Data Analysis with Python CognitiveClass
Enrollment in this course is by invitation only
About This Course
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! Topics covered: Importing Data sets
 Cleaning the Data
 Data frame manipulation
 Summarizing the Data
 Building machine learning models
 Building data pipelines
 Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an opensource library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another opensource library, scikitlearn, and we will use some of its machine learning algorithms to build smart models and make cool predictions.
Recommended skills prior to taking this course
Course Syllabus
Module 1  Importing Datasets
Module 2  Cleaning the Data
 Learning Objectives
 Understanding the Domain
 Understanding the Dataset
 Python package for data science
 Importing and Exporting Data in Python
 Basic Insights from Datasets
 Identify and Handle Missing Values
 Data Formatting
 Data NormalizationSets
 Binning
 Indicator variables
 Descriptive Statistics
 Basic of Grouping
 ANOVA
 Correlation
 Correlation 2
 Simple and Multiple Linear Regression
 Model Evaluation Using Visualization
 Polynomial Regression and Pipelines
 Rsquared and MSE for InSample Evaluation
 Prediction and Decision Making
 Model Evaluation
 Over Fitting, Under fitting and Model Selection
 Ridge Regression
 Grid Search
 Model Refinement
General Information


 This course is free.
 It is selfpaced.
 It can be taken at any time.
 It can be audited as many times as you wish.
 There is only ONE chance to pass the course, but multiple attempts per question
 Python programming, Statistics

Requirements
 Python programming
Course Staff
Mahdi Noorian Ph.D.
Mahdi Noorian is a Postdoctoral Fellow at the Laboratory for Systems, Software and Semantics (LS3) of the Ryerson University. He holds a Ph.D degree in Computer Science from University of New Brunswick. As a Data Scientist, he is interested in application of machine learning, data mining, optimization, and semantic data analysis for big data to solve the realworld problems.