AI · AIC-16

Claude AI for Data Analyst

12 hours 2 days

Last updated 25 Sep 2026

Claude AI for Data Analyst is a 12-hour training course by IT Genius Institute. Every organization now holds a vast amount of data, so the real problem is not a lack of data but turning it into decisions fast enough. Many analytics teams…

Training schedule

No public rounds are open right now — register your interest and we will contact you when the next round opens, or request an in-house session for your team.

Corporate training quote

Every organization now holds a vast amount of data, so the real problem is not a lack of data but turning it into decisions fast enough. Many analytics teams still spend most of their time on repetitive work such as cleaning data, formatting tables, building summary slides and answering the same executive questions every month, leaving less and less time for deep analysis. This course upgrades data-analysis skills with Claude AI, focusing on real work from raw data all the way to insight and decision. Learners cover choosing the right model for the task, designing prompts specifically for data work, setting goals and KPIs with the GQM Framework,

data cleansing and ETL, reproducible analysis with Claude Code and Python/Pandas, designing dashboards that answer business questions, building interactive dashboards and live artifacts, writing executive insight reports, and finally setting up automation with Claude Cowork, Claude Skills and MCP Connectors to systematically cut the time spent on routine reports. The highlight of this 2-day course is using Claude Code together with Python/Pandas so results are reproducible, creating Claude Skills so monthly reports become standardized automated work, and putting data governance and security in place in line with PDPA. All content is taught through workshops using realistic sample datasets and finishes with an end-to-end capstone project

Objectives

Understand the capabilities and limits of Claude AI for data analytics and choose the right model for the task
Design prompts specifically for data work using the Ask, Analyze, Validate, Visualize and Recommend patterns
Understand data thinking and design KPIs with the GQM Framework (Goal, Question, Metric) tied to real organizational goals
Check data quality, plan data cleansing and run ETL with Claude AI systematically
Use Claude Code with Python and Pandas to build reproducible analysis that can be traced and repeated
Design dashboards that answer business questions and build interactive dashboards, HTML reports and live artifacts
Write executive insight reports and a morning insight brief using the what happened, why, what next structure
Apply Claude Cowork, Claude Skills and MCP Connectors to automate routine reporting
Set data governance, security and PDPA practices for using AI with organizational data
Assess the accuracy of AI-generated results and verify the numbers before using them to decide

Who this course is for

Data analysts and business analysts who want to cut reporting time and deepen their analysis
Managers, team leads and executives who read and decide from data regularly
Business owners and SME entrepreneurs who want data-driven decisions without a large data team
Staff in planning, finance, marketing, operations and HR who prepare monthly summary reports
Those interested in becoming a data analyst who want to use AI to accelerate learning

Prerequisites

Basic computer and internet skills
Basic Microsoft Excel or spreadsheet skills such as opening files, managing data and reading data tables
Some experience working with data such as reporting, summarizing or basic analysis gives the most benefit
Understanding of your own team's workflow or business goals to use as a case study during training
No programming or data science background required

Curriculum

Course Details

A 2-day course, 6 hours per day (12 hours in total), delivered as a hands-on workshop with a capstone project. Intermediate level with no programming background required. Content is taught with realistic sample datasets (sales, customer, operations and finance). Learners take home a prompt library, a Claude skill, an executive report template, a dashboard wireframe and a data governance and PDPA checklist.

Day 1: From Raw Data to Trustworthy Analysis

Section 1: Claude AI as Your Data Analyst Assistant

Overview of generative AI for data analytics, choosing the right model (deep reasoning, high-volume analysis, report writing, file generation) and understanding the context window for large data
Uploading and working with many file formats (CSV, Excel, PDF, JSON, images) and using Projects and Project Knowledge to reuse organizational context
Limits of AI on numeric work (hallucination, miscalculation, misreading tables) and a verification mindset before using numbers
Workshop: upload a sample sales dataset and have Claude summarize it while you verify the numbers

Section 2: Prompt Engineering for Data Analysts

A good prompt structure for data work (Role, Context, Data, Task, Format, Constraint) and how it differs from general prompts
Five key prompt patterns: Ask, Analyze, Validate, Visualize and Recommend, plus chain-of-thought and few-shot examples
Building a personal prompt library for monthly recurring work
Workshop: design a prompt set for a report you actually produce, then test and refine it

Section 3: Data Thinking with the GQM Framework

Data analytics thinking that starts from the question not the data, and the levels of analysis: descriptive, diagnostic, predictive and prescriptive
The GQM Framework turning business goals into measurable KPIs, the difference between KPI, metric and dimension, and leading vs lagging indicators
Choosing metrics that do not fool you: vanity metrics, survivorship bias and Simpson's paradox
Workshop: build a GQM Canvas for your own team and have Claude check the KPI logic

Section 4: Data Cleansing and Data Preparation with Claude

Having Claude do data profiling and detect issues: missing values, duplicates, outliers, inconsistent formats and wrong data types
Thai-specific data issues (Buddhist vs Gregorian dates, Thai numerals, extra spaces, inconsistent name spelling) and a data cleaning plan that records what was changed
Lookup, merge, join, grouping and calculated columns via natural language, plus managing a data dictionary
Workshop: clean a real customer dataset from inspection to an analysis-ready file

Section 5: Reproducible Analysis with Claude Code and Python/Pandas

The problem with in-chat analysis (inconsistent results, hard to trace) and the concept of reproducible analysis
Having Claude write Python and Pandas scripts for cleansing and aggregation, and building a small ETL pipeline that reruns every month
Writing data validation checks to catch anomalies automatically and exporting results as Excel with real formulas
Workshop: build a monthly sales analysis script that takes a new file and produces a report instantly

Section 6: Day 1 Wrap-up and Review Workshop

Review the workflow: frame the question, prepare data, analyze and verify, plus common Day 1 mistakes and how to avoid them
Workshop: use the cleaned dataset to answer three business questions from your own GQM Canvas and prepare for Day 2

Day 2: From Insight to Dashboard, Report and Automation

Section 7: Dashboard Design and Insight Generation

Dashboard design principles for executives: a dashboard must answer questions not just show charts, and the strategic, operational and analytical types
Choosing charts that fit the question, visual hierarchy, meaningful use of color and presentation traps that mislead
Having Claude find insights, anomalies, trends and correlations, and distinguishing correlation from causation
Workshop: design an executive dashboard wireframe from the Day 1 dataset

Section 8: Claude Artifact and Interactive Dashboard Prototype

Building an interactive dashboard prototype with Artifact without coding, adding filters, drill down, sorting and search
Creating HTML reports and live artifacts that pull fresh data and refresh, plus tuning the design system to the organization brand
Where Artifact fits and when to move to Power BI or a full BI tool
Workshop: build an interactive dashboard from your wireframe and test it in use

Section 9: Executive Insight Report and Research Workflow

A report structure executives can act on within three minutes using the what happened, why, what next narrative and the Pyramid Principle
Using Claude Research and web search for market and competitor data, with source citation and credibility checks
Workshop: write a one-page executive insight report from your own analysis

Section 10: Automation, Claude Cowork and MCP Connectors

Assessing routine work for what to automate and what always needs a human, and using Cowork to handle many files on the user machine
An overview of MCP (Model Context Protocol) and connecting common connectors (Google Drive, Google Sheets, Gmail, MySQL, PostgreSQL)
Creating a morning insight brief and scheduling daily, weekly and monthly reports
Workshop: set up one automation to summarize data from a folder of report files

Section 11: Claude Skills for Recurring Organizational Reports

The structure of a Skill (SKILL.md, a good description, supporting files) and writing a description so the Skill triggers at the right time
Embedding report templates, calculation standards and business rules into a Skill so the monthly sales report is identical every time
Sharing Skills across the team and an overview of the Claude Agent SDK for full automation (demo)
Workshop: build one Skill for a report you must repeat every month

Section 12: Data Governance, Security and PDPA

Data classification, personal data under PDPA and what must never be entered into AI systems
Risk-reduction techniques: data masking, anonymization, pseudonymization and removing unnecessary columns
Setting connector and MCP permissions on least privilege, and establishing an AI usage policy, audit trail and human in the loop
Workshop: inspect a sample dataset, identify sensitive data and draft your team's practice guidelines

Section 13: Capstone Project and Real-world Adoption

Task: build an end-to-end analysis from a given business dataset or your own team data, setting goals and KPIs with the GQM Framework
Clean and analyze the data to find three key insights, build an interactive dashboard with Claude Artifact and write an executive insight report with recommendations
Present the work and get feedback, plus a first-30-days adoption plan and a learning path (Power BI, SQL, Python for Data Analysis, enterprise AI agents)

Frequently asked questions

Who is Claude AI for Data Analyst for, and what background is needed?

Built for Data analysts and business analysts who want to cut reporting time and deepen their analysis · Managers, team leads and executives who read and decide from data regularly · Business owners and SME entrepreneurs who want data-driven decisions without a large data team Background you should have: Basic computer and internet skills · Basic Microsoft Excel or spreadsheet skills such as opening files, managing data and reading data tables Not sure the fit is right? Talk to our team on LINE @itgenius or call 02-570-8449.

How much does Claude AI for Data Analyst cost and how long does it run?

THB 8,900 (currently THB 8,010 on promotion). The course runs 12 hours. The fee covers course materials, lunch and refreshments throughout. Pay by bank transfer to the company account, confirm it on our payment page, and we can issue the receipt or tax invoice in your company's name.

Do I get a certificate?

Yes. Everyone who completes the course receives a Certificate of Completion from IT Genius Institute. Each certificate carries its own number, and anyone holding that number can verify it online on our certificate page, so you can add it to your portfolio or pass it to HR as evidence of training.

Where does the training take place, and is there an online option?

You can attend onsite at IT Genius Institute or arrange to join online, and we also run it as a private in-house session for your team. Ask about dates and venues on LINE @itgenius or call 02-570-8449.

What if I fall behind or miss a session — can I retake it?

Yes. You may retake the same course free of charge in a later round, under the institute's conditions. Tell our team which course and round you attended, and we will check it and offer you the rounds that still have seats. Ask us on LINE @itgenius or call 02-570-8449.

How do I enrol, or request a quotation for my company?

Enrol online with the registration form on this page. You can register several attendees at once and enter your tax ID and billing address for the tax invoice. Or request a company quotation straight from the quote button. For anything else call 02-570-8449 or reach us on LINE @itgenius.