Analyzing and Visualizing Data with Python Training

Live Online & Classroom Enterprise Training

Analysing data and Visualisation with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models.

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What is Analyzing and Visualizing Data with Python Training about?

Learners will be exposed to statistics in this course, covering where data comes from, research design, data management, and studying and visualising data. Learners will recognise various forms of data and will be able to imagine, evaluate, and understand summaries for univariate and multivariate data. Learners will also be exposed to the distinctions between probability and non-probability sampling from more significant populations and the concept of how sample estimates change, and how probability sampling may be used to make conclusions about more prominent people.

What are the objectives of Analyzing and Visualizing Data with Python Training ?

Properly identify various data types and understand the different uses for each
Create data visualisations and numerical summaries with Python
Communicate statistical ideas clearly and concisely to a broad audience
Identify appropriate analytic techniques for probability and non-probability samples

Who is Analyzing and Visualizing Data with Python Training for?

This training is for learners who want to get involved in Analysing and data visualisation. Identifying patterns, trends and outliers in large data sets is easier.

What are the prerequisites for Analyzing and Visualizing Data with Python Training?

None

Available Training Modes

Live Online Training

20 Hours

Self-Paced Training

20 Hours

Course Outline Expand All

Expand All

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 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

Module 6: Introduction to Visualization Tools

Introduction to Data Visualization

Edit

CONFIGURE

DUPLICATE

DELETE

Drag to reorder

Introduction to Data Visualization

Introduction to Matplotlib

Basic Plotting with Matplotlib

Dataset on Immigration to Canada

Line Plots

Module 7: Basic Visualization Tools

Area Plots

Histograms

Bar Charts

Module 8: Specialized Visualization Tools

Pie Charts

Box Plots

Scatter Plots

Module 9: Advanced Visualization Tools

Waffle Charts

Word Clouds

Seaborn and Regression Plots

Module 10: Creating Maps and Visualizing Geospatial Data

Introduction to Folium

Maps with Markers

Choropleth Maps

Capstone Project

Who is the instructor for this training?

The trainer for this Analyzing and Visualizing Data with Python Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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