Coursera – Data Analysis with Python Specialization

Coursera – Data Analysis with Python Specialization
English | Tutorial | Size: 545.45 MB


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 pre-processing,
feature selection, and model selection

Skills you’ll Gain:
• Data Clustering Algorithms
• Dimensionality Reduction
• K-Means Clustering
• Principal Component Analysis (PCA)
• Dbscan
• Ensemble Learning
• Linear Regression
• Cross Validation
• Regression
• Scikit-Learn
• Bayesian Statistics
• Logistic Regression
• Support Vector Machine (SVM)
• Classification
• Decision Tree
• Unsupervised Learning
• Machine Learning
• Supervised Learning
• Project Planning
• Data Mining
• Association Rule Learning
• Outlier
• Apriori
• Frequent Patterns
• FP Growth

The Data Analysis specialization will provide a comprehensive overview of various techniques for analyzing data. The courses will cover a wide range of topics, including Classification, Regression, Clustering, Dimension Reduction, and Association Rules. The courses will be very hands-on and will include real-life examples and case studies, which will help students develop a deeper understanding of Data Analysis concepts and techniques. The courses will culminate in a project that demonstrates the student’s mastery of Data Analysis techniques.

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