Your privacy matters: This site uses cookies to analyze site usage and provide social media features. Learn More.

Introduction to Cloud-Based Python for Data Science & Machine Learning

PYTH-210 (2 Days)

Request Pricing

Python for Data Science Training Overview

This Cloud-Based Python for Data Science & Machine Learning training class teaches attendees how to use the power of the AWS (Amazon Web Services) platform for a wide array of cloud-native data science and machine learning tasks. Lab work uses the Python scripting language in conjunction with AWS platform technologies to deliver robust, scalable solutions.

Location and Pricing

Most Accelebrate courses are delivered as private, customized, on-site training at our clients' locations worldwide for groups of 3 or more attendees and are custom tailored to their specific needs. Please visit our client list to see organizations for whom we have delivered private in-house training. These courses can also be delivered as live, private online classes for groups that are geographically dispersed or wish to save on the instructor's or students' travel expenses. To receive a customized proposal and price quote for private training at your site or online, please contact us.

Python for Data Science Training Objectives

All students will:

  • Use cloud-based Python for Data Science by following the instructor through hands-on labs using Python in Jupyter Notebooks and Google Colab notebooks
  • Learn the advantages of cloud-based machine learning over local environments
  • Create programs to learn core Python concepts such as data types, functions, classes and control structures, which are necessary to effectively practice data science and implement machine learning
  • Practice implementing python functions and control structures, including error handling and exceptions
  • Work with both structured and unstructured data across the entire lifecycle
  • Work with Pandas to Explore and Clean Data
  • Learn about powerful cloud-based machine learning through Amazon Web Services

Python for Data Science Training Outline

Expand All | Collapse All | Printer-Friendly

Introduction
  • Introductory Concepts in Python, IPython, and Jupyter
  • IPython and Python REPL
  • Procedural statements
  • Strings and string formatting
  • Numbers and arithmetic operations
  • Data Structures: Lists, Dictionaries, Sets, and Operations
  • Writing and running scripts
  • Functions
  • Function arguments: positional, keyword
  • Functional Currying: Passing uncalled functions
  • Functions that yield
  • Decorators: Functions that wrap other functions
  • Lambdas
Using Libraries, Classes, Control, and Structures
  • Using Libraries In Python
  • Understanding Python Classes
  • Control Structures
  • Understanding Sorting
  • Python Regular Expressions
Working with Data
  • Structured Data
  • Working with Files (reading/writing)
  • Sub-processing and multiprocessing
  • Reading and Writing YAML Files
  • Reading and Writing DataFrames in Pandas
  • Joining, Merging and Querying DataFrames in Pandas
  • Walkthrough Social Power NBA Exploratory Data Analysis and Machine Learning Project
Python Pandas Interactive Visualizations for Machine Learning Project Exploration
  • Use Pandas DataFrames
  • Importing and merging DataFrames in Pandas
  • Data cleaning - filtering duplicates
  • Combining datasets
  • Visualization for EDA
Cloud-Native Data Science and Machine Learning
  • Overview of core AWS Services
  • Applied Python and Cloud Basics
  • Introduction to AWS Web Services: Creating accounts, Creating Users and Using Amazon S3 effectively
  • A brief overview of AWS Python Lambda development with Chalice
  • Overview of Step functions with AWS
  • Overview of AWS Batch for ML Jobs
  • Software Carpentry (foundational skills necessary for success:  using libraries, checking in code, running lint)
  • Using Git and Github to manage changes
  • Using CircleCI to build and test project sourced from Github
  • Using Static Analysis and Testing tools: Pylint and Pytest
  • Using Jupyter Notebook / Google Colaboratory
  • Introduction to AWS Sagemaker
Conclusion
Request Pricing

Lecture percentage

50%

Lecture/Demo

Lab percentage

50%

Lab

Course Number:

PYTH-210

Duration:

2 Days

Prerequisites:

All attendees should have prior programming experience in Python and an understanding of basic statistics.

Training Materials:

All Python training students receive comprehensive courseware.

Software Requirements:

  • Google Chrome or Mozilla Firefox
  • Github Account
  • AWS Free Account
  • GCP Free Account

Contact Us:

Accelebrate’s training classes are available for private groups of 3 or more people at your site or online anywhere worldwide.

Don't settle for a "one size fits all" public class! Have Accelebrate deliver exactly the training you want, privately at your site or online, for less than the cost of a public class.

For pricing and to learn more, please contact us.

Contact Us Train For Us

Toll-free in US/Canada:
877 849 1850
International:
+1 678 648 3113

Toll-free in US/Canada:
866 566 1228
International:
+1 404 420 2491

925B Peachtree Street, NE
PMB 378
Atlanta, GA 30309-3918
USA

Subscribe to our Newsletter:

Never miss the latest news and information from Accelebrate:

Microsoft Gold Partner

Please see our complete list of
Microsoft Official Courses

Recent Training Locations

Alabama

Huntsville

Montgomery

Birmingham

Alaska

Anchorage

Arizona

Phoenix

Tucson

Arkansas

Fayetteville

Little Rock

California

San Francisco

Oakland

San Jose

Orange County

Los Angeles

Sacramento

San Diego

Colorado

Denver

Boulder

Colorado Springs

Connecticut

Hartford

DC

Washington

Florida

Fort Lauderdale

Miami

Jacksonville

Orlando

Saint Petersburg

Tampa

Georgia

Atlanta

Augusta

Savannah

Idaho

Boise

Illinois

Chicago

Indiana

Indianapolis

Iowa

Ceder Rapids

Des Moines

Kansas

Wichita

Kentucky

Lexington

Louisville

Louisiana

Banton Rouge

New Orleans

Maine

Portland

Maryland

Annapolis

Baltimore

Hagerstown

Frederick

Massachusetts

Springfield

Boston

Cambridge

Michigan

Ann Arbor

Detroit

Grand Rapids

Minnesota

Saint Paul

Minneapolis

Mississippi

Jackson

Missouri

Kansas City

St. Louis

Nebraska

Lincoln

Omaha

Nevada

Reno

Las Vegas

New Jersey

Princeton

New Mexico

Albuquerque

New York

Buffalo

Albany

White Plains

New York City

North Carolina

Charlotte

Durham

Raleigh

Ohio

Canton

Akron

Cincinnati

Cleveland

Columbus

Dayton

Oklahoma

Tulsa

Oklahoma City

Oregon

Portland

Pennsylvania

Pittsburgh

Philadelphia

Rhode Island

Providence

South Carolina

Columbia

Charleston

Spartanburg

Greenville

Tennessee

Memphis

Nashville

Knoxville

Texas

Dallas

El Paso

Houston

San Antonio

Austin

Utah

Salt Lake City

Virginia

Richmond

Alexandria

Arlington

Washington

Tacoma

Seattle

West Virginia

Charleston

Wisconsin

Madison

Milwaukee

Alberta

Edmonton

Calgary

British Columbia

Vancouver

Nova Scotia

Halifax

Ontario

Ottawa

Toronto

Quebec

Montreal

Puerto Rico

San Juan

© 2013-2019 Accelebrate, Inc. All Rights Reserved. All trademarks are owned by their respective owners.