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[Practical AI Data Analysis for Professionals] Data Analysis with Claude Code Even Without Knowing How to Code

You no longer need to study SQL or Python for data analysis. While everyone else is using Claude Code, are you still stuck with old-fashioned methods? Many companies are already building AI Data Analyst assistants using Claude Code to ask the questions necessary for immediate service and business growth, instantly generating everything from analysis to insights and execution strategies. As a current Tech Lead who also took on a PO role, I needed growth data analysis, and I significantly improved the speed of decision-making and execution by applying this method to actual work. This course provides question templates for using Claude Code in the field and guides you through funnel, conversion, and churn analysis to derive actions, so you can apply it to your work immediately just by following along.

(1.0) 1 reviews

11 learners

Level Beginner

Course period Unlimited

Growth Hacking
Growth Hacking
Performance Marketing
Performance Marketing
Service Planning
Service Planning
Data literacy
Data literacy
claude
claude
Growth Hacking
Growth Hacking
Performance Marketing
Performance Marketing
Service Planning
Service Planning
Data literacy
Data literacy
claude
claude

What you will gain after the course

  • You can identify conversion/churn issues based on your own service data and derive actionable strategies.

  • You can create a professional routine that extracts analysis, insights, and actions within one minute using just a single-line question.

  • You can extract the necessary data yourself without depending on the development team, allowing for rapid experiment and improvement cycles.

This course teaches non-developers how to analyze their own data at work, even if they don't know a single line of code. This is not a course for studying data analysis, so please do not apply if it's not what you're looking for. This is a course for practical business use.


Instead of taking forever when assigned a data analysis task,
this is for those who need to quickly analyze urgent issues and respond rapidly to the market.

Even in the middle of the night! If you have something you're curious about, this is how to utilize an AI analyst who provides analysis results immediately. This is the actual method I used as a PO to grow the service.

AI data analysis is already being done like this in the field

These days, the way data is analyzed in the field has changed significantly.

The time spent directly handling SQL or Python as in the past is decreasing,
and a trend is emerging where AI is utilized to increase analysis speed
while focusing more on interpreting results and execution strategies.

In many teams already:

  • Creating analysis drafts with AI and

  • Automating the necessary data organization and

  • They are even receiving help with organizing insights.

So to be honest,
if you continue to do all the analysis manually by yourself,
there is a high possibility that you will fall behind in the speed competition.


What companies truly want from data analysis

In the end, there is only one thing the company wants.

👉 Rapid growth of services and business

That is why these questions keep coming up:

  • Why do they sign up but not proceed to payment?

  • Where do users drop off the most?

  • Based on the ROAS for the last 7 days, what action should we take right now?

The process of answering these questions is data analysis.

And the important thing is:

👉 Reporting faster
👉 Creating more persuasive insights
👉 And connecting them to immediately actionable strategies

This ultimately leads to growth.


The core of this lecture: Creating an AI analysis assistant

In this course, we focus not only on analysis methods but also on creating an AI analysis assistant to help you.
We provide data from actual products, and you will extract data directly from the DB and save it as a CSV file.

For those in HR, Finance, or Sales, simply download your own Excel data as a CSV file and just follow the instructions in the lecture.

So you:

👉 Business Judgment
👉 Execution Strategy Design
👉 Setting Growth Direction

You can focus on higher-level tasks like these.


This is how the actual workflow will change

Not only service data, but also data generated from business such as HR, logistics, and inventory:

Data Organization → AI Assistance
Determining Analysis Direction → Organizing Together with AI
Summarizing Insights → Automated Support up to Report Format

As a result:

  • Reporting speed becomes faster and

  • Analysis quality improves and

  • Feedback from superiors improves, and

  • A structure that leads all the way to execution is created.

After taking the course

“We are now able to apply things to the market quickly.”
“Analysis speed has definitely become faster.”
“Let’s execute the strategy immediately.”


What you will actually gain from the lecture

You will learn how to work with AI.

For example:

👉 Which data to collect to help with growth
👉 What questions to ask in the current situation
👉 How to create immediately actionable insights
👉 A workflow that naturally leads to a completed report

In other words, it is a part that is closer to
decision-making capabilities where analysis can be utilized immediately.


We provide practice data and an analytical environment identical to actual work.

The lecture focuses more on practice than theory.

  • Provides actual commerce data and DB-based practice (No SQL knowledge required)

  • 30 practical question templates provided

  • Create your own AI analysis assistant

  • Guide on how to apply to actual work while considering security

After following along with a practice session once, people often say things like this:

👉 “I heard that I’m doing a great job.”
👉 “Since the AI handles the analysis, I now have time to make decisions.”
👉 “It’s become clear what kind of data I need to collect.”
👉 “I can see the questions that are necessary for our company.”


This is especially well-suited for these types of people:

  • PM / Service Planner

  • Performance Marketer

  • Startup operators

  • Members of organizations without a data team

  • Jobs with heavy reporting and analysis tasks

  • Job seekers who need a data analysis portfolio

They all have one thing in common:

👉 Those who want to leave repetitive tasks to AI
👉 and focus on judgment and execution.


The experience of changing your work speed

For example, consider a situation like this.

I suddenly had a question late at night and asked it:

  • Data analysis starts immediately and

  • Insights are organized and

  • Even with the execution strategy organized

  • Ready for execution the very next day.

This is how data is utilized these days.


What you complete by following the lecture => Can be applied to your service immediately

You will build your own AI data analysis assistant
based on Claude Code.

  • Available on both Windows / Mac

  • Possible even if you don't know programming

  • It is enough if you know how to sign up for a membership and install a program.

After taking this course, you will say:

“Wow~ I should apply this to our service right away.”


Data analysis study vs. AI utilization skills

Is what you need right now necessarily the analysis technique itself?

Or:

👉 Is it about analyzing faster with the help of AI,
👉 creating execution strategies,
👉 and improving the quality of your reports?

This course focuses on the latter.

Because AI is not a tool intended to replace your work,
but a tool to help you do your work better.


Introduction of the Creator (Current Tech Lead / PO)

As a working data analyst,

Data was available, but the execution speed was slow,
and the analysis results did not lead to decision-making.

So the method I created is:

  • Question-oriented analysis structure

  • Data flow that leads to execution

  • Analysis system based on practical work templates

While applying this to our service:

  • Improved decision-making speed

  • Increased experiment execution speed

  • Establishing a Data-Driven Growth Framework

I have experienced the effects firsthand.

This lecture is a summary of that process.



Recommended for
these people

Who is this course right for?

  • Startup CEOs or solo operators who aren't seeing sales growth but don't know where the problem lies.

  • Marketers and growth managers who feel self-conscious about having to make requests to the developer or data team every time.

  • Service operators who have low sign-up and conversion rates but have never used data to identify the cause.

  • Analysts or beginners who want to extract metrics from a database and make decisions immediately, without needing SQL or Python.

  • PMs/POs who need to conduct funnel (AARRR) analysis but don't know where to start

  • A manager who is running ads but doesn't know what the problem is because sales aren't increasing.

  • Those who wish to get a job or change careers in product marketing or growth marketing

Need to know before starting?

  • Someone who knows how to sign up and install programs.

Hello
This is crocro

We share technical know-how used in the field.

 

Curriculum

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16 lectures ∙ (34min)

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