What you will learn in the Advanced Python Data Science Testing Distribution Lo094032 Course
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Design end-to-end data science pipelines for production environments
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Understand supervised and unsupervised learning algorithms
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Create data visualizations that communicate findings effectively
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Master exploratory data analysis workflows and best practices
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Implement data preprocessing and feature engineering techniques
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Work with large-scale datasets using industry-standard tools
Program Overview
Module 1: Data Exploration & Preprocessing
Duration: ~3 hours
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Guided project work with instructor feedback
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Review of tools and frameworks commonly used in practice
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Discussion of best practices and industry standards
Module 2: Statistical Analysis & Probability
Duration: ~3-4 hours
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Discussion of best practices and industry standards
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Review of tools and frameworks commonly used in practice
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Assessment: Quiz and peer-reviewed assignment
Module 3: Machine Learning Fundamentals
Duration: ~1-2 hours
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Introduction to key concepts in machine learning fundamentals
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Discussion of best practices and industry standards
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Case study analysis with real-world examples
Module 4: Model Evaluation & Optimization
Duration: ~2 hours
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Hands-on exercises applying model evaluation & optimization techniques
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Discussion of best practices and industry standards
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Review of tools and frameworks commonly used in practice
Module 5: Data Visualization & Storytelling
Duration: ~2-3 hours
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Assessment: Quiz and peer-reviewed assignment
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Hands-on exercises applying data visualization & storytelling techniques
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Review of tools and frameworks commonly used in practice
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Introduction to key concepts in data visualization & storytelling
Module 6: Advanced Analytics & Feature Engineering
Duration: ~4 hours
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Interactive lab: Building practical solutions
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Assessment: Quiz and peer-reviewed assignment
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Discussion of best practices and industry standards
Job Outlook
- Advanced Python skills for data science, testing, and distribution are highly in demand as organizations build scalable and reliable data-driven applications.
- Diverse career opportunities including roles such as Data Scientist, Python Developer, Machine Learning Engineer, and Data Engineer, with salaries ranging from $80K – $150K+ globally depending on experience and expertise.
- Strong demand for professionals who can write production-ready Python code, test data pipelines, and deploy scalable data science solutions.
- Ideal for developers and data scientists looking to enhance their Python skills for real-world applications.
- Advanced Python skills support career growth in data science, software engineering, AI development, and MLOps.
- Increasing adoption of Python in data-driven systems continues to drive demand for professionals with advanced coding and deployment expertise.
- Companies value candidates who can ensure code reliability, automate testing, and manage package distribution effectively.
- These skills also open doors to startups, consulting, freelancing, and building scalable data products.
