EulerFoldPython Data Science: Expert Level
“A 4-week intensive roadmap designed to master production-grade data science, encompassing advanced statistical modeling, robust ML pipelines, model interpretability, and scalable data engineering using Python.”
Module 1: Advanced Python for Data Engineering & Performance
By the end of this module you will be able to design and implement efficient data ingestion and transformation pipelines using advanced Python features and data structures, optimizing for performance.
Module 2: Advanced Statistical Modeling & Machine Learning
By the end of this module you will be able to apply advanced statistical modeling techniques, implement various machine learning algorithms from scratch, and critically evaluate model performance and assumptions.
Module 3: MLOps & Production-Grade ML Pipelines
By the end of this module you will be able to build, deploy, and monitor end-to-end machine learning pipelines, incorporating MLOps best practices for reproducibility, versioning, and scalability.
Module 4: Model Interpretability & Scalable Data Engineering
By the end of this module you will be able to interpret complex machine learning models, ensure fairness and transparency, and apply scalable data engineering techniques for processing and analyzing large datasets.
References
Week 1: Module 1: Advanced Python for Data Engineering & Performance
Week 2: Module 2: Advanced Statistical Modeling & Machine Learning
Week 3: Module 3: MLOps & Production-Grade ML Pipelines
Week 4: Module 4: Model Interpretability & Scalable Data Engineering
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