The course is part of this learning path
In this course, we will explore the Analytics tools provided by AWS, including Elastic Map Reduce (EMR), Data Pipeline, Elasticsearch, Kinesis, Amazon Machine Learning and QuickSight which is still in preview mode.
We will start with an overview of Data Science and Analytics concepts to give beginners the context they need to be successful in the course. The second part of the course will focus on the AWS offering for Analytics, this means, how AWS structures its portfolio in the different processes and steps of big data and data processing.
As a fundamentals course, the requirements are kept simple so you can focus on understanding the different services from AWS. But, a basic understanding of the following topics is necessary:
- As we are talking about technology and computing services, general IT knowledge is necessary, that is, the basics of programming logic, algorithms, and learning or working experience in the IT field.
- We will give you an overview of data science concepts, but if these concepts are already familiar to you, it will make your journey smoother.
- It is not mandatory but it would be helpful to have a general knowledge about AWS, most specifically about how to access your account and services such as S3 and EC2.
The following two courses from our portfolio can help you better understand the basics of AWS if you are just starting out:
If you have thoughts or suggestions for this course, please contact Cloud Academy at firstname.lastname@example.org.
Welcome to the AWS Analytics Fundamentals course. This first video is an introduction that will cover the requirements, course objectives, and what you'll learn through the course. As an introduction level course, we'll give you a broad overview about AWS Analytics Service. Let's go further and explore the requirements, audience, scope, and learning objectives from this course.
Requirements. As a fundamentals course, the requirements are kept simple so you can focus into understanding of the different services from AWS, but a basic understanding about the following topics is required or good to have. As we're talking about technology and computing services, general IT knowledge is necessary. By general IT, I mean the basics about programming language and logic, algorithms, and learning or working experience in the IT field. It will also give you an overview about data science concepts, but if these concepts are already familiar to you, this will make your journey more smoother. It's not mandatory, but it's important to have generic knowledge about AWS. More specifically about how to access your account and services, and the basics about S3 and EC2 solutions.
I would then like to recommend you two courses from CloudAcademy that can help you to better understand the AWS basics requirements for this course, AWS Technical Fundamentals, AWS 110 course, and AWS Networking Fundamentals, AWS 160. The course audience is quite wide. I tried to keep it simple and to maintain a good balance between the deepness of the content, not to scare beginners, so you'll not get scared by complex and very deep big data topics, and not to keep away data scientists that have already experience with one or more AWS services. If you're already a skilled data scientist, but a novice in AWS Cloud, this course will open your mind to the possibilities you can make to transform your problems from a current on-premises or auto cloud providers to bring them to AWS. And if you're preparing to take an associate or pro certification, this course will refresh concepts or give you new insights about the services.
This course's scope starts with an overview about data science and analytics concepts. This is focused mostly for our beginners, so you will not get lost during the course. After this, we'll give an introduction to analytics on AWS, so how AWS structures its offering, and at the end we'll provide an overview covering each service from the AWS analytics portfolio. So we'll guide you through the services providing you theory and some practice.
And finishing our introduction video, the learning objectives, what we will learn through this course. So I'd be very happy if at the end you get these basic learning objectives. So understand the basics of big data and analytics, then comprehend how these big data concepts and big data structures are applies to AWS, and how AWS has constructed its portfolio. And for sure, get hands on experience with the course.
So I'd recommend that you create an AWS account at this moment and you can use the free trial for several services, so we'll have no cost. Take always the remark to discredit resources after you use them. And let's go to the next video, we'll explore the concepts and play a bit with the services. So thank you. See you in the next video.
About the Author
Fernando has a solid experience with infrastructure and applications management on heterogeneous environments, working with Cloud-based solutions since the beginning of the Cloud revolution. Currently at Beck et al. Services, Fernando helps enterprises to make a safe journey to the Cloud, architecting and migrating workloads from on-premises to public Cloud providers.