Exploratory Data Analysis in AWS (Coursera)

Offered by Whizlabs,
Exploratory Data Analysis in AWS (Coursera)

Exploratory Data Analysis in AWS is the second course in the AWS Certified Machine Learning Specialty specialization. The main focus of this course is to analyze Data Streams and Data Analytics services in AWS along with exploring Data Analysis in AWS. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

This course facilitates learners with approximately 2:00-2:30 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners.
Module 1: Introduction to Data Streams and Data Analytics services in AWS
Module 2: Exploring Data Analysis in AWS
By the end of this course, a learner will be able to:
-Demonstrate the implementation of Kinesis Data Streams
-Analyze and visualize data for machine learning
-Examine AWS Glue service with creation of crawler and transform job
Course 2 of 5 in the Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization.

What You Will Learn

  • Analyze and visualize data for machine learning
  • Demonstrate the implementation of Kinesis Data Streams
  • Examine AWS Glue service with creation of crawler and transform job

Syllabus

WEEK 1
Introduction to Data Streams and Data Analytics services in AWS
Module 1:Introduction to Data Streams and Data Analytics services in AWS
Welcome to Week 1 of Exploratory Data Analysis in AWS Course. In this week, we’ll Analyze working of Kinesis Data Streams and Kinesis Data Firehose. We’ll also gain demonstrations on Kinesis Data Streams and Kinesis Data Firehose. Finally, the week will end by implementing Kinesis Video Streams and Kinesis Data Analytics.

WEEK 2
Exploring Data Analysis in AWS
Welcome to Week 2 of Exploratory Data Analysis in AWS Course. This week, we’ll learn AWS Glue Service for performing Data Analysis. We’ll be able to Analyze and visualize data for machine learning. In the end of the week, we’ll Demonstrate AWS Glue Crawler and Create transform job.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

ML Pipelines on Google Cloud (Coursera) Coursera
Google Cloud

ML Pipelines on Google Cloud (Coursera)

In this course, you will be learning from ML Engineers and Trainers who work with the state-of-the-art development of ML pipelines here at Google Cloud. The first few modules will cover about TensorFlow Extended (or TFX), which is Google’s production machine learning platform based on TensorFlow for management of ML pipelines and metadata. You will learn about pipeline components and pipeline orchestration with TFX. You will also learn how you can automate your pipeline through continuous integration and continuous deployment, and how to manage ML metadata.

Aug 17th 2026
4 Weeks
Gestión del análisis de datos (Coursera) Coursera
Johns Hopkins University

Gestión del análisis de datos (Coursera)

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results.

Aug 24th 2026
1 Week
AI-Driven Attribution Testing (Coursera) Coursera
Board Infinity

AI-Driven Attribution Testing (Coursera)

Welcome to AI-Driven Attribution Testing course an engaging and comprehensive course designed to guide you through the fundamental concepts and practical applications of attribution testing powered by artificial intelligence. This course is most suitable for marketers, data analysts, data scientists, and business leaders who aim to leverage data-driven insights for decision-making. It's also beneficial for students and professionals with a keen interest in the convergence of AI, data analysis, and marketing.

Aug 24th 2026
2 Weeks
Machine Learning for All (Coursera) Coursera
University of London

Machine Learning for All (Coursera)

Machine Learning, often called Artificial Intelligence or AI, is one of the most exciting areas of technology at the moment. We see daily news stories that herald new breakthroughs in facial recognition technology, self driving cars or computers that can have a conversation just like a real person. Machine Learning technology is set to revolutionise almost any area of human life and work, and so will affect all our lives, and so you are likely to want to find out more about it.

Aug 24th 2026
4 Weeks
Data Science for Business Innovation (Coursera) Coursera
Politecnico di Milano,EIT Digital

Data Science for Business Innovation (Coursera)

The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues.

Aug 24th 2026
4 Weeks
Business intelligence and data analytics: Generate insights (Coursera) Coursera
Macquarie University

Business intelligence and data analytics: Generate insights (Coursera)

‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation.

Aug 24th 2026
5-12 Weeks
Cadeia de Suprimentos na Nuvem (Coursera) Coursera
FIA Business School

Cadeia de Suprimentos na Nuvem (Coursera)

Nossas boas-vindas ao Curso Cadeia de Suprimentos na Nuvem. Neste curso, você aprenderá como o supply chain pode ampliar o valor da empresa explorando as diversas ferramentas disponíveis em cloud para potencializar a visibilidade e a responsividade da cadeia, melhorando o nível de serviço prestado aos clientes.

Aug 17th 2026
5-12 Weeks
Deep Learning for Business (Coursera) Coursera
Yonsei University

Deep Learning for Business (Coursera)

Your smartphone, smartwatch, and automobile (if it is a newer model) have AI (Artificial Intelligence) inside serving you every day. In the near future, more advanced “self-learning” capable DL (Deep Learning) and ML (Machine Learning) technology will be used in almost every aspect of your business and industry. So now is the right time to learn what DL and ML is and how to use it in advantage of your company. This course has three parts, where the first part focuses on DL and ML technology based future business strategy including details on new state-of-the-art products/services and open source DL software, which are the future enablers.

Aug 24th 2026
5-12 Weeks
Technologies and platforms for Artificial Intelligence (Coursera) Coursera
Politecnico di Milano

Technologies and platforms for Artificial Intelligence (Coursera)

This course will address the hardware technologies for machine and deep learning (from the units of an Internet-of-Things system to a large-scale data centers) and will explore the families of machine and deep learning platforms (libraries and frameworks) for the design and development of smart applications and systems.

Aug 17th 2026
4 Weeks
Deep Learning Applications for Computer Vision (Coursera) Coursera
University of Colorado Boulder

Deep Learning Applications for Computer Vision (Coursera)

This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics.

Aug 17th 2026
5-12 Weeks