Course · Data & Analytics

AI Analytics & Reporting

Analyze data with AI tools — ChatGPT for insights, Python for processing, automated dashboards, and smart reporting.

  • 1 free lesson every day
  • Verifiable certificate on completion
  • From Data-Curious up to AI Fluent
  • Personalized to you

Start learning today

Free to start — your first lesson is 5 minutes.

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Looking for AI Analytics & Reporting for your business?

Learn in your language

AI analytics, explained clearly in 15 languages

The interface, Kai’s guidance, and every explanation adapt to your language. Focus on SQL, Python, dashboards, and reporting—not translating technical terms.

English Deutsch Srpski Hrvatski Українська Български Română Georgian Español Français Türkçe Polski Italiano Tiếng Việt Português Русский

Why other learning paths stall

You studied the tools. The data still feels difficult.

Tutorials never became real analysis

You followed SQL, Python, or dashboard demos but struggled when your own dataset was messy and the business question was unclear.

AI gave you answers you could not trust

ChatGPT produced code, charts, or conclusions quickly. Checking its logic, assumptions, and metrics took much longer.

Generic courses repeated the wrong material

Beginner content covered concepts you knew, while advanced lessons skipped the gaps that were actually holding you back.

Dashboards did not drive decisions

You built charts and reports, but stakeholders still asked what changed, why it mattered, and what they should do next.

Your path to mastery

Start at your real level. Keep progressing to AI analytics mastery.

A short placement skips what you already know. From there, focused lessons build your ability to query, analyze, automate, govern, and communicate data with AI.

Where are you today?

Today
1 month
Mastery
Data-CuriousQueryingAnalyzingAutomatingGoverningAI Fluent

Today

You have data questions but rely on others to query, clean, or explain the numbers.

In 1 month

With a daily five-minute lesson, you can move into Querying: using core data, SQL, spreadsheet, and statistics concepts to answer defined questions.

At mastery

You can design, review, and communicate governed AI analytics workflows from raw data to decision-ready reporting.

Find the gaps between your current workflow and mastery

Take the placement, skip familiar material, and begin with the skills that need attention.

How Kampster works

A direct route from your current level to verified capability

You do not restart from lesson one or finish after watching a fixed playlist. The course keeps adapting until you reach the top of the proficiency scale.

Find your real level

A roughly two-minute placement checks what you can already do across data, AI-assisted analysis, reporting, and governance. Demonstrated skills are skipped.

Practice for five minutes with Kai

Complete interactive lessons shaped around your gaps, goals, and pace. Ask Kai questions, inspect analyses, and rehearse decisions without being rushed.

Verify what you can do

Your level is assessed through demonstrated skills. Reach mastery to earn a verifiable, shareable certificate based on capability—not watch time.
Example course certificate

Inside each lesson

Practice the decisions analysts make with AI

Every activity connects methods to realistic data work, from cleaning a CSV to defending an executive recommendation.

Worked analyses, end to end

Step through a business question from SQL query and Python cleanup to visualization, interpretation, and stakeholder summary.

Interpret-the-data quizzes

Read tables, distributions, charts, GA4 insights, and AI-generated findings. Decide what the evidence supports—and what it does not.

Decision scenarios with Kai

Choose metrics, challenge an AI conclusion, respond to a stakeholder, or decide whether a dashboard is ready to publish.

Method and terminology flashcards

Recall concepts such as joins, variance, semantic layers, data quality checks, agentic workflows, and ROI measurement.

Review before concepts fade

Spaced repetition brings back statistical methods, SQL patterns, governance rules, and reporting principles when you need reinforcement.

Custom lessons for your next task

Create focused practice for a dataset, metric dispute, Python error, dashboard review, or leadership report in about 30 seconds.

Built around your work

The course adapts to what you know, forget, ask, and need

The Kampster engine continuously adjusts your route instead of forcing every learner through the same sequence.

The Kampster engine

Your demonstrated gaps

The placement and lesson checks identify whether you need SQL foundations, stronger interpretation, better automation, or deeper governance.

Your retention pattern

Key methods and definitions return just before you are likely to forget them, with more review where recall is weaker.

Your questions for Kai

Ask why code failed, whether a conclusion is justified, or how to explain a metric. Kai responds patiently and corrects without judgment.

Your analytics context

Examples and custom lessons can reflect your datasets, stakeholders, reporting tools, and the decisions your organization faces.

13 modules · 103 lessons

A full AI analytics curriculum that arrives when you are ready

Move from data and SQL essentials through statistics, pandas, visualization, AI-assisted coding, BI copilots, GA4 reporting, semantic layers, data quality, Oracle Analytics Cloud, storytelling, agentic workflows, governance, and ROI. You see the material your next level requires—not a backlog of homework.

01

Data & SQL Essentials

Query a real dataset with SQL to answer a concrete business question and share the result.

02

Statistics & Spreadsheet Layer

Compute and interpret descriptive statistics in a spreadsheet to summarize a business dataset.

03

Python Data Wrangling

Load, clean, and summarize a CSV dataset using Python and pandas to produce a reproducible analysis script.

04

Python Visualization & EDA

Produce a visual exploratory analysis of a dataset using Python and communicate findings in a short written summary.

05

AI-Assisted Code Generation

Use an LLM to draft, debug, and refine Python analytics code, reducing scripting time by at least half on a real task.

01

Data & SQL Essentials

Query a real dataset with SQL to answer a concrete business question and share the result.

02

Statistics & Spreadsheet Layer

Compute and interpret descriptive statistics in a spreadsheet to summarize a business dataset.

03

Python Data Wrangling

Load, clean, and summarize a CSV dataset using Python and pandas to produce a reproducible analysis script.

04

Python Visualization & EDA

Produce a visual exploratory analysis of a dataset using Python and communicate findings in a short written summary.

05

AI-Assisted Code Generation

Use an LLM to draft, debug, and refine Python analytics code, reducing scripting time by at least half on a real task.

06

BI Dashboards & Copilots

Build and publish an interactive BI dashboard using an AI-assisted tool and present it to a simulated stakeholder.

07

GA4 AI Reporting

Configure and interpret GA4 AI-generated insights for a digital property and extract a concrete optimization recommendation.

08

Semantic Layer & Metric Governance

Define and enforce a governed metric in a semantic layer tool so that all downstream AI queries use a single consistent business definition.

09

Data Pipeline & Quality AI

Build a lightweight automated data pipeline that uses AI to flag quality issues before data reaches a dashboard.

10

Oracle AI Analytics Cloud

Configure and use Oracle Analytics Cloud (OAC) AI features to generate an executive-ready report from enterprise data.

06

BI Dashboards & Copilots

Build and publish an interactive BI dashboard using an AI-assisted tool and present it to a simulated stakeholder.

07

GA4 AI Reporting

Configure and interpret GA4 AI-generated insights for a digital property and extract a concrete optimization recommendation.

08

Semantic Layer & Metric Governance

Define and enforce a governed metric in a semantic layer tool so that all downstream AI queries use a single consistent business definition.

09

Data Pipeline & Quality AI

Build a lightweight automated data pipeline that uses AI to flag quality issues before data reaches a dashboard.

10

Oracle AI Analytics Cloud

Configure and use Oracle Analytics Cloud (OAC) AI features to generate an executive-ready report from enterprise data.

11

Smart Reporting & Storytelling

Transform a completed data analysis into a stakeholder narrative that drives a decision, using AI to draft and refine the prose.

12

Agentic Analytics Workflows

Design and run a multi-step agentic workflow that executes a full EDA cycle autonomously and delivers a reviewed output.

13

AI Governance & ROI Measurement

Implement a governance checklist for an AI analytics system and calculate and communicate its business ROI to a leadership team.

11

Smart Reporting & Storytelling

Transform a completed data analysis into a stakeholder narrative that drives a decision, using AI to draft and refine the prose.

12

Agentic Analytics Workflows

Design and run a multi-step agentic workflow that executes a full EDA cycle autonomously and delivers a reviewed output.

13

AI Governance & ROI Measurement

Implement a governance checklist for an AI analytics system and calculate and communicate its business ROI to a leadership team.

Your task, turned into practice

Create a custom lesson in about 30 seconds

Type a real scenario and Kai builds focused practice around it. Try: “Help me clean this sales CSV” · “Check my dashboard metric logic” · “Explain this GA4 traffic drop” · “Debug my pandas groupby” · “Draft my executive data story”.

Help me clean this sales CSV

Whatever’s coming up — the lesson exists before your coffee’s ready.

Questions, answered

What to expect from AI Analytics & Reporting

Do I need SQL or Python experience?

No. The placement identifies your starting point. If you are new, you can begin with data, SQL, statistics, and spreadsheet foundations. If you demonstrate those skills, the course skips them.

Is this only about using ChatGPT?

No. You learn how AI supports the full analytics workflow: code generation, Python processing, exploratory analysis, BI dashboards, GA4 insights, data quality, semantic layers, reporting, agentic workflows, governance, and ROI.

How much time should I set aside?

Lessons take about five minutes. A daily habit is roughly 35 minutes per week. You can continue at your own pace, and the course keeps adapting rather than ending after a fixed schedule.

Can Kai help with a real work scenario?

Yes. Kai can answer questions, correct your reasoning kindly, and roleplay stakeholders or review situations. You can also create a custom lesson for a specific scenario in about 30 seconds.

How do you stop me from trusting incorrect AI output?

Lessons repeatedly ask you to inspect assumptions, validate code and metrics, interpret evidence, flag quality issues, and review outputs before they reach a dashboard or decision-maker.

What does the certificate verify?

It reflects assessed skills demonstrated in the course. It is verifiable and shareable, and it is based on capability rather than videos watched or time spent.

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AI Analytics & Reporting leaderboard

See who is leading the course

The live leaderboard recognizes learners progressing toward the highest verified level in AI-assisted analytics and reporting.

B

Biljana

100 / 100

2
Я

Ярик

100 / 100

1
E

Elena

83 / 100

3
4
А
Александра0 / 100
5
B
Bakir0 / 100
6
M
Milena0 / 100
7
B
Bilja0 / 100
8
I
Ivica0 / 100
9
B
Biljana0 / 100
10
S
Smilja0 / 100

Put your current analytics skills to the test

Find your level in about two minutes, skip what you know, and start closing the gaps with Kai.

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