Data Architecture for Data Scientists

Data Architecture for Data Scientists, available at $69.99, has an average rating of 4.47, with 37 lectures, 7 quizzes, based on 484 reviews, and has 2287 subscribers.

You will learn about Data Architecture in general, to be able to navigate your organizations data landscape Develop understanding of topics like Data Lake, Datawarehousing and even Data Lakehouse to be able to communicate with data engineering teams Understand the pricinciples of data governance topics like Data Mesh to better navigate the data governance paradigm Get introduced to technologies related to machine learning specific data infrastructure like feature stores and vector databases What is data architecture? What is a data warehouse (DWH) ? What is data lake? What is data lakehouse? What is data mesh? How is streaming data used in data science? What is a feature store? How is a feature store used in machine learning? What are vector databases?? This course is ideal for individuals who are Data Scientists who are transitioning from academia or business domains or Junior data scientists who would like to understand the topics surrounding data infrastructure or Citizen data scientists who wish to deploy machine learning models in production or Anyone who wishes to learn the basics of data architecture in a very short time or BI Analysts and BI developers who would like a quick overview of the enterprise data landscape or Folks who wish to get a quick overview of data architecture components in an enterprise. It is particularly useful for Data Scientists who are transitioning from academia or business domains or Junior data scientists who would like to understand the topics surrounding data infrastructure or Citizen data scientists who wish to deploy machine learning models in production or Anyone who wishes to learn the basics of data architecture in a very short time or BI Analysts and BI developers who would like a quick overview of the enterprise data landscape or Folks who wish to get a quick overview of data architecture components in an enterprise.

Enroll now: Data Architecture for Data Scientists

Summary

Title: Data Architecture for Data Scientists

Price: $69.99

Average Rating: 4.47

Number of Lectures: 37

Number of Quizzes: 7

Number of Published Lectures: 37

Number of Published Quizzes: 7

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 44

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

Data Architecture in general, to be able to navigate your organizations data landscape

Develop understanding of topics like Data Lake, Datawarehousing and even Data Lakehouse to be able to communicate with data engineering teams

Understand the pricinciples of data governance topics like Data Mesh to better navigate the data governance paradigm

Get introduced to technologies related to machine learning specific data infrastructure like feature stores and vector databases

What is data architecture? What is a data warehouse (DWH) ? What is data lake? What is data lakehouse? What is data mesh?

How is streaming data used in data science? What is a feature store? How is a feature store used in machine learning? What are vector databases??

Who Should Attend

Data Scientists who are transitioning from academia or business domains

Junior data scientists who would like to understand the topics surrounding data infrastructure

Citizen data scientists who wish to deploy machine learning models in production

Anyone who wishes to learn the basics of data architecture in a very short time

BI Analysts and BI developers who would like a quick overview of the enterprise data landscape

Folks who wish to get a quick overview of data architecture components in an enterprise.

Target Audiences

Data Scientists who are transitioning from academia or business domains

Junior data scientists who would like to understand the topics surrounding data infrastructure

Citizen data scientists who wish to deploy machine learning models in production

Anyone who wishes to learn the basics of data architecture in a very short time

BI Analysts and BI developers who would like a quick overview of the enterprise data landscape

Folks who wish to get a quick overview of data architecture components in an enterprise.

Machine learning models are only as good as the data they are trained on, which is why understanding data architecture is critical for data scientists building machine learning models.

This course will teach you:

The fundamentals of data architecture

A refresher on data types, including structured, unstructured, and semi-structured data

DataWarehouse Fundamentals

Data Lake Fundamentals

The differences between data warehouses and data lakes

DataLakehouse Fundamentals

Data Mesh fundamentals for decentralized governance of data including topics like data catalog, data contracts and data fabric.

The challenges of incorporating streaming data in data science

Some machine learning-specific data infrastructure, such as feature stores and vector databases

The course will help you:

Make informed decisions about the architecture of your data infrastructure to improve the accuracy and effectiveness of your models

Adopt modern technologies and practices to improve workflows

Develop a better understanding and empathy for data engineers

Improve your reputation as an all-around data scientist

Think of data architecture as the framework that supports the construction of a machine learning model. Just as a building needs a strong framework to support its structure, a machine learning model needs a solid data architecture to support its accuracy and effectiveness. Without a strong framework, the building is at risk of collapsing, and without a strong data architecture, machine learning models are at risk of producing inaccurate or biased results. By understanding the principles of data architecture, data scientists can ensure that their data infrastructure is robust, reliable, and capable of supporting the training and deployment of accurate and effective machine learning models.

By the end of this course, you’ll have the knowledge to help guide your team and organization in creating the right data architecture for deploying data science use cases.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Why enroll in this course?

Lecture 2: Course contents

Lecture 3: About the course creator

Lecture 4: Million dollar slide

Chapter 2: Data Types

Lecture 1: Structured data

Lecture 2: Unstructured data

Lecture 3: Semi-structured data

Lecture 4: Short explanation of JSON and XML structures

Lecture 5: Semi-structured data in machine learning

Lecture 6: Resources and Slides

Chapter 3: Datawarehouse

Lecture 1: Introduction to datawarehousing

Lecture 2: Datawarehousing for data scientists

Lecture 3: Cloud datawarehousing

Lecture 4: Resources and Slides

Chapter 4: Data Lake

Lecture 1: Introduction to a data lake

Lecture 2: The technology used to build a data lake

Lecture 3: Cloud Storage terminology – Buckets and blobs

Lecture 4: Resources and Slides

Chapter 5: Data Lakehouse

Lecture 1: Challenges with the data lake

Lecture 2: Introduction to the data lakehouse

Lecture 3: Resources and Slides

Chapter 6: Data Governance with the Data Mesh

Lecture 1: Introduction to Data Mesh

Lecture 2: Data Mesh principles : Domain ownership and data as a product

Lecture 3: Data Mesh principles : Self service and federated governance

Lecture 4: Data Catalog

Lecture 5: Data Contracts

Lecture 6: Data Fabric

Lecture 7: Resources and Slides

Chapter 7: Streaming data in Data Science

Lecture 1: Introduction to streaming data

Lecture 2: Kafka 101

Lecture 3: Lambda architecture

Lecture 4: Kappa architecture and comparison

Lecture 5: Word of caution and Resources

Chapter 8: Data infrastructure for Machine Learning

Lecture 1: Feature Store

Lecture 2: Vector Database

Chapter 9: Flowchart and Use case examples

Lecture 1: Data Architecture decision making flowchart

Lecture 2: Use case examples and applying the decision flow

Instructors

Biju Krishnan
AI Architect @ DataSiens

Rating Distribution

1 stars: 2 votes

2 stars: 4 votes

3 stars: 45 votes

4 stars: 188 votes

5 stars: 248 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!