Analyzing Data with Python

About

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LEARN TO ANALYZE DATA WITH PYTHON

Learn how to analyze data using Python in this introductory course. You will go from understanding the basics of Python to exploring many different types of data through lecture, hands-on labs, and assignments. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!

What you will learn

• Import data sets, clean and prepare data for analysis, summarize data, and build data pipelines
• Use Pandas, DataFrames, Numpy multidimensional arrays, and SciPy libraries to work with various datasets
• Load, manipulate, analyze, and visualize dataset
• Build machine-learning models and make predictions with scikit-learn

Skills you learn

• Scikit-learn (Machine Learning Library)
• Python (Programming Language)
• Basic Math
• Machine Learning
• SciPy
• Pandas (Python Package)
• Data Visualization
• Data Analysis
• NumPy

Syllabus

Module 1 - Importing Datasets

• Learning Objectives
• Understanding the Domain
• Understanding the Dataset
• Python package for data science
• Importing and Exporting Data in Python
• Basic Insights from Datasets

Module 2 - Cleaning and Preparing the Data

• Identify and Handle Missing Values
• Data Formatting
• Data Normalization Sets
• Binning
• Indicator variables

Module 3 - Summarizing the Data Frame

• Descriptive Statistics
• Basic of Grouping
• ANOVA
• Correlation
• More on Correlation

Module 4 - Model Development

• Simple and Multiple Linear Regression
• Model EvaluationUsingVisualization
• Polynomial Regression and Pipelines
• R-squared and MSE for In-Sample Evaluation
• Prediction and Decision Making

Module 5 - Model Evaluation

• Model Evaluation
• Over-fitting, Under-fitting and Model Selection
• Ridge Regression
• Grid Search
• Model Refinement

Auto Summary

"Analyzing Data with Python" is a foundational course in IT & Computer Science, offered by edX, focusing on data analysis using Python. Over 15 hours, learners will explore numpy for multi-dimensional arrays, pandas for DataFrame manipulation, SciPy for mathematical routines, and scikit-learn for machine learning. Available subscription options include Starter and Professional, catering to beginners eager to enhance their data analysis skills.