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Rafael Lopes
Learn how to go from raw data to meaningful insights using AWS with this one-week course. Throughout the course, you’ll learn about the fundamentals of Data Analytics from AWS experts.
Read more
Learn how to go from raw data to meaningful insights using AWS with this one-week course. Throughout the course, you’ll learn about the fundamentals of Data Analytics from AWS experts.
Read more
Learn how to go from raw data to meaningful insights using AWS with this one-week course. Throughout the course, you’ll learn about the fundamentals of Data Analytics from AWS experts.
Start off with an overview of different types of data analytics techniques - descriptive, diagnostic, predictive, and prescriptive before diving deeper into the descriptive data analytics. Then, apply your knowledge with a guided project that makes use of a simple, but powerful dataset available by default in every AWS account: the logs from AWS CloudTrail. The CloudTrail service enables governance, compliance, operational auditing, and risk auditing of your AWS account. Through the project you’ll also get an introduction to Amazon Athena and Amazon QuickSight. And, you’ll learn how to build a basic security dashboard as a simple but practical method of applying your newfound data analytics knowledge.
Register for this course and see more details by visiting:
OpenCourser.com/course/awmxnm/getting
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What's inside
Syllabus
Getting Started with Data Analytics on AWS
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Does not teach any specific software that may become deprecated
Provides a hands-on project that uses a dataset available in every AWS account
Covers topics such as descriptive, diagnostic, predictive, and prescriptive analytics techniques
Taught by AWS experts, who are recognized for their work in the field
Helps learners build a basic security dashboard, which is a practical application of data analytics knowledge
Requires no prerequisites, making it accessible to beginners
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Reviews summary
Aws data analytics basics
Learners say this 5-star rated beginner-friendly course offers an informative introduction into data analytics using AWS services. It's good for beginners who want to learn the basics of data analytics and AWS, but it may be too basic for those with prior knowledge.
Focuses on descriptive data analysis and its solutions using AWS.
"This course is highly recommended for anyone interested in data science and business analytics. It's absolute beginner friendly and is great to start on your journey by first learning about descriptive data analysis and its solution by AWS (Amazon Web Service)."
Covers various AWS services for data analytics, such as S3, Athena, CloudTrail, and QuikSight.
"Excellent, quick course, cleverly presenting combining Data Analytics and AWS services S3, QuickTrail, QuickSight and Athena."
Provides a good overview of data analytics concepts and AWS features.
"Gives us a very good overview of the Data Anlytics domain and AWS features and utilities."
"Fantastic course to start with AWS and Data Analytics."
Suitable for learners with little to no prior knowledge of data analytics.
"Really simple and easy to understand. Perfect for beginners like me!"
"As a student&beginner, this course is easily understandable."
May assume some prior knowledge, which can be challenging for complete beginners.
"Expected more learning content and it was not exactly for a beginner. Not Satisfied."
Limited hands-on practice or examples, which some learners may find insufficient.
"It was amazing but i also want to learn those aws s3 aws athena tools in more detail and in more easy to understandable manner."
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 Getting Started with Data Analytics on AWS with these
activities:
Refresher on the Basics of Data Analytics
Show steps
Refresh your understanding of core data analytics concepts before the course begins to enhance your comprehension of the course materials.
Show steps
-
Review introductory materials on data analytics, such as articles, videos, or online tutorials.
-
Go through your notes or textbooks from previous data analytics courses or programs.
-
Complete practice exercises or quizzes on basic data analytics concepts.
Participate in Study Groups for Course Review
Show steps
Enhance your learning experience by collaborating with peers, discussing course concepts, and exploring different perspectives to deepen your understanding.
Show steps
-
Form or join study groups with fellow students.
-
Meet regularly to review course materials, ask questions, and engage in discussions.
-
Utilize these sessions to clarify concepts, share insights, and learn from each other.
Regular Practice with Data Analytics Exercises
Show steps
Solidify your understanding and develop your proficiency in data analytics by regularly engaging in practice exercises, honing your skills and reinforcing concepts.
Show steps
-
Seek out and solve data analytics exercises and problems.
-
Work through datasets, practicing data cleaning, exploration, and analysis techniques.
-
Review solutions and compare your approaches to improve your problem-solving skills.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Hands-On Tutorial for AWS CloudTrail Logging
Show steps
Apply your knowledge of descriptive analytics with a hands-on project using AWS CloudTrail logs, enhancing your understanding of security auditing.
Browse courses on
AWS CloudTrail
Show steps
-
Follow guided tutorials on enabling and configuring AWS CloudTrail logs.
-
Set up a simple security monitoring dashboard using CloudTrail logs.
-
Analyze log data to identify potential security events.
Summarize Key Concepts from Course Lectures
Show steps
Reinforce your understanding of course materials by creating summaries of key concepts presented in the lectures, improving your retention and comprehension.
Show steps
-
Identify the main ideas and supporting points from each lecture.
-
Write concise summaries summarizing the key concepts, using your own words.
-
Review and refine your summaries to ensure clarity and accuracy.
Attend a Workshop on Advanced Data Analytics Techniques
Show steps
Supplement your learning with a workshop focused on advanced data analytics techniques, broadening your knowledge and skills beyond the course scope.
Browse courses on
Predictive Analytics
Show steps
-
Research and identify workshops on advanced data analytics techniques.
-
Enroll and attend the selected workshop, actively participating in sessions and discussions.
-
Apply what you've learned to enhance your data analytics projects.
Develop a Comprehensive Data Analytics Portfolio
Show steps
Showcase your data analytics skills and knowledge by creating a portfolio of your best projects and deliverables, providing evidence of your capabilities and progress.
Show steps
-
Gather and select your strongest data analytics projects and deliverables.
-
Organize and present your portfolio in a visually appealing and coherent manner.
-
Share your portfolio with potential employers or clients to demonstrate your abilities.
Refresher on the Basics of Data Analytics
Show steps
Refresh your understanding of core data analytics concepts before the course begins to enhance your comprehension of the course materials.
Show steps
Show steps
Show steps
- Review introductory materials on data analytics, such as articles, videos, or online tutorials.
- Go through your notes or textbooks from previous data analytics courses or programs.
- Complete practice exercises or quizzes on basic data analytics concepts.
Participate in Study Groups for Course Review
Show steps
Enhance your learning experience by collaborating with peers, discussing course concepts, and exploring different perspectives to deepen your understanding.
Show steps
Show steps
Show steps
- Form or join study groups with fellow students.
- Meet regularly to review course materials, ask questions, and engage in discussions.
- Utilize these sessions to clarify concepts, share insights, and learn from each other.
Regular Practice with Data Analytics Exercises
Show steps
Solidify your understanding and develop your proficiency in data analytics by regularly engaging in practice exercises, honing your skills and reinforcing concepts.
Show steps
Show steps
Show steps
- Seek out and solve data analytics exercises and problems.
- Work through datasets, practicing data cleaning, exploration, and analysis techniques.
- Review solutions and compare your approaches to improve your problem-solving skills.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Hands-On Tutorial for AWS CloudTrail Logging
Show steps
Apply your knowledge of descriptive analytics with a hands-on project using AWS CloudTrail logs, enhancing your understanding of security auditing.
Browse courses on
AWS CloudTrail
Show steps
Show steps
Show steps
- Follow guided tutorials on enabling and configuring AWS CloudTrail logs.
- Set up a simple security monitoring dashboard using CloudTrail logs.
- Analyze log data to identify potential security events.
Summarize Key Concepts from Course Lectures
Show steps
Reinforce your understanding of course materials by creating summaries of key concepts presented in the lectures, improving your retention and comprehension.
Show steps
Show steps
Show steps
- Identify the main ideas and supporting points from each lecture.
- Write concise summaries summarizing the key concepts, using your own words.
- Review and refine your summaries to ensure clarity and accuracy.
Attend a Workshop on Advanced Data Analytics Techniques
Show steps
Supplement your learning with a workshop focused on advanced data analytics techniques, broadening your knowledge and skills beyond the course scope.
Browse courses on
Predictive Analytics
Show steps
Show steps
Show steps
- Research and identify workshops on advanced data analytics techniques.
- Enroll and attend the selected workshop, actively participating in sessions and discussions.
- Apply what you've learned to enhance your data analytics projects.
Develop a Comprehensive Data Analytics Portfolio
Show steps
Showcase your data analytics skills and knowledge by creating a portfolio of your best projects and deliverables, providing evidence of your capabilities and progress.
Show steps
Show steps
Show steps
- Gather and select your strongest data analytics projects and deliverables.
- Organize and present your portfolio in a visually appealing and coherent manner.
- Share your portfolio with potential employers or clients to demonstrate your abilities.
Career center
Learners who complete Getting Started with Data Analytics on AWS will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts turn raw data into meaningful insights using statistical techniques and computing tools. They help businesses make better decisions by identifying trends and patterns in data. This course helps build a foundation in data analytics, providing an introduction to descriptive, diagnostic, predictive, and prescriptive analytics techniques. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the infrastructure and systems that store and process data. They work closely with Data Analysts to ensure that data is available and accessible for analysis. This course provides an introduction to the fundamentals of data engineering, including data storage, data processing, and data analytics. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Business Analyst
Business Analyst
Business Analysts identify and solve business problems using data. They work with stakeholders across the organization to gather requirements, analyze data, and develop recommendations. This course provides an introduction to the fundamentals of business analysis, including data analysis, data visualization, and problem-solving. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Data Scientist
Data Scientist
Data Scientists use statistical techniques and machine learning algorithms to build predictive models. They help businesses make better decisions by identifying trends and patterns in data. This course provides an introduction to the fundamentals of data science, including data analysis, machine learning, and predictive modeling. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with stakeholders across the organization to gather requirements, design solutions, and implement code. This course provides an introduction to the fundamentals of software engineering, including data structures, algorithms, and software design. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Cloud Architect
Cloud Architect
Cloud Architects design, build, and maintain cloud computing environments. They work with stakeholders across the organization to assess needs, design solutions, and implement infrastructure. This course provides an introduction to the fundamentals of cloud computing, including cloud architecture, cloud services, and cloud security. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
DevOps Engineer
DevOps Engineer
DevOps Engineers bridge the gap between development and operations teams. They work to automate and streamline the software development process. This course provides an introduction to the fundamentals of DevOps, including continuous integration, continuous delivery, and infrastructure as code. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Security Analyst
Security Analyst
Security Analysts identify and mitigate security risks. They work with stakeholders across the organization to assess threats, develop security plans, and implement security measures. This course provides an introduction to the fundamentals of security analysis, including security assessment, security planning, and security implementation. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Database Administrator
Database Administrator
Database Administrators design, build, and maintain databases. They work with stakeholders across the organization to ensure that data is available and accessible for analysis. This course provides an introduction to the fundamentals of database administration, including database design, database management, and database security. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Data Visualization Analyst
Data Visualization Analyst
Data Visualization Analysts create visual representations of data. They work with stakeholders across the organization to communicate insights and trends. This course provides an introduction to the fundamentals of data visualization, including data visualization techniques, data visualization tools, and data visualization best practices. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Product Manager
Product Manager
Product Managers identify and solve customer problems. They work with stakeholders across the organization to define product requirements, design product solutions, and launch products. This course provides an introduction to the fundamentals of product management, including product development, product marketing, and product management tools. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Project Manager
Project Manager
Project Managers plan and execute projects. They work with stakeholders across the organization to define project scope, create project plans, and manage project risks. This course provides an introduction to the fundamentals of project management, including project planning, project execution, and project management tools. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Systems Analyst
Systems Analyst
Systems Analysts design, build, and maintain information systems. They work with stakeholders across the organization to identify needs, develop solutions, and implement systems. This course provides an introduction to the fundamentals of systems analysis, including systems design, systems development, and systems implementation. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
IT Auditor
IT Auditor
IT Auditors assess the security and compliance of IT systems. They work with stakeholders across the organization to identify risks, develop audit plans, and conduct audits. This course provides an introduction to the fundamentals of IT auditing, including IT audit techniques, IT audit tools, and IT audit best practices. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
Management Consultant
Management Consultant
Management Consultants help organizations improve their performance. They work with stakeholders across the organization to identify problems, develop solutions, and implement change. This course provides an introduction to the fundamentals of management consulting, including consulting techniques, consulting tools, and consulting best practices. Learners will also gain practical experience working with real-world datasets using Amazon Athena and Amazon QuickSight.
For more career information including salaries, visit:
OpenCourser.com/course/awmxnm/getting
Reading list
We've selected seven 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
Getting Started with Data Analytics on AWS.
A beginner-friendly guide to data analytics, covering fundamental concepts, techniques, and tools. Provides a solid foundation for understanding the course material.
Provides a comprehensive overview of SQL for data analytics, including data retrieval, manipulation, and analysis techniques. Serves as a valuable reference for using SQL in the course project.
Save
Provides a comprehensive overview of cloud computing concepts, technologies, and architectures. Offers a solid foundation for understanding the fundamentals of cloud data analytics.
Focuses on practical data analytics using the popular Python library Pandas. Offers hands-on exercises and examples to reinforce the course concepts.
A comprehensive resource on Hadoop, a popular distributed computing platform used for big data analytics. Offers in-depth coverage of Hadoop components and ecosystem.
Provides a business-oriented perspective on data science. Helps learners understand how data science can drive business value and inform decision-making.
Provides a comprehensive introduction to natural language processing (NLP) techniques. Covers NLP concepts, algorithms, and applications, which are increasingly relevant in data analytics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/awmxnm/getting
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Effort
1 week
Level
Introductory
Via
Coursera
Institution
Amazon Web Services
Instructor
Rafael Lopes
Language
English
Transcripts
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آذربایجان دیلی
Good to know
Does not teach any specific software that may become deprecated
Provides a hands-on project that uses a dataset available in every AWS account
Covers topics such as descriptive, diagnostic, predictive, and prescriptive analytics techniques
Taught by AWS experts, who are recognized for their work in the field
Helps learners build a basic security dashboard, which is a practical application of data analytics knowledge
Requires no prerequisites, making it accessible to beginners
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