Cloud Basics for Data Professionals

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Maven Analytics,Chris Bruehl

1:53:25

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1. Getting Started

1. Course Introduction.mp4

01:45

2. Course Structure & Outline.mp4

01:15

3. READ ME Important Notes for New Students.html

4.1 Cloud Basics for Data Professionals.pdf

4. DOWNLOAD Course Resources.html

5. Setting Expectations.mp4

01:04

2. Cloud 101

1. What is The Cloud.mp4

01:15

2. The Rise of The Cloud.mp4

01:20

3. Why Do Companies Choose The Cloud.mp4

02:24

4. On Premise vs. Cloud Computing.mp4

04:52

5. Data Roles & The Cloud.mp4

02:37

6. Key Takeaways.mp4

01:28

7. Cloud 101.html

3. Cloud Architecture

1. Your Computer.mp4

01:34

2. On Premise Servers.mp4

02:25

3. Cloud Data Centers & Networks.mp4

02:02

4. Is The Cloud Secure.mp4

00:58

5. Cloud Storage.mp4

04:58

6. Cloud Compute.mp4

01:34

7. Virtualization.mp4

01:58

8. PRO TIP Cost Control.mp4

02:14

9. DEMO Inside a Cloud Platform.mp4

03:42

10. Types of Cloud Services.mp4

03:24

11. Types of Cloud Infrastructure.mp4

03:29

12. Key Takeaways.mp4

02:00

13. Cloud Architecture.html

4. The Cloud Landscape

1. Public Cloud Providers.mp4

03:04

2. Comparing Big 3 Service Names.mp4

04:29

3. Private Cloud Providers.mp4

03:16

4. Cloud Data Platforms (PaaS).mp4

03:10

5. Cloud Software Products (SaaS).mp4

03:39

6. The Risk of Vendor Lock-In.mp4

05:29

7. Key Takeaways.mp4

01:09

8. The Cloud Landscape.html

5. Common Cloud Data Stacks

1. Choosing a Stack.mp4

02:56

2. DEMO Amazon Web Services (AWS).mp4

05:50

3. DEMO Microsoft Azure.mp4

07:44

4. DEMO Google Cloud Platform (GCP).mp4

04:54

5. DEMO Snowflake.mp4

07:43

6. CASE STUDY AWS & Azure.mp4

04:05

7. CASE STUDY GCP & Snowflake.mp4

03:30

8. Key Takeaways.mp4

01:59

6. Wrapping Up

1. Key Course Takeaways.mp4

02:10

2. BONUS LESSON.html

Description

Learn basic cloud technology for data science & analytics, and get to know key players like AWS, GCP, Azure & Snowflake

What You'll Learn?

Learn why so many companies are leveraging cloud technology for data science & analytics
Understand the basic use cases of cloud computing for different data roles (analysts, data scientists & data engineers)
Compare the different types of cloud services (IaaS, PaaS, and SaaS) and cloud infrastructure (private, public & hybrid)
Explore the similarities and differences between major players in the cloud landscape, including Amazon Web Services, Microsoft Azure & Google Cloud
Demo real-world data analytics workflows using Azure, GCP, AWS and Snowflake

Who is this for?

Everyday people looking to build a basic understanding of cloud technology for data analytics

Leaders looking to learn more about the cloud landscape and ecosystem

Data professionals who want an introduction to modern cloud data stacks and workflows

Anyone looking to get familiar with major cloud players like AWS, Azure, GCP and Snowflake

What You Need to Know?

This is an entry-level course (no prerequisites)

Some experience working with data is helpful, but not required

More details

Description
This course is a high-level introduction to the world of cloud computing.

The cloud ecosystem has grown exponentially in recent years, now storing more than half of the worldâ€™s corporate data. Yet most people who interact with cloud services are unaware of whatâ€™s going on behind the scenes.

In this course, weâ€™ll set the stage by defining what cloud computing means and why companies rely on it, draw comparisons against traditional on-premise computing, and explore how different types of data professionals interact with cloud technology.

From there weâ€™ll dig into the core components of cloud architecture, compare different types of cloud services and infrastructure, and review important topics like security, virtualization, cost control, and more.

Next, weâ€™ll explore the modern cloud landscape, and compare services offered by key players like AWS, Microsoft Azure, and Google Cloud. Weâ€™ll introduce public and private cloud providers, data platforms and software products, and discuss how to mitigate the risk of vendor lock-in.

Last but not least, weâ€™ll walk through unique demos and real-world use cases to showcase how you can begin to leverage these services as a data professional, including workflows built on AWS, Azure, GCP and Snowflake.

COURSEÂ OUTLINE:

Cloud 101
Introduce the basics of cloud computing, including what it is, why companies use it, and the way different data roles interact with it

Cloud Architecture
Understand the core components of cloud computing and cloud infrastructure, as well as the types of cloud services and architecture

The Cloud Landscape
Review some of the major players in the cloud computing industry for data analytics, and compare their similarities and differences

Cloud Data Stacks
Demo simple data analytics pipelines using combinations of cloud products and services (or â€œstacksâ€), including AWS, MySQLÂ Workbench, GCP, Looker, Azure, Snowflake, and more

__________

Ready to dive in? Join todayÂ and get immediate, LIFETIME accessÂ to the following:

2 hours of high-quality video
4 real-world cloud demos & case studies
3 course quizzes
Cloud Basics for Data Professionals ebook (50+Â pages)
Expert support and Q&AÂ forum
30-day Udemy satisfaction guarantee

Whether youâ€™re an analyst or data scientist interested in cloud computing or a business leader looking to learn about the cloud landscape, this course is for you.

Happy learning!
-Chris Bruehl (Data Science Expert & Lead Python Instructor, Maven Analytics)
Who this course is for:
Everyday people looking to build a basic understanding of cloud technology for data analytics
Leaders looking to learn more about the cloud landscape and ecosystem
Data professionals who want an introduction to modern cloud data stacks and workflows
Anyone looking to get familiar with major cloud players like AWS, Azure, GCP and Snowflake

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Maven Analytics helps individuals and teams build expert-level analytics & business intelligence skills. We've helped more than 1,000,000 students around the world build job-ready skills, master sought-after tools like Excel, SQL, Power BI, Tableau & Python, and build the foundation for a successful career in data. At Maven Analytics, we empower everyday people to change the world with data.

Chris Bruehl

Instructor's Courses

Chris is a seasoned data scientist, having held Data Science roles in the financial services industry. He was first trained on SAS before falling in love with Python and making it his tool of choice. Chris transitioned from applying data science in the field, to teaching at a top tier data science bootcamp. He is passionate about teaching and is able to break down complex concepts into bite size lessons. He holds a Masters Degree in Analytics from NCSU.

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