DAT 210 - Cloud Computing for Data Scientists

Delivery Options Online Synchronous

UCalgary Continuing Education

Course Description

The Digital Transformation is here! Equip yourself with the necessary skills to build data science applications utilizing Amazon Web Services (AWS) cloud platform. Learn the fundamentals of cloud computing, with a focus on the AWS cloud platform.

Students will work with AWS's python API to provision services and build a simple cloud-based data application. Collect and ingest data using EC2 and Kinesis Firehose, store data in S3 and visualize data using Quicksight.

This course is delivered in collaboration with WeCloudData.

Course Details

Learning Outcomes

By the completion of this course, successful students will be able to:

Describe the current cloud computing landscape and products and services offered by different vendors such as Microsoft Azure, Amazon Web Services, and Google Cloud
Explain AWS services such as EC2 (compute), S3 (storage), Kinesis (ingestion), Athena (analytics), Quicksight (visualization)
Apply the principles of cloud computing and the role it plays in modern data science and engineering
Create an AI application in cloud computing, using tools like AWS Python SDK boto3, AWS’s SageMaker, and Rekognition services
Construct data analytics pipelines by interacting with cloud services, such as AWS EC2, S3, Kinesis, Athena, Redshift, and AWS’s Python SDK boto3

Topics

Introduction to Cloud Computing

Introduction to AWS
Cloud Storage with S3
Cloud Compute with EC2
Managed Data Warehouse with Redshift
Serverless Analytics with Presto and Athena
Visualization in AWS with QuickSight
Programming for the cloud
Build your first cloud-based data application

Who is this course for?

Data scientists who want to learn how to move their data science applications to the cloud
IT and Engineering Professionals looking to gain cloud-based data science experience
Data and business analytics professionals
Recent graduates and academics in Computer Science

Notes

Software Requirements

This course is built around AWS solutions and services. To complete the lab activities and mini-project, you will require:

A development environment that includes Visual Studio Code or PyCharm
An AWS account (free tier services)

Prerequisites

There are no mandatory prerequisites for this course. However, you are required to perform a self-assessment to ensure you meet the requirements to enroll.

Self-assessment for enrolment

A minimum of 1-year experience with the following skillsets: python programming, relational database, data visualization using python/excel, machine learning algorithms

Recommended Pre-requisites

DAT 110 Data Analytics and Visualization in Business
DAT 120 Practical Machine Learning for Business

Applies Towards the Following Program(s)

Big Data in Cloud : Required

Enrol Now - Select a section to enrol in

DAT 210 - 006

Apr 07, 2026

Online Synchronous

Available

Apr 07, 2026 to May 02, 2026

Online Synchronous

5:00PM to 8:00PM

Apr 07, 2026 to Apr 28, 2026

Online Synchronous

8:00AM to 4:00PM

Apr 11, 2026 to May 02, 2026

Schedule and Location

View Details

45.0

Online Synchronous

Flat Fee non-credit

$1,495.00

Required Software

Zoom web conferencing software Laptop or computer installed with Windows or Mac OS A development environment that includes Visual Studio Code or PyCharm and AWS account (free tier services)

Reading List / Textbook

No textbook required.

Section Notes

Classes are held online in real time (Mountain Time) at the specified time and dates.

This course uses:

D2L Learning Management System
Zoom web conferencing software

This course is delivered in an online blended format, meaning that some classes are taught in a live virtual session using Zoom, and some work have to be completed in a designated online e-learning platform on your own time.

For the best experience, you will require access to a computer with Internet connection, a headset with speakers and microphone, webcam, and a monitor large enough to display multiple applications (or the use of two monitors). Your computer and internet connection should meet certain requirements. See the recommended requirements.

For more information, please visit our Online Learning Resources.

Students unfamiliar with online learning are encouraged to take our free Digital Skills for Learning Online course.

Unless otherwise stated, notice of withdrawal or transfer from a course must be received at least seven calendar days prior to the start date of the course.