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 4 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 and Tableau
• Week 4: 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 using n8n and Zapier, 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 does this program entail?

• Spreadsheets: Excel and Google Sheets, pivot tables, lookups, macros
• SQL: joins, window functions, CTEs
• Power BI or Tableau: dashboards, DAX, data modeling
• Python: Pandas, Matplotlib, Seaborn
• Basic Machine Learning: regression, classification, clustering (Scikit-learn)
• Automation: n8n, Zapier, automate reports, alerts, data collection

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 using dbt, a tool every modern data team uses.

What does this program entail?

• dbt (data build tool): transform data in the warehouse, manage tests, docs, incremental models
• Great Expectations: data quality testing in pipelines
• Advanced SQL: window functions, query tuning, indexing, partitioning
• ETL basics: extract from APIs and CSVs, transform, load

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 dbt, ETL basics, and SQL optimization to their toolkit.

Prerequisite

Path 1 or equivalent SQL and Python knowledge.

Outcome

dbt models and Great Expectations suite, automated pipeline, 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 like Airflow, Kafka, dbt, and cloud data warehouses.

Career opportunities and salary expectations

What does this program entail?

• Advanced SQL: window functions, optimization, indexing, partitioning
• Apache Airflow: orchestrate pipelines, retry failed tasks, backfill, monitor
• Apache Kafka: real-time streaming, pub/sub, event-driven architectures
• dbt (advanced): incremental models, testing, documentation, lineage
• BigQuery or Snowflake: cloud warehousing, partitioning, clustering, time travel
• PySpark: distributed processing for large datasets
• Great Expectations: data validation in pipelines
• Terraform basics: infrastructure as code (local backend)
• Airbyte or Meltano: open-source ELT

Who is this for?

Junior developers, IT professionals, analytics graduates, and anyone who wants to build scalable data infrastructure. You should have basic SQL and Python knowledge before starting.

Outcome

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