we will learn data processing patterns that frequently appear in real-world situations and analyze the processed data.

Coding Test [ALL IN ONE] ✔️ Complete with one lecture

It would be efficient to automate IT security tasks using Python, wouldn't it? This course follows hands-on practice, applying Python and web Flask development to automate tasks, idea by idea.

AI does the coding, I get the results! Maximize practical programming skills, achievable even for beginners!

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.

Learn network programming from scratch, fully utilizing Python and ChatGPT. Rather than tedious conceptual explanations, the focus is on students directly writing network code through practical exercises and personally verifying how their written programs operate. You can acquire skills ranging from basic network practicals to network technologies applicable in real-world scenarios, and build deep understanding and proficiency through exercises dealing with various protocols and tools. Furthermore, by leveraging ChatGPT, students can have a memorable learning experience without feeling difficulty or boredom.

* 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

Prepare perfectly for the Goorm environment—the biggest challenge of the Big Data Analysis Certification practical exam—on the practice platform provided by Algorun. Practice past exam questions for Task Types 1, 2, and 3 repeatedly in a setting identical to the actual exam environment to gain an intuitive feel for the test rather than just memorizing code. This is a practice-oriented lecture designed to train your hands to move automatically in an environment that differs from Colab or Jupyter.

🚀 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.

If you have repeatedly failed at studying Python, this is a must-take course. We will teach you how to study practical Python that you can actually use, in connection with "blog automation."

We guide non-majors and beginners to quickly obtain the Big Data Analysis Certification (Practical Exam)! Keep the theory light and the practice solid—focusing on core points that are guaranteed to appear on the exam through past questions, without the need for complex background knowledge.

Creating your own data analysis portfolio with Google Antigravity CLI harness engineering and vibe coding: data collection, analysis, reporting, dashboard creation, and task automation. Even if you are new to data collection, once you master the principles, prompt engineering, and how to use Antigravity, you can perform data collection, analysis, visualization, reporting, and dashboard creation just like a data analyst. From Python data collection to report writing learned with Antigravity IDE and CLI. Prompt writing and error resolution methods for foolproof data collection and analysis.

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.

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.

ADsP Summary + Past Exam Solutions. Reflects August 2025 46th Exam! (Continuously Updated!)

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.