From an overview of artificial intelligence to its history
knsw
Free
Beginner / AI
New
New
I would like to introduce the history of AI and the perspective from which we should view the future of AI.
Beginner
AI
Fundamentals of Data Analysis
This course is a basic course designed to develop data literacy skills using Excel, a software program considered to have the highest recognition and usability among office automation software.
1 learners are taking this course
Level Beginner
Course period Unlimited
Excel
Excel
Data literacy
Data literacy
Excel
Excel
Data literacy
Data literacy
What you will gain after the course
You can understand and explain the concepts of data and data literacy.
Can define data-driven problems and explain data analysis techniques for each type of data.
Can use software for data analysis appropriately for its intended purpose.
You can experience and carry out data analysis tasks.
Do you stop at just reading data in Excel?
Don’t stop at organizing data,
you can uncover the meaning of data only by defining problems and connecting everything from preprocessing to analysis and visualization. Learn the fundamentals of data literacy and the actual analysis process using Excel.
Understand the concepts of data and data literacy, and define the problems to be solved using data yourself.
Experience the process of preprocessing data in Excel and organizing it into a format suitable for analysis.
Find meaning in data through summary analysis, exploratory analysis, predictive analysis, and visualization.
It is natural to find data challenging.
From basic concepts to hands-on analysis tasks, you can build your data skills at your own pace.
Learn everything from data concepts and Excel preprocessing to
summary, exploratory, and predictive analysis, as well as visualization.
Even beginners who only vaguely worked with tables
grow into analysts who define and explain problems with data.
By the end of this course, you will be able to
You can turn vague numbers into questions to analyze.
You will understand the meaning of data and data literacy, and learn how to define problems you encounter at work based on clear criteria. Rather than simply listing numbers such as sales or customer counts, you will develop the habit of organizing for yourself what needs to be checked.
✔️
Move beyond simply looking at data and
learn how to analyze it yourself using Excel.
Practice reading data
and turning it into a problem
After understanding the meaning of data and data literacy, you will learn how to define problems based on data and select appropriate analysis methods for each type. From preprocessing using Excel to summary, exploratory, and predictive analysis and visualization, you will learn the analytical process as one connected workflow.
Turning Excel tables into analytical results
Hands-on practice
After organizing and preprocessing data in Excel, you will create summary tables and exploratory results while carrying out actual analysis tasks. You will compare the purposes of analytical software tools and envision deliverables for use in work or academic settings through examples of data literacy assignments.
Practice materials for each analysis stage and
tool usage guidance
The course is structured around Excel to guide you through data preprocessing and analysis procedures, allowing you to examine the workflows needed for summarization, exploration, prediction, and visualization step by step. You will also explore data analysis software tools and assignment examples together, enabling even beginners to establish criteria for applying them to their own data.
📚
A hands-on journey to refine and analyze data in Excel
We can help solve the concerns of people like these!
📌
College students who are new to Excel
Those who need to organize tabular data for class assignments or team projects but are unfamiliar with distinguishing between data types and extracting only the values they need
Those who want to use Excel’s basic features to organize data and complete simple summaries and visualizations themselves
📌
Entry-level office workers managing work-related data
Those who spend a lot of time preparing reports because of duplicate data and missing values while managing sales records or customer lists in Excel
Those who want to learn the data preprocessing process, transform work data into an analyzable format, and explain the results based on evidence
📌
Aspiring professionals preparing their data utilization skills
Those preparing for a career in data analysis or digital work who want to learn the differences between summary analysis, exploratory analysis, and predictive analysis using real-world data
Those who want to use Excel as an analysis tool to define problems, visualize results in charts, and carry out data-driven tasks
Notes Before Taking the Course
Practice environment
Excel is used on the Windows operating system.
An internet connection and a basic office computer are required.
Prerequisite Knowledge and Important Notes
Learners who are new to Excel can also participate.
Experience creating simple tables and saving files will be helpful.
You will practice by organizing the data yourself.
Learning materials
We organize the key concepts using the lecture slide materials.
It is helpful to prepare data for Excel practice and analysis examples.
Use them for exercises in summarization, exploration, prediction, and visualization.
Recommended for
these people
Who is this course right for?
Data analysis beginner
Excel beginner
Hello
This is knsw
It is a project team composed of professors specializing in AI and software.
We are offering a variety of software-related courses free of charge.
I hope this will be of great help.
Curriculum
All
14 lectures ∙ (7hr 37min)
Published:
Last updated:
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