Analyzing Data with Python

In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn!

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Created by: Joseph Santarcangelo

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Course Description

LEARN TO ANALYZE DATA WITH PYTHON
Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!
COURSE 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 Evaluation Using Visualization
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

Beginner Level

Time: 5 Weeks - 2-4 hours per week

Instructor Details

Joseph Santarcangelo

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Joseph Santarcangelo is currently working as a Data Scientist at IBM. Joseph has a Ph.D. in Electrical Engineering. His research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition.