What is this course
A STRATEGIC UPGRADE
You already know data.
Now learn how AI changes analytics.
Now learn how AI changes analytics.
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02
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Understand AI deeply
Apply it strategically
Build a system
Know what's under the hood of every marketing tool you use so you stop buying wrappers at 10× markup and believing outputs you shouldn't trust.
Learn which tools win which jobs: research, content, paid, lifecycle, analytics, automation. Not opinions - evidence-backed frameworks.
Finish the course with a real AI marketing stack design, including prompts, an evaluation set, an automated workflow, and an ethics policy.
This course teaches you how to use AI across the full analytics workflow: from exploring messy datasets and writing SQL/Python, to building BI agents, governed metrics, reusable tools, and AI-powered data apps.
In 8 practical sessions, you’ll learn how to work with AI safely, validate its outputs, avoid hallucinated analysis, and turn one-time conversations into repeatable analytics systems.
In 8 practical sessions, you’ll learn how to work with AI safely, validate its outputs, avoid hallucinated analysis, and turn one-time conversations into repeatable analytics systems.
Who want to use AI for EDA, SQL, Python, pandas analysis, stakeholder requests, and faster insight generation.
Data Analysts
Product Analysts
Who need to explore product data, validate patterns, explain insights, and build clearer data-backed recommendations.
BI Specialists
Who work with dashboards, metrics, reporting, and want to understand how BI agents and governed metrics can support decision-making.
Business Analysts
Who work between stakeholders and data teams and want to translate business questions into better analysis workflows.
Reporting Specialists
Who regularly answer recurring business questions and want to turn repeated analysis into reusable templates and mini-tools.
Analytics Team Leads
Who want to understand AI risks, governance, validation, and how to introduce AI into analytics processes responsibly.
Who is this for
BUILT FOR DATA PROFESSIONALS WHO WANT TO WORK SMARTER WITH AI
MCP for Analysts
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From AI Conversations to Reusable Software
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From Notebook to Data App
Capstone: AI Analyst Assistant Demo
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08
BI Agents and Governed Metrics
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Coding Assistant for SQL and Python
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AI-Assisted EDA with DIG Framework
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AI-Native Analytics Foundations
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Curriculum
EIGHT SKILLS.
ONE MONTH.
ONE MONTH.
Final Project
YOU DON’T GRADUATE WITH A CERTIFICATE. YOU GRADUATE WITH AN AI ANALYST ASSISTANT.
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AI Analytics Workflow
Tool Stack
Metric Catalog
A clear workflow showing how AI supports data exploration, SQL/Python analysis, validation, and final insight delivery.
A structured prompt system, coding assistant setup, and tool stack for solving analytics tasks more consistently.
A small governed catalog of business metrics with definitions, logic, source tables, and validation rules.
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AI-Assisted Data App
A simple Streamlit app with filters, charts, summary table, AI-generated narrative, source references, and limitations.
05
Safety & Validation Guide
A practical guide showing where AI can be trusted, where outputs must be checked, and how to avoid unsupported claims
In the final session, you’ll present a practical AI-powered analytics workflow or assistant designed for a real data use case.
Start your journey at ACA X
Course Fee: 100,000 AMD
Get up to 100,000 AMD back if you submit your annual tax declaration and have income tax.
Master AI skills.
Build your future.
Lead the change.
Build your future.
Lead the change.
Add your details and proceed to payment.
Secure your spot now
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FREQUENTLY ASKED QUESTIONS
This course is designed for data analysts, BI specialists, reporting professionals, product analysts, business analysts, and analytics team leads who want to use AI in real analytics workflows.
The course covers AI coding assistants, SQL and Python workflows, VS Code, virtual environments, repositories, MCP-capable clients, Postgres, filesystem tools, Metabase, and Streamlit.
You’ll be able to use AI for exploratory data analysis, SQL/Python generation, metric validation, reusable analytics templates, BI agent workflows, and simple AI-powered data apps.
Most AI courses focus on prompts and tools. This bootcamp focuses on real analytics workflows: data quality, validation, reusable systems, governed metrics, BI agents, and practical data products.