Big Data on AWS - Training and Certification
Big Data on AWS – Training and Certification Online by Checkmate IT Tech offers a transformative journey, elevating your expertise and mastering essential skills. Position yourself for success in the dynamic field of AWS by enrolling today. Unlock new career opportunities!
- 10+ Courses
- 30+ Projects
- 400 Hours
Data Engineers: Data engineers are experts in creating and overseeing massive data pipelines who wish to become familiar with AWS services to improve performance and scalability.
Scientists and data analysts: People who want to use AWS platforms for machine learning and predictive analytics, as well as to examine big datasets.
IT & Cloud Architects: Experts looking to use AWS services to create reliable big data architectures for businesses of all sizes.
Developers: Programmers who want to use AWS frameworks and APIs to create and implement big data applications.
Professionals in business intelligence: Those who use AWS big data tools to create dashboards, reports, and insights for decision-making.
Students and IT enthusiasts: People who want to begin a career in cloud computing and big data, with an emphasis on AWS technology.
Big Data Engineer: Creating and overseeing AWS data processing systems while guaranteeing scalability and effectiveness when working with big datasets.
Data Scientist: AWS Machine Learning and analytics services are used by data scientists to extract insights and predictive models from large amounts of data.
Cloud Data Architect: Using AWS technologies like Redshift, Kinesis, and EMR to design big data solutions that satisfy corporate needs.
AWS Solutions Architect: With a focus on big data applications, this professional assists businesses in putting effective and scalable AWS solutions into place.
Business Intelligence Analyst: Using AWS tools to analyze data, generate reports, and give stakeholders useful information.
DevOps Engineer (Big Data Focus): Managing big data deployments and workflows in AWS environments while maintaining operational efficiency is the responsibility of a DevOps Engineer with a focus on big data.
Machine Learning Engineer: Using AWS SageMaker and associated services to implement machine learning models and workflows.
In the USA and Canada, big data specialists with AWS experience are highly sought after in sectors like technology, healthcare, retail, and finance, which provide competitive pay and chances for professional advancement.
- An overview of the ideas and structure behind big data
- An overview of the big data ecosystem at Amazon Web Services
- Big data has three main features: volume, velocity, and variety.
- A look at cloud-based data analytics
- Getting to know Amazon S3 for storing data
- Constructing a data lake framework
- Using Amazon S3 for storage management
- Amazon Redshift for data warehousing
- Using AWS Glue to organize data
- Ways to get data into a system
- Basics of distributed data processing
- Using Amazon EMR to process data
- Getting to Know Apache Hadoop and Apache Spark
- Methods for processing batch data
- Making big data workflows work better
- Data ingestion in real time
- Using Amazon Kinesis for stream processing
- Using AWS Lambda to process data without a server
- Architecture based on events
- Use cases for real-time analytics
- Processes for Extract, Transform, and Load (ETL)
- Using AWS Glue to get data ready
- Pipelines for changing data
- Orchestration of workflows
- Checking and improving the quality of data
- Using Amazon Athena to query data
- Business intelligence and reporting
- Using Amazon QuickSight for visualisation
- Dashboards for analytics
- Making decisions based on data
- Best ways to keep data safe
- AWS Identity and Access Management (IAM)
- Encryption and following the rules
- Fine-tuning performance for big data jobs
- Ways to cut costs
- Final Project presentation and evaluation
- Certification preparation
- Mock Interviews & Job Placement
It is a course that teaches how to use Amazon Web Services to store, process and analyze large datasets.
People who work with big data technologies include data engineers, data analysts, cloud engineers, and IT professionals.
The duration is 2 months (8 weeks), with sessions held 2 times per week (either during week or weekends), including theory, hands-on practice and project work.
Yes, upon successful completion, you’ll receive a Certificate of Completion from Checkmate IT Tech. We also guide you on pursuing global certifications like IIBA-AAC and ICAgile-BA.
Yes, the training includes real-world exercises that use Amazon Web Services.
We offer online training classes to promote easy access to all candidates. Recordings are also made available for revision or if you miss a session.
Yes. We provide resume reviews, mock interviews, LinkedIn optimization, and guidance on job portals to help boost your chances in the job market.
Students will learn about data lakes, ETL pipelines, streaming analytics, data visualisation and big data architecture.
Yes, a lot of people use Amazon Web Services for big data processing and analytics that can grow, particularly because it offers scalable storage solutions, powerful computing resources, and a variety of tools for data analysis.
You can enroll via our website or contact our support team directly via email or phone. We’ll guide you through the quick and easy registration process.
Email info@checkmateittech.com OR Call Us +1-347-4082054
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Job opportunities in USA and Canada
Big Data Engineer: Creating and overseeing AWS data processing systems while guaranteeing scalability and effectiveness when working with big datasets.
Data Scientist: AWS Machine Learning and analytics services are used by data scientists to extract insights and predictive models from large amounts of data.
Cloud Data Architect: Using AWS technologies like Redshift, Kinesis, and EMR to design big data solutions that satisfy corporate needs.
AWS Solutions Architect: With a focus on big data applications, this professional assists businesses in putting effective and scalable AWS solutions into place.
Business Intelligence Analyst: Using AWS tools to analyze data, generate reports, and give stakeholders useful information.
DevOps Engineer (Big Data Focus): Managing big data deployments and workflows in AWS environments while maintaining operational efficiency is the responsibility of a DevOps Engineer with a focus on big data.
Machine Learning Engineer: Using AWS SageMaker and associated services to implement machine learning models and workflows.
In the USA and Canada, big data specialists with AWS experience are highly sought after in sectors like technology, healthcare, retail, and finance, which provide competitive pay and chances for professional advancement.
