Designing a comprehensive syllabus for Data Engineering concepts covering Python, PySpark, SQL, AWS, Apache Airflow, Pandas, Kafka, and real-time projects.
Creating technical content, including study materials, hands-on exercises, and project documentation.
Developing end-to-end content for real-time projects, ensuring practical exposure to industry scenarios.
Setting up a sandbox environment for learners to practice and implement real-time data engineering workflows.
Crafting detailed project records with step-by-step implementation guides.
Ensuring content is aligned with industry standards and best practices.
Continuously updating and enhancing learning materials based on emerging technologies and feedback.