This course, Coursera - Data Analysis with Python Specialization, provides you with the necessary tools and knowledge for a Data Scientist and Analyst. You will be taught about different procedures used in the field, which will help you when you face actual data issues.
The major topics you will cover while in the class include Classification, Regression, Clustering, Dimensionality Reduction, and Association Rules. You will also learn how to create good workflows that include elements such as data cleaning, feature extraction, and model selection, among others, thus developing good practice in data analysis.
Thus, after finishing this course, “Coursera - Data Analysis with Python Specialization,” you will acquire hands-on experience in applying algorithms and tools, namely K-Means Clustering, PCA, DBSCAN, and Scikit-Learn. Using the Bayesian approach and Support Vector Machines, you will also learn concepts such as Ensemble Learning and advanced Statistics. Also, you’ll sharpen your skills in planning data analysis initiatives and projects, extracting patterns from the data, and applying your knowledge of association rule learning.
Coursera - Data Analysis with Python Specialization Table of Contents:
- Classification Analysis (Course 1 - 38 hours)
- Regression Analysis (Course 2 - 40 hours)
- Clustering Analysis (Course 3 - 37 hours)
- Association Rules Analysis (Course 4 - 22 hours)
- Data Analysis with Python Project (Course 5 - 18 hours)
Who is this course for?
- Aspiring Data Scientists
- Employees who are getting promoted to new analytical positions
- Whosoever wishes to grasp the methods and strategies used in data analysis.
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