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

PYTH-210 (2 Days)
Request Pricing for Introduction to Cloud-Based Python for Data Science & Machine Learning

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

Accelebrate courses are taught as private, customized training for groups of 3 or more at your site. In addition, we offer live, private online training for teams who may be in multiple locations or wish to save on travel costs. To receive a customized proposal and price quote for private on-site or online training, 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

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

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.

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