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AdvancedData Analytics8 weeks
Certificate IncludedCertificate EligibleUcanly certificate

Data Analytics with Python: Advanced

From analyst to analytics architect: analytics engineering, big data pipelines, causal inference, advanced forecasting, and production Generative AI analytics.

Duration
8 weeks
Level
Advanced
Content
48 lessons
8 modules · 16 h 32 min
Certificate
Included
On completion
Access
Fee by email
Or take the free aptitude test

What you'll learn

Architect a modern data stack with dimensional modelling, dbt, and semantic layers for single source of truth metrics
Process big data at scale with Polars, DuckDB, and PySpark, and orchestrate pipelines with Airflow
Build automated data quality testing with Great Expectations and enforce governance, access, and privacy at scale
Apply causal inference, quasi experiments, and uplift modelling to move from reporting to genuine decisions
Build hierarchical, multi series, and gradient boosted forecasting systems with prediction intervals
Build production RAG and governed semantic layers for text to SQL over enterprise data
Build multi agent analytics systems with LangGraph and automated insight and narrative generation
Run LLMOps in production: rigorous evaluation, numerical accuracy guardrails, and cost optimization
Architect and launch a scalable, production grade analytics platform with a semantic layer, an AI agent, and full CI/CD

Who this course is for

  • Intermediate level graduates ready to architect production grade analytics platforms
  • Working data analysts preparing for senior analyst, analytics engineer, or analytics architect roles
  • Analysts who want deep, hands on experience with causal inference and production Generative AI
  • Anyone targeting senior level analytics architecture and executive case interviews

Skills you'll gain

Advanced Data AnalyticsAnalytics ArchitectAnalytics EngineeringdbtDimensional ModellingSemantic LayerAirflowPySparkPolarsDuckDBSnowflakeBigQueryData QualityData GovernanceCausal InferenceUplift ModellingAdvanced ForecastingPrescriptive AnalyticsProduction RAGText to SQLLangGraphLLMOpsSenior Data Analyst

This course includes

Live mentor led Ucanly sessions plus self paced recorded content
Ucanly mock analytics architecture and executive case interviews and senior portfolio review
Resume and profile audit with placement guidance
Production style projects in every module
Lifetime access to course materials and future updates
Advanced Certificate of Completion from Ucanly

Course content

8 modules · 48 lessons · 16 h 32 min

Analytics engineering and data architecture, big data performance and automated pipelines, data quality governance and trust, causal inference and decision science, advanced forecasting and optimization, advanced Generative AI for analytics, LLMOps and cost engineering, and a capstone production analytics platform.

Requirements

  • Completion of the Intermediate level, or hands on experience delivering analysis, dashboards, and experiments on real business data
  • Comfort with Python, SQL, and basic cloud or deployment concepts
  • A computer or cloud environment capable of running larger scale data processing

About this course

This is the final stage of the Ucanly Data Analytics with Python track, where analysts become analytics architects. Built for practitioners with hands on experience delivering analysis, dashboards, and experiments on real business data, this program goes deep into analytics engineering with dbt and dimensional modelling, big data processing with Polars, DuckDB, and PySpark, and rigorous data quality and governance with Great Expectations. You will move from reporting into decision science with causal inference, quasi experiments, and uplift modelling, and build advanced forecasting systems with hierarchical and gradient boosted time series models. On the Generative AI side, you will build production RAG over enterprise data, governed semantic layers for text to SQL, multi agent analytics with LangGraph, and full LLMOps covering evaluation, guardrails, and cost optimization. You will graduate having architected and launched a scalable, production grade analytics platform with automated pipelines, a governed semantic layer, an executive decision system, and an AI analytics agent, deployed with full CI/CD.

Earn a Ucanly certificate

Complete this course to earn a Ucanly certificate with its own page and QR code. Save it as a PDF, share its link, or add it to the certifications on your LinkedIn profile.

Certificate IncludedCertificate EligibleUcanly certificate

Frequently asked questions

It is recommended, but hands on experience delivering analysis, dashboards, and experiments on real business data is sufficient to start.

Yes, you will process data at scale with Polars, DuckDB, and PySpark, and orchestrate pipelines with Airflow.

DAGs and confounding, quasi experiments like difference in differences and matching, uplift modelling and treatment effects, and multi armed bandit based experimentation.

A scalable, production grade analytics platform with automated pipelines, a governed semantic layer, an executive decision system, and an AI analytics agent, deployed with full CI/CD and mentored end to end by Ucanly.