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Machine Learning and Data Science with AWS

Machine Learning and Data Science with AWS

Learn various cloud services on AWS- Glue, Athena, Quicksight and Comprehend

updated on icon Updated on Jul, 2024

language icon Language - English

person icon Pranjal Srivastava, Harshit Srivastava

English [CC]

category icon Machine Learning,Data Science

Lectures -30

Duration -2 hours

4.1

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Course Description

Welcome to this course on Machine Learning and Data Science with AWS. Amazon Web services or AWS is one of the biggest cloud computing platform where everything gets deployed to scale and action. Understanding the concepts and methods are vital, but being able to develop and deploy those concepts in forms of real life applications is something that is most weighted by the industry. Thus, here in this course, we are focused on ways you can use various cloud services on AWS to actually build and deploy you ideas into actions on multiple domains on Machine Learning and Data Science. You could be an IT professional looking for job change or upgrading your skillset or you could be a passionate learner or cloud certification aspirant, this course is for wider audience that if formed by the people who would like to learn any of these or a combination of these things-

  • Create and Analyze dataset to find insights and spot outliers or trends

  • Build Data visualization reports and dashboards by combining various visualization charts to represent data insights

  • Develop machine learning models for Natural Language Processing for various applications on AWS

  • And much more.

This course consists of multiple topics that are arranged in multiple sections. In the first few sections you would learn cloud services related to Data Science and Analysis on AWS with hands on practical examples. There you would be learning about creating a crawler in Glue, Analyzing dataset using SQL in Amazon Athena. After that you would learn to prepare a dataset for creating Data Visualization charts and reports that can be used for finding critical insights from the dataset that can be used in decision making process. You will learn to create calculated fields, excluded lists and filters on AWS Quicksight, followed by some advanced charts such as Word cloud and Funnel chart.

After that in Machine Learning section, you will learn about Natural language processing and it's application with the help of AWS Comprehend and Translate. AWS Comprehend is used to identify the language of the text, extract key phrases, places, people, brands, or events, understand sentiment about products or services, and identify the main topics from a library of documents. AWS Translate is used for translating language from one language to another.

Goals

  • You could prepare your dataset using AWS Glue, and Quicksight
  • Perform Data Analysis using Athena
  • Could Create Data Visualization Charts with Quicksight
  • You could create and develop machine learning models using Natural Language Processing

Prerequisites

  • Before taking this course, if you are already familiar with Data Science and Machine Learning at basic level, it would be useful.
Machine Learning and Data Science with AWS

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction
1 Lectures
  • play icon Introduction 01:27 01:27
Glue and Athena
6 Lectures
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Data Preparations with Quicksight
7 Lectures
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Data Visualization
4 Lectures
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Advanced Chart
4 Lectures
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NLP Natural Language Processing
8 Lectures
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Instructor Details

Pranjal Srivastava

Pranjal Srivastava

I am an Instructor, Devops engineer, machine learning enthusiast, cloud expert and passionate developer.

I have authored 78 courses with over 115,000 students worldwide across 175+ countries on wide array of technologies like devops, containerization, machine learning, Linux, programming languages and cloud computing platforms like Microsoft Azure, Amazon Web Service and IBM Cloud.

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