This database design course by Caleb Curry will help you understand database concepts and give you a deeper grasp of database design.

Contents / Time stamps:

⌨️ (0:00:00) Introduction
⌨️ (0:03:12) What is a Database?
⌨️ (0:11:04) What is a Relational Database?
⌨️ (0:23:42) RDBMS
⌨️ (0:37:32) Introduction to SQL
⌨️ (0:44:01) Naming Conventions
⌨️ (0:47:16) What is Database Design?
⌨️ (1:00:26) Data Integrity
⌨️ (1:13:28) Database Terms
⌨️ (1:28:28) More Database Terms
⌨️ (1:38:46) Atomic Values
⌨️ (1:44:25) Relationships
⌨️ (1:50:35) One-to-One Relationships
⌨️ (1:53:45) One-to-Many Relationships
⌨️ (1:57:50) Many-to-Many Relationships
⌨️ (2:02:24) Designing One-to-One Relationships
⌨️ (2:13:40) Designing One-to-Many Relationships
⌨️ (2:23:50) Parent Tables and Child Tables
⌨️ (2:30:42) Designing Many-to-Many Relationships
⌨️ (2:46:23) Summary of Relationships
⌨️ (2:54:42) Introduction to Keys
⌨️ (3:07:24) Primary Key Index
⌨️ (3:13:42) Look up Table
⌨️ (3:30:19) Superkey and Candidate Key
⌨️ (3:48:59) Primary Key and Alternate Key
⌨️ (3:56:34) Surrogate Key and Natural Key
⌨️ (4:03:43) Should I use Surrogate Keys or Natural Keys?
⌨️ (4:13:07) Foreign Key
⌨️ (4:25:15) NOT NULL Foreign Key
⌨️ (4:38:17) Foreign Key Constraints
⌨️ (4:49:50) Simple Key, Composite Key, Compound Key
⌨️ (5:01:54) Review and Key Points….HA GET IT? KEY points!
⌨️ (5:10:28) Introduction to Entity Relationship Modeling
⌨️ (5:17:34) Cardinality
⌨️ (5:24:41) Modality
⌨️ (5:35:14) Introduction to Database Normalization
⌨️ (5:39:48) 1NF (First Normal Form of Database Normalization)
⌨️ (5:46:34) 2NF (Second Normal Form of Database Normalization)
⌨️ (5:55:00) 3NF (Third Normal Form of Database Normalization)
⌨️ (6:01:12) Indexes (Clustered, Nonclustered, Composite Index)
⌨️ (6:14:36) Data Types
⌨️ (6:25:55) Introduction to Joins
⌨️ (6:39:23) Inner Join
⌨️ (6:54:48) Inner Join on 3 Tables
⌨️ (7:07:41) Inner Join on 3 Tables (Example)
⌨️ (7:23:53) Introduction to Outer Joins
⌨️ (7:29:46) Right Outer Join
⌨️ (7:35:33) JOIN with NOT NULL Columns
⌨️ (7:42:40) Outer Join Across 3 Tables
⌨️ (7:48:24) Alias
⌨️ (7:52:13) Self Join

In this episode of Data Exposed with Tolga Tekin, learn about the ability to deploy Azure Arc Data services via Kubernetes to any hardware platform.

Time stamps:

  • [00:55] What is Azure Arc
  • [02:20] Azure data services anywhere at a glance
  • [03:28] On-premises vs Azure
  • [04:02] Azure Arc-enabled data services architecture
  • [06:07] Management capabilities comparison by deployment model
  • [08:22] Customer scenarios with Azure Arc
  • [09:53] Example – managing different infrastructures at different locations
  • [11:51] Getting started
Resources:

Leila Gharani shows us how to use Microsoft Forms you can collect data from different people via fillable forms that you can control from Excel.

With Microsoft Forms you can easily create surveys, quizzes and polls. You can export the data to Excel to analyze and share the results with your audience. No programming is necessary, no VBA, no add-ons. Just a Microsoft 365 account (free or paid).

We’ll cover how you can use Microsoft forms to add dropdowns, multiple choice, calendar date selection, number checks, net promoter score, and even star ratings.

Time Stamps

  • 00:00 How to Use Microsoft Forms
  • 01:19 How to Get Started with Microsoft Forms
  • 01:50 Automatic Connection between Excel and Microsoft Forms
  • 02:58 Create Data Entry Form with Microsoft Forms
  • 04:10 Star rating in Microsoft Forms
  • 04:35 Choice in Microsoft Forms
  • 05:08 How to add a drop-down to Microsoft Forms
  • 06:10 Date picker with calendar pop-up
  • 06:30 Add a text box and validate numbers
  • 06:50 Add a Likert scale to Microsoft Forms
  • 07:15 Net Promoter score in Microsoft Forms
  • 07:50 How to Add a Theme to Microsoft Forms
  • 08:09 How to Share a Data Entry Form with Microsoft Forms
  • 09:24 How to Fill Out a Data Entry Form
  • 10:34 Analyze the Responses from Microsoft Forms in Excel
  • 13:39 Grid

Here’s an interesting look at how data played (and continues to play) in space exploration.

00:00 – Introduction and Agenda for the episode
02:49 – Setup local environment guidelines
03:56 – Setup for this project and intro to Python notebooks in VSCode
06:40 – Choosing data for analysis – NASA Lunar Rock Curation
07:51 – Discussion on importance of weight in space exploration
08:56 – Defining problem to solve through data science practices
10:45 – Import and explore data into notebook with pandas
14:12 – Manipulate rock sample data to match rocket data
18:30 – Create dataframe to view data based on unique missions
20:23 – Add total sample amount for each mission
23:05 – Comparing missions
24:09 – Removing not-a-number values
25:04 – Add rocket ship data into dataframe
26:47 – Add rocket payload data and determine ratios
29:00 – Add Artemis data
30:42 – Estimate sample weight per Artemis mission
31:37 – Determining the right samples to collect
36:00 – Exploring the cut of samples to prioritize
38:00 – Finalizing the samples that represent the profile for new samples
40:09 – Create the dataframe final profile for new sample gathering
44:50 – Determine recommendations based on Artemis constraints
47:01 – Recap

freeCodeCamp.org has made the Practical Deep Learning for Coders is a course from fast.ai available .

This course was created to make deep learning accessible to as many people as possible. The only prerequisite for this course is that you know how to code (a year of experience is enough), preferably in Python, and that you have at least followed a high school math course.

This course was developed by Jeremy Howard and Sylvain Gugger. Jeremy has been using and teaching machine learning for around 30 years. He is the former president of Kaggle, the world’s largest machine learning community. Sylvain Gugger is a researcher who has written 10 math textbooks.

Jeff Geerling puts the Compute Module 4 through its paces and compares it to the Raspberry Pi 4 and Compute Module 3+, highlighting some great new features like a PCI Express 1x slot on the IO board and NVMe support.

Content index:

  • 00:00 – Introduction
  • 03:29 – A Complete Redesign
  • 04:35 – PCIe, USB 3, and NVMe
  • 10:04 – Networking – Wired and Wireless
  • 12:37 – CPU Performance
  • 13:41 – eMMC Performance
  • 14:54 – USB Boot
  • 15:50 – NAS/NFS Performance
  • 17:05 – IO Board Features
  • 19:47 – Summary and Final Thoughts
  • 20:50 – Bloopers

Linked servers enable the SQL Server and Azure SQL Database Managed Instance to read data from remote data sources and execute commands against the remote database servers.

In this video, Anna Thomas and Colin Murphy go over configuring linked servers in Azure SQL Database Managed Instance.

At the end, Anna briefly mentions creating a linked server to the readable secondary replica for read-heavy workloads.

Here’s a great tutorial on how to use the Azure Machine Learning Designer interface to create machine learning models without code.

You don’t need to write code to build your model, though there’s the option to bring in custom R or Python where necessary. It’s a replacement for the original ML Studio tool, adding deeper integration into Azure’s machine learning SDKs and with support for more than CPU-based models, offering GPU-powered machine learning and automated model training and tuning.