Learn without fear. Build with confidence.

Why take this pilot?

Data is everywhere, but most people don't know where to start. This pilot gives you a low-risk, low-cost introduction to the core tools and mindset of a data analyst. In just 5 weeks, you'll go from zero coding to building your first dashboard.

What does the pilot entail?

• Week 1: Python basics (variables, loops, functions)
• Week 2: Pandas for data manipulation (cleaning, filtering, grouping)
• Week 3: Visualization with Matplotlib
• Week 4: Tableau Public – dashboards and storytelling
• Week 5: Capstone project – build your first dashboard

Who is this for?

Total beginners, career pivoters, high schoolers waiting to join college, or anyone curious about data but not ready for a full program. No coding experience needed.

Why learn Data Analytics?

Every business needs people who can turn data into decisions. This program teaches you not just to analyze data, but to automate repetitive tasks – a skill most analysts don't have. You'll graduate with a portfolio of 6+ projects and the ability to build dashboards that save teams hours every week.

Career opportunities and salary expectations

What you'll learn

• Extract and transform data: Pull data from multiple sources and prepare it for analysis
• Interactive dashboards: Build dashboards that answer real business questions
• Automation: Automate reports, alerts, and data collection – no more manual copy-paste
• Machine learning fundamentals: Predict customer churn, segment audiences, and forecast sales
• Data-driven thinking: Learn to think like a decision-maker, not just a tool operator

Who is this for?

Career pivoters, business professionals (marketing, finance, operations, HR), and anyone who wants to become a data analyst with an automation edge. No coding experience required – we start from scratch.

Why learn Analytics Engineering?

Analytics engineering is one of the fastest-growing roles in data. It sits between analytics (dashboards, business questions) and engineering (pipelines, infrastructure). This bridge program teaches you to transform raw data into clean, tested, documented models – a skill every modern data team needs.

What you'll learn

• Data transformation: Turn raw data into clean, reliable datasets
• Data quality testing: Ensure accuracy and reliability at every stage
• Advanced SQL: Write optimized queries that run fast and scale
• Automated pipelines: Build data pipelines that run on schedule
• Documentation: Track and document data transformations for your team

Who is this for?

Analytics graduates who want to work closer to data engineering. Analysts tired of messy data and manual transformations. Professionals who want to add modern data stack skills to their toolkit.

Prerequisite

Path 1 or equivalent SQL and Python knowledge.

Outcome

A portfolio of dbt models, a Great Expectations test suite, an automated pipeline, and a QR-verifiable credential.

Why learn Data Engineering?

Data engineers build the infrastructure that powers analytics and machine learning. They are among the highest-paid professionals in tech. This program teaches you to build reliable, scalable pipelines using industry-standard tools and cloud platforms.

Career opportunities and salary expectations

What you'll learn

• Workflow orchestration: Schedule, monitor, and manage complex data workflows
• Real-time streaming: Build pipelines that process data as it arrives
• Cloud data warehousing: Design and manage scalable cloud data warehouses
• Big data processing: Process large datasets efficiently
• Data quality: Ensure data quality at every stage of the pipeline

Who is this for?

Junior developers, IT professionals, analytics graduates, and anyone who wants to build scalable data infrastructure. Basic SQL and Python knowledge required.

Outcome

A portfolio of 4+ pipelines (batch and streaming), Airflow DAGs, a Great Expectations suite, QR-verifiable credential, CV and interview prep, and mock interviews.