DataLyft Career Tracks combine live tutoring, realistic exercises, complete projects and feedback across analytics, engineering and automation.
Compare each track by its outcome, starting level and practical focus.
12 weeks · Live cohort programme
Turn raw business data into clear analysis, reports and recommendations.
People who are completely new to data and need a structured starting point.
SQL · Excel · Power BI · Python
View programme16 weeks · Live cohort programme
Move, transform and test data through maintainable analytical pipelines.
Learners who are already comfortable with SQL or Python.
Python · SQL · dbt · Airflow
View programme10 weeks · Live cohort programme
Identify useful automation opportunities and build practical data-enabled workflows.
People who want to automate repetitive reporting or operational work.
Python · APIs · AI tools
View programmeThese are starting points, not absolute rules. Explore the detail pages before deciding.
A good place to start may be Data Analytics, where the learning path begins with foundational analysis.
Data Analytics can help you deepen your analysis foundations and build clearer reports and dashboards.
Data Engineering may be a useful next step if you want to work on pipelines, transformations and warehouses.
AI & Data Automation may fit if you want to connect Python, APIs and applied AI to practical workflows.