Complete AWS Big Data and Analytics Certification
What you'll learn
- On completion of this course you would be able to develop and deploy your applications over Amazon Cloud- Amazon Web Services.
- You would be in a position to take AWS Big Data Analytics Speciality Exam and qualify with good marks.
- Having command over various options, services and tools available including kinesis, athena, etc.
- After learning various concepts, you would be better prepared for AWS Certification exams
Requirements
- No prerequisites at all. You just need a little experience of doing GOOGLE search only ! But if u are aware of some cloud based or web development tools and technologies, it is helpful.
Description
In this course, we would explore Amazon Cloud- Amazon Web Services. We would explore AWS Big Data and Analytics Certification that one can take, exploring the learning path in the domain of big data and analytics .
We would also explore how we can prepare for this aws certification, what are the services covered, exam pattern, weight-age, syllabus, etc
In this course we will learn and practice all the tools of AWS Analytics which is being offered by AWS Cloud. There will be both theoretical and practical section of each AWS Analytics tools.This course is for those who wanted to groom their analytics skills .
Analytics plays very important role in the world of big data. There is no use of big data if we can not extract proper or meaningful insights from that. In short more data means better analysis, better analysis means better decision which makes organisation profitable.
Analytics tools like
Amazon Athena (Querying data instantly and get results in seconds)
Amazon CloudSearch (Makes it simple and cost-effective to set up, manage, and scale a search solution for your website or application)
Amazon ElasticSearch (Search, Analyse, and Visualise data in real-time.)
Amazon Kinesis (Easily collecting, processing, and analysing video and data streams in real time)
Amazon QuickSight (Fast, Cloud-powered BI service that makes it easy to build visualisations and quickly get business insights from your data.)
Amazon Glue (Simple, flexible, and cost-effective ETL)
This course also contains many practicals to groom your analytics skills.
And also
COMPUTE Services(EC2, Beanstalk, Lambda, Container, Lightsail, VPC), AWS CLI and many more topics
This course is generally for AWS certification aspirants providing them all the necessary information regarding various certifications in different domains before taking actual exam, in a manner to maximize the benefits of certification and chances of being certified.
Who this course is for:
- Anyone who may take AWS Cloud Big Data Analytics Speciality Exam and would be preparing for it.
- Anyone who just wants to learn and test Amazon Web Services Platform or any developer willing to develop his/her application over Amazon Cloud- Amazon Web Services.
Instructors
- 3.8 Instructor Rating
- 4,000 Reviews
- 126,043 Students
- 111 Courses
I am Self-Taught developer who had worked on various platforms using varied languages, and involved in various Projects both Open Source and Proprietary.
I have developed Web and Android Applications, chrome Extension, worked on various frameworks, fixed bugs for some projects, and explored numerous others. I think education and learning should be free and open, not be bound with restrictions like attending classes or going to college, People from all age groups, gender, faith, race, nations, etc must get equal privilege. When entire world would act this way like being a single FAMILY, we would truly realize VALUE of Knowledge and Human Life.
Currently I am teaching more than 99,000 students from 174 countries across the world.
- 3.7 Instructor Rating
- 2,701 Reviews
- 99,020 Students
- 71 Courses
I am an Instructor, Devops engineer, machine learning enthusiast, cloud expert and passionate developer.
I have authored 60+ courses with over 80,000+ students worldwide across 175+ countries on wide array of technologies like containerization, machine learning, Linux, programming languages and cloud computing platforms like Microsoft Azure, Amazon Web Service and IBM Cloud.