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Python Programming Level 3: Data Analysis Using Python is unfortunately unavailable

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Python Programming 2: Advanced Programming Techniques

ONLC Training Centers @ 1320 Tower Rd, Chicago, IL

Take your Python programming skills to the next level with advanced techniques in this training course. Learn how to work with classes and objects, inheritance, interact with the operating system, and more. Elevate your programming skills with this advanced Python course.

(7) Advanced 18 and older
$995

2 sessions

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Python Programming Level 1: Intro for Non-Programmers

ONLC Training Centers @ Midwest Plaza South, Oak Brook, IL

Learn Python programming from scratch with this introductory course designed for non-programmers. Gain a strong foundation in Python syntax, file handling, exception handling, and data types. Discover object-oriented concepts, database connectivity, and GUI development.

(7) All levels 18 and older
$1,595

4 sessions

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Python Programming Level 3: Data Analysis Using Python

Master the art of analyzing and visualizing complex data using Python programming. Dive deep into Pandas and Seaborn libraries, and learn how to analyze time-series data and make predictions with regression models. Let your data insights drive informed decisions and unlock new opportunities.

  • All levels
  • 18 and older
  • $1,495
  • Earn 14,950 reward points
  • Price Lock Guarantee
  • Midwest Plaza South, Oak Brook, IL
  • 20 hours & 15 minutes over 3 sessions

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  • $1,495
  • 20 hours & 15 minutes over 3 sessions
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Class Description

Description

What you'll learn in this python class:

The widespread use of the World Wide Web and social media has resulted in the creation and access to enormous amount of data becoming available. The data needs to be analyzed to be able to apply the information in useful ways in many fields including business, science, and social science. The course will teach you to apply your Python programming skills to complex data analysis problems. You will learn to use Pandas for data analysis and Seaborn for data visualization, with JupyterLab as your IDE. Additionally, you’ll learn how to get, clean, prepare, and analyze data, including time-series data. Moreover, you’ll learn to use linear regression models to predict unknown and future values.

Audience
Previous experience with Python programming.

Prerequisites
Basic Python programming experience. You should be comfortable working with strings, lists, tuples, dictionaries loops and conditionals and writing your own functions.

Course Outline

Introduction to Python for data analysis

  • What data analysis is
  • The Python skills that you need for data analysis
  • How to use JupyterLab as your IDE
  • How to split the screen between two Notebooks
  • How to use Magic Commands

The Pandas essentials for data analysis

  • Introduction to the Pandas DataFrame
  • How to examine the data
  • How to access the columns and rows
  • How to work with the data
  • How to shape the data
  • How to analyze the data

The Pandas essentials for data visualization

  • Introduction to data visualization
  • How to create 8 types of plots
  • How to enhance a plot

The Seaborn essentials for data visualization

  • Introduction to Seaborn
  • How to enhance and save plots
  • How to create relational plots
  • How to create categorical plots
  • How to create distribution plots
  • Other techniques for enhancing a plot

How to get the data

  • How to find the data that you want to analyze
  • How to import data into a DataFrame
  • How to get database data into a DataFrame
  • How to work with a Stata file
  • How to work with a JSON file

How to clean the data

  • Introduction to data cleaning
  • How to simplify the data
  • How to find and fix missing values
  • How to fix data type problems
  • How find and fix outliers

How to prepare the data

  • How to add and modify columns
  • How to apply functions and lambda expressions
  • How to work with indexes
  • How to combine DataFrames
  • How to handle the SettingWithCopyWarning

How to analyze the data

  • How to create and plot long data
  • How to group and aggregate the data
  • How to create and use pivot tables
  • How to work with bins
  • More skills for data analysis

How to analyze time-series data

  • How to reindex time-series data
  • How to resample time-series data
  • How to work with rolling windows
  • How to work with running totals

How to make predictions with a linear regression model

  • Introduction to predictive analysis
  • How to find correlations between variables
  • How to use Scikit-learn to work with a linear regression
  • How to plot regression models with Seaborn

How to make predictions with a multiple regression model

  • A simple regression model for a Cars dataset
  • How to work with a multiple regression model
  • How to work with categorical variables
  • How to improve a multiple regression model

Refund Policy

Cancellation / Reschedule by Student

Because we must schedule rooms, ship course materials, assign instructors and provision computer resources well in advance, it is important students alert us ASAP with any cancel/reschedule requests.

Please note the following policies:

  • If requested 16 or more calendar days before the class
    • Cancellation requests made in this timeframe are eligible for refund less 5% cancellation fee.
    • Reschedule requests made in this timeframe will be accommodated if availability exists and will be processed at no additional charge.
  • If requested 15 calendar days or less before the class
    • Cancellation or Reschedule requests made by the student 15 calendar days or less before the class starts will be charged 100% the course fee and are not entitled to a refund.

Substitutions

  • If you are unable to attend your class, a substitute who meets the course prerequisites may attend in your place at no additional charge for the original class title, date and location. If you cannot find a substitute, you will be subject to the class cancellation policy.

Make-up Policy

Students are permitted one (1) Make-Up opportunity to attend an instructor-led class that was paid for but not previously attended for no additional charge.

  • Make-Up class registrations are subject to availability and are not entitled to refund.
  • Students may not reschedule a Make-up class registration.
  • Any no shows or cancellations forfeit their one Make-up opportunity.

Additionally, ONLC reserves the right to retire courses due to lack of demand. Retired classes are not available for Make-Up.

In the event that an instructor or the school needs to cancel at the last minute, students will receive a refund less a 5% non-refundable registration fee.

In any event where a customer wants to cancel their enrollment and is eligible for a full refund, a 5% processing fee will be deducted from the refund amount.

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ONLC Training Centers

ONLC Training Centers was founded in 1983 when Jim Palic and Andy Williamson left their positions as mainframe programmers with the Dupont Company to start one of the industry's first computer training companies.

Over thirty years and still growing, ONLC Training Centers is one of the the largest privately...

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