Python Programming
- Introduction to Python programming tailored for data engineering tasks.
- Data manipulation and preprocessing with pandas and NumPy.
- Basic data visualization techniques using libraries like Matplotlib and Seaborn.
Foundations of Data Engineering
- ntroduction to data engineering principles and practices.
- Overview of data storage solutions such as relational databases (SQL) and NoSQL databases.
- Building ETL pipelines with Python for data processing.
Big Data Technologies with Python
- Utilizing Python-based big data processing frameworks like PySpark.
- Hands-on experience with distributed computing and data processing using PySpark.
- Introduction to parallel processing and optimization techniques with Python.
Machine Learning for Data Engineers
- Basics of machine learning algorithms implemented in Python.
- Integrating machine learning models into data engineering pipelines using scikit-learn.
- Feature engineering for ML model training with Python-based tools.
Deep Learning for Data Engineers
- Introduction to deep learning using Python frameworks like Pytroch.
- Building neural networks and deep learning models for data engineering tasks.
- Training deep learning models for tasks like anomaly detection and predictive maintenance.
Data Pipeline Orchestration with Python
- Workflow management with Python-based tools like Apache Airflow.
- Designing and scheduling complex data workflows using Python scripts.
- Deployment and monitoring of data pipelines using Python monitoring libraries
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