Description
Course Content
Setting Up Your Data Environment
Learn how to create your own data environment using free tools so you can store, access, and manage data without relying on others.
Data Cleaning and Preparation for Analysis
Master how to take raw, messy data and transform it into structured, reliable datasets ready for analysis.
Structuring Data for Analysis
Organize data into proper tables and relationships so it can be efficiently queried and modeled.
SQL — Accessing and Exploring Data
Learn how to retrieve, join, filter, and aggregate data to answer real business questions.
Thinking Like a Data Scientist
Move beyond reporting numbers and learn how to break down performance and identify key drivers.
Data Exploration and Statistical Insight
Use practical statistical tools to quickly identify patterns, trends, and anomalies.
Python for Data Analysis and Automation
Automate data cleaning, manipulation, and workflows to eliminate repetitive work.
Designing Analytical Models and Workflows
Learn how to structure analysis from raw data to insight to decision in a consistent way.
Advanced Excel for Modeling and Forecasting
Build forecasting models and analytical frameworks that stakeholders can use and trust.
Automating Reporting and Analysis
Create workflows that run automatically, from data extraction to final reporting.
Dashboard Design and Data Visualization
Design and build dashboards in Power BI and Looker Studio that clearly communicate insights.
Working in Modern Analysis Environments
Use Jupyter Notebooks and Google Colab to structure and share your analysis.
Version Control for Analysts
Learn how to manage and track your work using GitHub so nothing is lost and everything is reproducible.
Data Scraping and APIs
Expand your data sources by learning how to collect external data programmatically.
Knowledge Graphs and the Future of Data
Understand how AI systems structure and use data so you can stay ahead of where things are going.