LuxDevHQ Curriculum
Explore our core learning tracks for Data Science & AI, Data Analytics, and Data Engineering.
Data Science & AI Curriculum
- • Python for data analysis and machine learning
- • Statistics, feature engineering, and model evaluation
- • Supervised and unsupervised learning workflows
- • Real-world projects and portfolio development
Data Analytics Curriculum
- • SQL fundamentals to advanced analytical queries
- • Excel and Power BI for business reporting
- • KPI design, dashboard storytelling, and stakeholder communication
- • Case studies for operations, finance, and growth analytics
LuxDevHQ Data Engineering Curriculum (6 Months, Extendable to 7)
Week 1 remains exactly as currently designed at LuxDevHQ. From Week 2 onward, the roadmap below gives a clear, industry-aligned path focused on real projects, production workflows, and graduate employability.
Program Design Principles
- • 24-week baseline: Weeks 1-16 instruction + Weeks 17-24 internship.
- • Optional extension to Weeks 25-28 for remedial and specialization tracks.
- • Learning mix: 70% hands-on, 20% guided instruction, 10% assessments/reflection.
- • Portfolio-first delivery with production-style artifacts and capstone outputs.
Career Outcomes by Graduation
- • Junior Data Engineer
- • Analytics Engineer (entry level)
- • BI/Data Pipeline Developer
- • Data Operations Engineer (entry level)
- • Ability to design, deploy, test, and monitor end-to-end data systems.
Week-by-Week Curriculum (Weeks 2-16)
Internship Phase (Weeks 17-24)
- • Week 17: Internship onboarding, KPI contracts, and architecture proposal.
- • Week 18: Solution architecture, environment provisioning, and stack setup.
- • Week 19: Ingestion from multiple sources with quality gates and quarantine patterns.
- • Week 20: Silver/gold modeling with incremental dbt transformations and tests.
- • Week 21: Streaming extension with Kafka and near-real-time dashboarding.
- • Week 22: Observability, reliability, alerts, and incident response game day.
- • Week 23: CI/CD pipelines for tests, deployments, rollback, and versioning.
- • Week 24: Capstone demo day, technical defense, and portfolio publication.
Optional Extension (Weeks 25-28)
- • Week 25: Remedial SQL, Python, and data modeling clinics.
- • Week 26: Cloud specialization track (Azure, AWS, or GCP).
- • Week 27: Advanced Spark performance tuning and optimization.
- • Week 28: Interview sprint and certification support.
Assessment & Portfolio Framework
Weekly check-ins include labs, mini-quizzes, and code reviews with practical build assessments.
Portfolio artifacts expected by Week 24:
- 1 Power BI dashboard
- 2 SQL case studies
- 2 Python ETL automation projects
- 1 Dockerized data application
- 1 Airflow-orchestrated pipeline
- 1 Kafka/Spark streaming mini-system
- 1 dbt project with tests, docs, and lineage
- 1 Grafana monitoring stack with alerts
- 1 capstone repository with CI/CD and architecture documentation