Coursera

AWS: Data Collection Systems (Coursera)

Offered by Whizlabs,
AWS: Data Collection Systems (Coursera)

AWS: Data Collection Systems Course is the first course of the AWS Certified Data Analytics Speciality Specialization. This Course is designed to describe data collection systems and their characteristics in detail. This course is basically divided into three modules and each module is further segmented by Lessons and Video Lectures.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

This course facilitates learners with approximately 3:30-4:00 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners.

Module 1: Data Collection Systems and Data Streams in AWS
Module 2: Data Integration Services in AWS
Module 3: Data Compression and Transformation in AWS
e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming.
Course 1 of 5 in the Exam Prep DAS-C01: AWS Certified Data Analytics Specialty Specialization.

What You Will Learn

  • Describe data collection stages and compare their systems.
  • Implement Kinesis Data streams with Kinesis Producer Library and KCL
  • Describe Kinesis Data Firehouse and compare their functions
  • Implement the AWS Glue, experiment their functions with others services

Syllabus

WEEK 1
Data Collection Systems and Data Streams in AWS
Welcome to Week 1 of the AWS: Data Collection Systems. This week, we will learn about data collection systems and implement Kinesis Data Streams and Kinesis Data Firehose. We will gain hands-on experience with real-time data streaming and learn how to effectively load stream data into data stores and processing services. By the end of the week, we should have a better understanding of how to use Kinesis services to process real-time data.

WEEK 2
Data Integration Services in AWS
Welcome to Week 2 of the AWS: Data Collection Systems.This week, we will explore data integration services and their characteristics. This will involve analyzing the frequency, volume, batch, streaming, and transactional data to determine the appropriate integration services needed. We will also gain hands-on experience with implementing the AWS Glue service, a fully managed ETL service that makes it easy to move data between data stores. By the end of the module, we should have a solid understanding of how to effectively integrate different types of data using AWS Glue and other data integration services.

WEEK 3
Data Compression and Transformation in AWS
Welcome to Week 3 of the AWS: Data Collection Systems. This week, we will learn how to compare different data collection systems and choose the appropriate one for our needs. We will also explore how to implement data order, format, and compression techniques to optimize data ingestion processes. Additionally, we will analyze data transformation while ingesting the data in AWS to ensure the data is in a usable format for downstream applications. By the end of the week, we should have a solid understanding of how to optimize data ingestion processes and ensure the data is in a usable format for downstream applications.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Statistical Inference (Coursera) Coursera
Johns Hopkins University

Statistical Inference (Coursera)

Statistics & Data Analysis Data Science

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference.

Jun 22nd 2026
4 Weeks
Statistics Probability Data Analysis
Details
Big Data Modeling and Management Systems (Coursera) Coursera
University of California, San Diego

Big Data Modeling and Management Systems (Coursera)

Statistics & Data Analysis Data Science

Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools.

Jun 22nd 2026
5-12 Weeks
Big Data Data Management Data Modeling
Details
Data Manipulation at Scale: Systems and Algorithms (Coursera) Coursera
University of Washington

Data Manipulation at Scale: Systems and Algorithms (Coursera)

Statistics & Data Analysis Data Science

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales.

Jun 22nd 2026
4 Weeks
Algebra Algorithms Databases
Details
Julia Scientific Programming (Coursera) Coursera
University of Cape Town

Julia Scientific Programming (Coursera)

Statistics & Data Analysis Data Science

This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more.

Jun 22nd 2026
4 Weeks
IPython Data Analysis Computer Programming
Details
Marketing Analytics (Coursera) Coursera
University of Virginia

Marketing Analytics (Coursera)

Marketing & Communication Business

Organizations large and small are inundated with data about consumer choices. But that wealth of information does not always translate into better decisions. Knowing how to interpret data is the challenge -- and marketers in particular are increasingly expected to use analytics to inform and justify their decisions. Marketing analytics enables marketers to measure, manage and analyze marketing performance to maximize its effectiveness and optimize return on investment (ROI). Beyond the obvious sales and lead generation applications, marketing analytics can offer profound insights into customer preferences and trends, which can be further utilized for future marketing and business decisions.

Jun 22nd 2026
5-12 Weeks
Marketing Regression Data Analysis
Details
Business Intelligence Concepts, Tools, and Applications (Coursera) Coursera
University of Colorado System

Business Intelligence Concepts, Tools, and Applications (Coursera)

Statistics & Data Analysis Data Science

This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer. You’ll have the opportunity to work with large data sets in a data warehouse environment and will learn the use of MicroStrategy's Online Analytical Processing (OLAP) and Visualization capabilities to create visualizations and dashboards.

Jun 22nd 2026
5-12 Weeks
Data Analysis Decision Making Business Intelligence
Details
Introduction to Data Analysis Using Excel (Coursera) Coursera
Rice University

Introduction to Data Analysis Using Excel (Coursera)

Statistics & Data Analysis

The use of Excel is widespread in the industry. It is a very powerful data analysis tool and almost all big and small businesses use Excel in their day to day functioning. This course is designed to give you a working knowledge of Excel with the aim of getting to use it for more advance topics in Business Statistics. The course is designed keeping in mind two kinds of learners - those who have very little functional knowledge of Excel and those who use Excel regularly but at a peripheral level and wish to enhance their skills.

Jun 22nd 2026
4 Weeks
Spreadsheets Excel Data Analysis
Details
Introduction to Data Science in Python (Coursera) Coursera
University of Michigan

Introduction to Data Science in Python (Coursera)

CS: Software Engineering Statistics & Data Analysis

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

Jun 22nd 2026
4 Weeks
Python Data Analysis Data Science
Details
Framework for Data Collection and Analysis (Coursera) Coursera
University of Maryland, College Park

Framework for Data Collection and Analysis (Coursera)

Statistics & Data Analysis Data Science

This course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research question, how to turn your research question into measurable pieces, and how to think about an analysis plan.

Jun 22nd 2026
4 Weeks
Analysis Data Analysis Analytics
Details
Introduction to Spreadsheets and Models (Coursera) Coursera
University of Pennsylvania

Introduction to Spreadsheets and Models (Coursera)

Management & Leadership Business

The simple spreadsheet is one of the most powerful data analysis tools that exists, and it’s available to almost anyone. Major corporations and small businesses alike use spreadsheet models to determine where key measures of their success are now, and where they are likely to be in the future. But in order to get the most out of a spreadsheet, you have know how to use it. This course is designed to give you an introduction to basic spreadsheet tools and formulas so that you can begin harness the power of spreadsheets to map the data you have now and to predict the data you may have in the future.

Jun 22nd 2026
4 Weeks
Business Models Spreadsheets
Details
AWS Cloud Technical Essentials (Coursera) Coursera
AWS

AWS Cloud Technical Essentials (Coursera)

CS: Information & Technology

Are you in a technical role and want to learn the fundamentals of AWS? Do you aspire to have a job or career as a cloud developer, architect, or in an operations role? If so, AWS Cloud Technical Essentials is an ideal way to start. This course was designed for those at the beginning of their cloud-learning journey - no prior knowledge of cloud computing or AWS products and services required!

Jun 23rd 2026
5-12 Weeks
Cloud Databases Cloud Computing
Details