Every module. In order. Free.

The tested professional baseline every data role requires before a specialization.

1. 01

   Python Foundations

   Programs you can trust

   10h
2. 02

   Tabular Python

   NumPy and pandas

   10h
3. 03

   SQL Foundations

   Questions into queries

   10h
4. 04

   Git & GitHub

   Version everything

   6h
5. 05

   Command Line

   Live in the terminal

   5h
6. 06

   Statistics Basics

   Think in distributions

   10h
7. 07

   AI Literacy

   Work with the machines

   6h
8. 08

   Foundation Readiness Capstone

   Evidence before specialization

   14h

Build the infrastructure. Design robust pipelines, manage massive datasets, and ensure data quality and accessibility.

1. 01

   Local Data Platform

   Docker, PostgreSQL, and ingestion

   10h
2. 02

   Data Modeling

   Dimensional modeling

   12h
3. 03

   dbt

   Data build tool

   12h
4. 04

   Workflow Orchestration

   Airflow operations

   12h
5. 05

   Cloud & Infrastructure as Code

   GCP, Terraform, security, and cost

   14h
6. 06

   Spark — Advanced

   Distributed compute

   16h
7. 07

   Real-time Streaming

   Kafka

   16h
8. 08

   Production Readiness Capstone

   Prove the whole platform works

   16h

Turn ambiguous questions and messy data into trustworthy, decision-ready products.

1. 01

   Exploratory Data Analysis

   Interrogate the data

   10h
2. 02

   Data Visualization

   Matplotlib, Seaborn

   10h
3. 03

   Dashboard Design

   Interfaces for decisions

   10h
4. 04

   Data Storytelling

   Insight to action

   8h
5. 05

   Governed BI Delivery

   Power BI from model to release

   12h
6. 06

   AI-Assisted Analysis

   Analyst + LLM

   8h
7. 07

   Decision Intelligence Capstone

   Evidence to action

   18h

Frame, validate, deploy, and responsibly operate predictive systems whose complexity is earned by evidence.

1. 01

   ML Fundamentals

   Supervised learning core

   14h
2. 02

   Feature Engineering

   Signal from raw data

   10h
3. 03

   Model Building & Evaluation

   Beyond accuracy

   12h
4. 04

   Experimentation & A/B Testing

   Causal by design

   12h
5. 05

   Model Deployment

   Models as services

   12h
6. 06

   Advanced Modeling

   Complexity must earn its place

   18h
7. 07

   Responsible Production Capstone

   From model to decision system

   16h

Turn a validated model into a tested, deployable, observable production system with a safe path for continuous improvement.

1. 01

   Experiments & Reproducible Pipelines

   From notebook to repeatable run

   14h
2. 02

   CI/CD for ML

   Automate the path to prod

   14h
3. 03

   Serving & Safe Release

   Ship without gambling production

   14h
4. 04

   Monitoring & Incident Response

   Know, decide, recover

   14h
5. 05

   Continuous ML Platform Capstone

   Operate the whole lifecycle

   18h

Build useful AI products. LLM orchestration, RAG systems, agents, and production AI architecture.

Curriculum preserved. Release held until the complete data and MLOps ecosystem is ready.