Data Analysis with Python Specialization

Launch your career in Data Science & Data Analysis. By mastering the skills and techniques covered in these courses, students will be better equipped to handle the challenges of real-world data analysis.

Instructor: Di Wu

What you'll learn

  •   Describe and define the fundamental concepts and techniques used in Data Analysis.  Identify the appropriate techniques to apply.
  •   Compare and contrast different Data Analysis techniques, including Classification, Regression, Clustering, Dimension Reduction, and Association Rules
  •   Design and implement effective Data Analysis workflows, including data preprocessing, feature selection, and model selection

    • Skills you'll gain

  •   Supervised Learning
  •   Machine Learning
  •   Machine Learning Methods
  •   Data Mining
  •   Regression Analysis
  •   Scikit Learn (Machine Learning Library)
  •   Anomaly Detection
  •   Data Analysis
  •   Statistical Analysis
  •   Feature Engineering
  •   Statistical Methods
  •   Analytics

    • Specialization - 5 course series

    The "Data Analysis Project" course empowers students to apply their knowledge and skills gained in this specialization to conduct a real-life data analysis project of their interest. Participants will explore various directions in data analysis, including supervised and unsupervised learning, regression, clustering, dimension reduction, association rules, and outlier detection. Throughout the modules, students will learn essential data analysis techniques and methodologies and embark on a journey from raw data to knowledge and intelligence. By completing the course, students will be proficient in data analysis, capable of applying their expertise in diverse projects and making data-driven decisions.

    Regression Analysis

    Clustering Analysis

    Association Rules Analysis

    Data Analysis with Python Project

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