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.
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

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Regression Analysis (Coursera)

The "Regression Analysis" course equips students with the fundamental concepts of one of the most important supervised learning methods, regression. Participants will explore various regression techniques and learn how to evaluate them effectively. Additionally, students will gain expertise in advanced topics, including polynomial regression, regularization techniques (Ridge, Lasso, and [...]

Clustering Analysis (Coursera)

The "Clustering Analysis" course introduces students to the fundamental concepts of unsupervised learning, focusing on clustering and dimension reduction techniques. Participants will explore various clustering methods, including partitioning, hierarchical, density-based, and grid-based clustering. Additionally, students will learn about Principal Component Analysis (PCA) for dimension reduction. Through interactive tutorials and [...]

Data Analysis with Python Project (Coursera)

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. [...]

Association Rules Analysis (Coursera)

The "Association Rules and Outliers Analysis" course introduces students to fundamental concepts of unsupervised learning methods, focusing on association rules and outlier detection. Participants will delve into frequent patterns and association rules, gaining insights into Apriori algorithms and constraint-based association rule mining. Additionally, students will explore outlier detection methods, [...]