


This course is a comprehensive and rigorous training program designed to prepare aspiring data analytics professionals for the AWS Certified Data Analytics Specialty certification exam (DAS-C01). This course offers a comprehensive set of mock exams carefully curated to mimic the structure, content, and difficulty level of the actual certification exam.
Through this course, candidates gain invaluable hands-on experience and a deeper understanding of AWS data analytics services and best practices. Each mock exam consists of challenging questions that cover a wide range of topics, including data collection, storage, processing, visualization, and security on the AWS platform.
Students can assess their knowledge and proficiency in data analytics techniques and tools, as well as their ability to design and implement scalable, cost-effective, and reliable data solutions on AWS. By simulating real-world scenarios, the course prepares candidates to confidently tackle complex challenges they might encounter in their professional careers. With detailed explanations and rationales for each question, learners can identify areas for improvement and focus their efforts on strengthening their weak points.
Overall, the AWS Certified Data Analytics Specialty DAS-C01 - Mock Exams course equips aspiring data analytics specialists with the knowledge, skills, and confidence needed to excel in the certification exam and demonstrate their proficiency in leveraging AWS services for data analytics projects.
Queuing messages with Simple Queue Service (SQS)
Analyzing streaming data in real-time with Kinesis Analytics
Searching and analyzing petabyte-scale data with Amazon Elasticsearch Service
Querying S3 data lakes with Amazon Athena
Hosting massive-scale data warehouses with Redshift and Redshift Spectrum
Integrating smaller data with your big data, using the Relational Database Service (RDS) and Aurora
Visualizing your data interactively with Quicksight
Keeping your data secure with encryption, KMS, HSM, IAM, Cognito, STS, and more
Streaming massive data with AWS Kinesis
Wrangling the explosion data from the Internet of Things (IOT)
Transitioning from small to big data with the AWS Database Migration Service (DMS)
Storing massive data lakes with the Simple Storage Service (S3)
Optimizing transactional queries with DynamoDB
Tying your big data systems together with AWS Lambda
Making unstructured data query-able with AWS Glue
Processing data at unlimited scale with Elastic MapReduce, including Apache Spark, Hive, HBase, Presto, Zeppelin, Splunk, and Flume
Applying neural networks at massive scale with Deep Learning, MXNet, and Tensorflow
Applying advanced machine learning algorithms at scale with Amazon SageMaker
Thank you for taking the time to read about the course. We hope you now have enough motivation to get into the learning right away. If so, click the Enroll Now button at the top of the page to get started!