Learning materials & tool kits
Self-paced, beginner-friendly deep dives — $200 each. Available with or without the full program.
Python
Practical, hands-on Python for any IT role. Covers data types, file I/O, pandas, and writing production-grade scripts used by analysts, engineers, and data scientists alike.
WHAT'S INCLUDED
- 12 structured exercises
- Pandas for data wrangling
- File I/O and error handling
- Real-world project templates
SQL
From basic SELECT statements to advanced window functions. The exact SQL patterns that appear in 80% of technical interviews across Data Engineering, Analytics, and Data Science roles.
WHAT'S INCLUDED
- 200+ practice queries
- Window function deep dive
- Query optimization guide
- Interview cheat sheets
AWS
Build real data pipelines on Amazon Web Services. Covers the complete stack — S3, Glue, Redshift, and Lambda — with hands-on exercises using a real cloud account.
WHAT'S INCLUDED
- S3 + Glue ETL patterns
- Redshift warehouse setup
- Lambda-triggered pipelines
- IAM & security best practices
GCP
Google Cloud for IT professionals. BigQuery, Dataflow, and Pub/Sub — the tools powering analytics at companies like Spotify, Twitter, and Airbnb.
WHAT'S INCLUDED
- BigQuery fundamentals
- Partitioning & clustering
- Pub/Sub streaming setup
- Cost control strategies
Azure
Microsoft Azure for data workloads. Master Synapse Analytics, Azure Data Factory, and Blob Storage — essential for enterprise IT roles in Data, Cloud, and Analytics.
WHAT'S INCLUDED
- Azure Data Factory pipelines
- Synapse workspace setup
- Blob Storage & ADLS Gen2
- Role-based access control
Big Data
Tame large-scale datasets with Apache Spark and Hadoop. Learn distributed processing patterns, RDDs, DataFrames, and how to design systems that scale.
WHAT'S INCLUDED
- Spark DataFrames & RDDs
- HDFS architecture guide
- Hive & HBase overview
- Performance tuning patterns
DevOps
Automate your data pipelines with CI/CD, Docker, and Kubernetes. Build the operational skills that separate junior engineers from senior ones.
WHAT'S INCLUDED
- GitHub Actions workflows
- Docker for data pipelines
- Terraform fundamentals
- Monitoring & alerting setup
AI & ML
An engineer's guide to machine learning — not the math, but the pipelines. Feature engineering, model serving, and integrating ML into data workflows.
WHAT'S INCLUDED
- scikit-learn for engineers
- Feature store patterns
- Model deployment with FastAPI
- Intro to MLflow & tracking
Java
Core Java for data-focused developers. Understanding Java is key to working with Spark, Kafka, and Flink — this kit covers the essential patterns you actually need.
WHAT'S INCLUDED
- Java fundamentals for data
- Collections & streams API
- OOP concepts applied
- Guided reference exercises
Cybersecurity
Security fundamentals every IT professional needs. Protect pipelines, manage secrets, understand data governance, and build systems that compliance teams won't reject.
WHAT'S INCLUDED
- Secrets vault & .env patterns
- Encryption at rest & transit
- Access control design
- Compliance audit checklist
Reading is great. Building is better.
Apply what you've learned with structured mentorship from the QGTM cohort.