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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. 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.
Read more
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. 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.
Read more
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. 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
Register for this course and see more details by visiting:
OpenCourser.com/course/fwj1fy/exploratory
What's inside
Syllabus
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.
Read more
Syllabus
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.
Read more
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.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops skills in working with data for machine learning through AWS services
Provides a hands-on learning experience through video lectures and graded quizzes
Covers foundational concepts of data streams and data analytics in AWS
Introduces learners to the AWS Glue service for data analysis
May require prior knowledge of data analysis and AWS services
The content might be outdated if there are significant updates to AWS services
Save this course
Save Exploratory Data Analysis in AWS to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Exploratory Data Analysis in AWS with these
activities:
Review Data Analysis Fundamentals
Show steps
Revisit the fundamental concepts of data analysis, statistics, and Python programming to strengthen your foundation before embarking on this course.
Browse courses on
Data Analysis
Show steps
-
Review basic data analysis concepts
-
Refresh your understanding of statistics
-
Practice using Python for data analysis
Course Materials Compilation
Show steps
Organize and review your class notes, assignments, and other course materials to enhance your understanding and retention of the course content.
Show steps
-
Gather and organize your course materials
-
Review and summarize key concepts
-
Create a study guide or cheat sheet for reference
Study Group Discussions
Show steps
Join a study group to engage with peers, share insights, and reinforce your understanding of the course concepts through collaborative learning.
Show steps
-
Find or form a study group
-
Meet regularly to discuss course topics
-
Collaborate on assignments and projects
Four other activities
Expand to see all activities and additional details
Show all seven activities
AWS Glue Tutorials
Show steps
Follow AWS Glue tutorials to gain practical experience with data transformations and integration, enhancing your understanding of data analysis techniques in AWS.
Browse courses on
AWS Glue
Show steps
-
Complete the AWS Glue Getting Started tutorial
-
Explore additional AWS Glue tutorials based on your interests
Data Streams Lab Exercises
Show steps
Practice the implementation and configuration of data streams services in AWS to reinforce your understanding of data streaming concepts.
Browse courses on
Kinesis Data Streams
Show steps
-
Create a Kinesis Data Stream
-
Write data to the Kinesis Data Stream
-
Create a Kinesis Data Analytics application
-
Analyze data in the Kinesis Data Analytics application
Data Analysis Dashboard
Show steps
Create a comprehensive data analysis dashboard to visualize and analyze data for your chosen use case, solidifying your understanding of data analysis techniques.
Browse courses on
Data Analysis
Show steps
-
Gather and prepare your data
-
Create a data visualization framework
-
Design and develop your dashboard
-
Publish and share your dashboard
Machine Learning Project with AWS Data Analytics Services
Show steps
Embark on a project that leverages AWS data analytics services to build and train a machine learning model, applying your knowledge of data analysis and machine learning in a practical setting.
Browse courses on
Machine Learning
Show steps
-
Define your project goals and scope
-
Gather and prepare your data
-
Build and train your machine learning model
-
Evaluate and refine your model
-
Deploy your model and monitor its performance
Review Data Analysis Fundamentals
Show steps
Revisit the fundamental concepts of data analysis, statistics, and Python programming to strengthen your foundation before embarking on this course.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Review basic data analysis concepts
- Refresh your understanding of statistics
- Practice using Python for data analysis
Course Materials Compilation
Show steps
Organize and review your class notes, assignments, and other course materials to enhance your understanding and retention of the course content.
Show steps
Show steps
Show steps
- Gather and organize your course materials
- Review and summarize key concepts
- Create a study guide or cheat sheet for reference
Study Group Discussions
Show steps
Join a study group to engage with peers, share insights, and reinforce your understanding of the course concepts through collaborative learning.
Show steps
Show steps
Show steps
- Find or form a study group
- Meet regularly to discuss course topics
- Collaborate on assignments and projects
Four other activities
Expand to see all activities and additional details
Show all seven activities
AWS Glue Tutorials
Show steps
Follow AWS Glue tutorials to gain practical experience with data transformations and integration, enhancing your understanding of data analysis techniques in AWS.
Browse courses on
AWS Glue
Show steps
Show steps
Show steps
- Complete the AWS Glue Getting Started tutorial
- Explore additional AWS Glue tutorials based on your interests
Data Streams Lab Exercises
Show steps
Practice the implementation and configuration of data streams services in AWS to reinforce your understanding of data streaming concepts.
Browse courses on
Kinesis Data Streams
Show steps
Show steps
Show steps
- Create a Kinesis Data Stream
- Write data to the Kinesis Data Stream
- Create a Kinesis Data Analytics application
- Analyze data in the Kinesis Data Analytics application
Data Analysis Dashboard
Show steps
Create a comprehensive data analysis dashboard to visualize and analyze data for your chosen use case, solidifying your understanding of data analysis techniques.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Gather and prepare your data
- Create a data visualization framework
- Design and develop your dashboard
- Publish and share your dashboard
Machine Learning Project with AWS Data Analytics Services
Show steps
Embark on a project that leverages AWS data analytics services to build and train a machine learning model, applying your knowledge of data analysis and machine learning in a practical setting.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Define your project goals and scope
- Gather and prepare your data
- Build and train your machine learning model
- Evaluate and refine your model
- Deploy your model and monitor its performance
Career center
Learners who complete Exploratory Data Analysis in AWS will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst is responsible for collecting, cleaning, analyzing, and interpreting data to help businesses make informed decisions. This course can help you develop the skills needed to be a successful Data Analyst, such as data wrangling, data visualization, and statistical analysis. Additionally, the course covers AWS-specific tools and services that are commonly used by Data Analysts, such as Kinesis Data Streams and AWS Glue.
Data Engineer
Data Engineer
A Data Engineer is responsible for designing, building, and maintaining data pipelines and data infrastructure. This course can help you develop the skills needed to be a successful Data Engineer, such as data modeling, data integration, and cloud computing. Additionally, the course covers AWS-specific tools and services that are commonly used by Data Engineers, such as Kinesis Data Firehose and AWS Glue.
Data Scientist
Data Scientist
A Data Scientist is responsible for using data to solve business problems. This course can help you develop the skills needed to be a successful Data Scientist, such as machine learning, data mining, and predictive analytics. Additionally, the course covers AWS-specific tools and services that are commonly used by Data Scientists, such as Kinesis Data Analytics and AWS SageMaker.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for designing, building, and deploying machine learning models. This course can help you develop the skills needed to be a successful Machine Learning Engineer, such as machine learning algorithms, model evaluation, and cloud computing. Additionally, the course covers AWS-specific tools and services that are commonly used by Machine Learning Engineers, such as Kinesis Data Streams and AWS SageMaker.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst is responsible for using data to make informed business decisions. This course can help you develop the skills needed to be a successful Business Intelligence Analyst, such as data visualization, data mining, and predictive analytics. Additionally, the course covers AWS-specific tools and services that are commonly used by Business Intelligence Analysts, such as Kinesis Data Streams and AWS QuickSight.
Statistician
Statistician
A Statistician is responsible for collecting, analyzing, and interpreting data. This course can help you develop the skills needed to be a successful Statistician, such as statistical analysis, data visualization, and probability theory. Additionally, the course covers AWS-specific tools and services that are commonly used by Statisticians, such as Kinesis Data Streams and Amazon Redshift.
Data Architect
Data Architect
A Data Architect is responsible for designing and managing data systems. This course can help you develop the skills needed to be a successful Data Architect, such as data modeling, data integration, and cloud computing. Additionally, the course covers AWS-specific tools and services that are commonly used by Data Architects, such as Kinesis Data Streams and AWS Glue.
Database Administrator
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. This course can help you develop the skills needed to be a successful Database Administrator, such as database design, database optimization, and cloud computing. Additionally, the course covers AWS-specific tools and services that are commonly used by Database Administrators, such as Amazon RDS and Amazon DynamoDB.
Software Engineer
Software Engineer
A Software Engineer is responsible for designing, building, and maintaining software applications. This course can help you develop the skills needed to be a successful Software Engineer, such as software design, software development, and cloud computing. Additionally, the course covers AWS-specific tools and services that are commonly used by Software Engineers, such as Kinesis Data Streams and AWS Lambda.
Cloud Architect
Cloud Architect
A Cloud Architect is responsible for designing and managing cloud computing systems. This course can help you develop the skills needed to be a successful Cloud Architect, such as cloud computing, cloud security, and cloud optimization. Additionally, the course covers AWS-specific tools and services that are commonly used by Cloud Architects, such as Kinesis Data Streams and AWS CloudFormation.
DevOps Engineer
DevOps Engineer
A DevOps Engineer is responsible for bridging the gap between development and operations teams. This course can help you develop the skills needed to be a successful DevOps Engineer, such as cloud computing, continuous integration, and continuous delivery. Additionally, the course covers AWS-specific tools and services that are commonly used by DevOps Engineers, such as Kinesis Data Streams and AWS CodePipeline.
Big Data Engineer
Big Data Engineer
A Big Data Engineer is responsible for designing, building, and maintaining big data systems. This course can help you develop the skills needed to be a successful Big Data Engineer, such as big data technologies, big data analytics, and cloud computing. Additionally, the course covers AWS-specific tools and services that are commonly used by Big Data Engineers, such as Kinesis Data Streams and Amazon EMR.
Data Visualization Engineer
Data Visualization Engineer
A Data Visualization Engineer is responsible for designing and creating data visualizations. This course can help you develop the skills needed to be a successful Data Visualization Engineer, such as data visualization techniques, data visualization tools, and cloud computing. Additionally, the course covers AWS-specific tools and services that are commonly used by Data Visualization Engineers, such as Kinesis Data Streams and Amazon QuickSight.
Machine Learning Scientist
Machine Learning Scientist
A Machine Learning Scientist is responsible for conducting research and developing machine learning algorithms. This course may help you develop some of the skills needed to be a successful Machine Learning Scientist, such as machine learning algorithms and machine learning theory. However, this course does not cover advanced topics such as natural language processing or computer vision.
Data Security Analyst
Data Security Analyst
A Data Security Analyst is responsible for protecting data from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may help you develop some of the skills needed to be a successful Data Security Analyst, such as data security principles and data security technologies. However, this course does not cover advanced topics such as intrusion detection or security auditing.
For more career information including salaries, visit:
OpenCourser.com/course/fwj1fy/exploratory
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Exploratory Data Analysis in AWS.
Will help learners to understand the basics of data analysis in Python using Pandas.
Covers the basics of machine learning using Python and scikit-learn.
Covers natural language processing in Python using NLTK.
Provides a beginner-friendly introduction to AWS services, useful for learners who are new to AWS.
Covers advanced data analytics techniques using Spark.
Provides a comprehensive overview of machine learning with AWS. It covers a wide range of topics, including data preparation, model training, and model deployment.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/fwj1fy/exploratory
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Effort
2 weeks of study, 2-2:30 hours/week
Level
Introductory
Via
Coursera
Institution
Whizlabs
Instructor
Whizlabs Instructor
Language
English
This course belongs to a
collection
called
Exam Prep MLS-C01: AWS Certified Specialty Machine Learning. It's comprised of five courses:
- ML Algorithms
- Machine Learning Implementation and Operations in AWS
- Exploratory Data Analysis in AWS (viewing)
- Data Engineering in AWS
- Modeling in AWS
Good to know
Develops skills in working with data for machine learning through AWS services
Provides a hands-on learning experience through video lectures and graded quizzes
Covers foundational concepts of data streams and data analytics in AWS
Introduces learners to the AWS Glue service for data analysis
May require prior knowledge of data analysis and AWS services
The content might be outdated if there are significant updates to AWS services
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