Snowflake Cortex Masterclass 2024 Hands-On!

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Cristian Scutaru

20:12:52

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1. Introduction to Snowflake Cortex

1. Course Structure and Content.mp4

01:48

2. Welcome to This Course.mp4

02:26

3.1 GitHub Repository with all the source code for this course.html

3.2 My Medium Blog.html

3.3 Snowflake-Cortex-All-Slides.pdf

3. All About This Course (FAQ Post).html

4.1 Snowflake Preview Features.html

4.2 Snowflake Release Notes.html

4.3 Snowflake Whats New.html

4. Roadmap to Snowflake Cortex.mp4

07:26

5. Quick Tips SQL Query Without Typing SQL.mp4

01:09

6. Related Features and Technologies.mp4

07:25

7.1 Introduction to Snowflake Cortex FAQs.html

7.2 Snowflake Cortex.html

7. Overview of Snowflake Cortex.mp4

12:12

8. Quick Tips TRANSLATE LLM Function.mp4

01:03

9. Quick Checkpoint About ...Quick Checkpoints.mp4

00:26

10. Test Your Knowledge.html

2. ML Pipelines on Datasets (outside Snowflake)

1. About this Section.mp4

01:37

2. Quick Tips Correlation Heatmap.mp4

01:04

3. Introduction Machine Learning Basics.mp4

09:45

4. Introduction ML Pipeline Phases.mp4

10:19

5. Introduction ML Pipeline Architectures.mp4

10:00

6. Quick Checkpoint What if You Already Know All This.mp4

00:46

7. Data Collection Time Series Generation.mp4

05:24

8. Data Collection Make RegressionClassification.mp4

05:36

9. Data Collection Realistic Fake Data Generation.mp4

02:30

10. Data Collection Data Access.mp4

08:41

11. Data Collection Data Split.mp4

08:09

12. Data Collection Overview.mp4

04:16

13. Quick Tips Fake but Realistic Data Generation.mp4

00:55

14. Data Exploration Overview.mp4

12:18

15. Data Exploration Correlation Matrix Heatmap.mp4

06:27

16. Data Exploration Pandas Profiling.mp4

08:31

17. Quick Checkpoint About Pandas Profiling.mp4

00:41

18. Data Wrangling Overview.mp4

09:24

19. Data Wrangling Feature Engineering with Pandas DataFrame.mp4

06:07

20. Data Wrangling Data Preprocessing with Transformers.mp4

04:33

21. Data Wrangling Data Preprocessing with Pipeline.mp4

04:12

22. Quick Checkpoint About Basic ML on Datasets.mp4

00:54

23. Quick Tips SUMMARIZE LLM Function.mp4

01:04

24. Model Training Overview.mp4

07:43

25. Model Training Regression.mp4

05:14

26. Model Training Classification.mp4

03:05

27. Model Validation Manual Hyperparameter Optimization.mp4

03:53

28. Model Validation Manual Cross-Validation.mp4

06:31

29. Model Validation GridSearchCV for Regression.mp4

04:33

30. Model Validation RandomizedSearchCV for Classification.mp4

05:12

31. Quick Checkpoint About Model Validation.mp4

01:03

32.1 What is the difference between model validation and evaluation.html

32. Model Evaluation Performance Metrics for Regression.mp4

07:05

33. Model Evaluation Performance Metrics for Classification.mp4

06:09

34. Model Serving SaveLoad the Trained Model File.mp4

10:11

35. Quick Tips Signup for a Free Snowflake Trial Account.mp4

01:04

36. Test Your Knowledge.html

3. ML Pipelines using Snowpark (before Cortex)

1. About this Section.mp4

03:32

2. Quick Tips Uploading Files in Snowflake.mp4

01:14

3. Introduction Snowpark Components.mp4

09:22

4. Introduction Procedures and Functions from SQL.mp4

09:04

5. Introduction Snowpark for Python.mp4

10:09

6. Introduction Procedures and Functions from Python.mp4

13:21

7. Introduction Vectorized User-Defined Functions.mp4

10:40

8. Introduction Runtimes and Package Versions.mp4

06:15

9. Introduction Snowpark for ML Pipelines.mp4

08:14

10. Data Collection Populating with SQL Statements.mp4

07:47

11. Data Collection Synthetic Data Generation.mp4

05:39

12. Data Collection Faker Library in Python Worksheet.mp4

06:20

13. Quick Tips Easiest Way to Connect to Snowflake.mp4

01:16

14. Data Collection Uploading with SQL Scripts.mp4

12:22

15. Data Collection Uploading with Python Code.mp4

04:15

16. Data Collection Uploading from External Stages.mp4

03:36

17. Data Collection Uploading Other Datasets.mp4

07:01

18. Data Collection Sample Data Extraction.mp4

10:22

19. Data Collection Data Split.mp4

06:21

20. Quick Checkpoint About Ingesting Data in Snowflake.mp4

00:42

21. Quick Tips Correlation Heatmap in Snowflake.mp4

01:05

22. Data Exploration Snowsight Charts and Dashboards.mp4

05:27

23.1 Exploratory Data Analysis with Snowflake and Deepnote.html

23.2 Seamless Machine Learning Workflows with Snowpark & Deepnote.html

23. Data Exploration Snowflake Partner Notebooks.mp4

09:59

24.1 Build and Deploy ML with Ease Using Snowpark ML, Snowflake Notebooks, and Snowflake Feature Store.html

24.2 Diamond Price Prediction End-to-End Machine Learning with Snowpark ML in Snowflake Notebooks.html

24. Data Exploration Snowflake Notebooks.mp4

01:26

25. Data Exploration Overview.mp4

09:43

26. Quick Tips Data Profiling in Snowflake.mp4

01:13

27. Quick Checkpoint Pandas vs Snowpark Data Frames.mp4

00:41

28.1 Snowpark Python Top Three Tips for Optimal Performance.html

28. Feature Engineering Pandas vs Snowpark DataFrames.mp4

14:39

29.1 End to end Machine Learning with Scikit-Learn and Snowpark.html

29. Feature Engineering Using Pandas DataFrames.mp4

06:49

30.1 How to Create a Complex Query with Snowpark DataFrame in Python.html

30. Feature Engineering Using Snowpark DataFrames.mp4

07:53

31. Feature Engineering Scalability Check with Python Worksheets.mp4

08:12

32.1 Snowpark API The Object Model.html

32. Feature Engineering Overview.mp4

06:10

33.1 How to Generate Snowflake Stored Procs via Python Worksheets.html

33. Quick Checkpoint About the Python Worksheets.mp4

00:25

34. Quick Tips DataFrame Queries.mp4

01:06

35. Data Preprocessing When You Cannot Avoid Pandas.mp4

07:47

36. Model Training Sentiment Analysis in Local Mode.mp4

09:47

37.1 NLP and ML with Snowpark Python and Streamlit for Sentiment Analysis.html

37. Model Training Sentiment Analysis with Stored Procedure.mp4

09:03

38. Model Training Overview.mp4

06:24

39. Model Training Sentiment Analysis with Imported Modules.mp4

05:48

40.1 Getting Started with Snowpark for Python with Scikit-learn.html

40. Model Training House Predictions with Stored Procedure.mp4

11:17

41. Model Serving Overview.mp4

06:44

42. Model Serving Sentiment Predictions with UDFs.mp4

14:30

43. Model Serving Sentiment Predictions with SQL.mp4

04:28

44.1 Vectorized UDFs for Batching.html

44. Model Serving House Predictions with Vectorized UDF.mp4

06:51

45.1 Examining the performance benefits of the Cachetools library.html

45. Model Serving Introduction to Cachetools.mp4

12:22

46. Model Serving UDFs vs Vectorized UDFs.mp4

04:50

47. Test Your Knowledge.html

4. ML Pipelines with Snowpark ML (in Cortex)

1. About this Section.mp4

02:29

2. Quick Tips Python Worksheets.mp4

01:07

3. Introduction Snowpark ML APIs.mp4

10:21

4. Data Collection FileSystem.mp4

09:23

5. Data Collection FileSet and Framework Connectors.mp4

06:14

6. Data Collection SnowflakeFile.mp4

07:13

7. Data Collection Overview.mp4

07:32

8. Distributed Preprocessing Sklearn vs Snowpark ML.mp4

12:21

9. Distributed Preprocessing Snowpark vs Snowpark ML.mp4

04:50

10. Distributed Preprocessing Notebook Experiments.mp4

09:38

11. Distributed Preprocessing Overview.mp4

07:49

12. Model Training Sklearn vs Snowpark ML.mp4

05:32

13. Model Training Snowpark vs Snowpark ML.mp4

07:41

14. Model Training Notebook Experiment.mp4

07:13

15. Model Training Overview.mp4

02:13

16. Quick Tips Estimator Pattern in Snowpark ML Modeling.mp4

01:20

17. Quick Checkpoint About the Roadmap to Snowpark ML.mp4

00:34

18. Distributed HPO Sklearn vs Snowpark ML.mp4

16:21

19. Distributed HPO Snowpark vs Snowpark ML.mp4

07:40

20. Distributed HPO Notebook Experiment.mp4

04:57

21. Distributed HPO Overview.mp4

05:57

22. Distributed Metrics Sklearn vs Snowpark ML.mp4

11:14

23. Distributed Metrics Snowpark vs Snowpark ML.mp4

05:34

24. Distributed Metrics Notebook Experiment.mp4

04:43

25. Distributed Metrics Overview.mp4

03:37

26. Snowflake MLOps Overview.mp4

09:37

27. Snowflake MLOps Logging a Model.mp4

12:47

28. Snowflake MLOps The Model Registry.mp4

10:16

29. Snowflake MLOps Model Predictions from Registered Models.mp4

09:35

30. Snowflake MLOps Model Types and Providers.mp4

08:54

31. Quick Tips Prediction Functions from Model Registry.mp4

01:06

32. Cost of Snowpark ML.mp4

07:03

33. Quick Tips Warehouse Auto-Suspend Value.mp4

01:23

34.1 100 Snowflake Cost Optimization Techniques.html

34. Quick Checkpoint About Auto-Suspend in Warehouses.mp4

00:24

35. Test Your Knowledge.html

5. ML Functions (in Cortex)

1. About this Section.mp4

01:41

2. Quick Tips Simple Classification through Wizard.mp4

00:56

3. Introduction ML Classes.mp4

07:54

4. Introduction ML Class Methods.mp4

08:10

5. Introduction Snowflake SQL Classes.mp4

03:36

6. Introduction Snowflake SQL Class Instances.mp4

09:23

7. Quick Checkpoint About the ML-Powered Functions.mp4

00:34

8. Classification Binary Classifier.mp4

12:55

9. Classification Multiclass Classifier.mp4

08:03

10. Classification Bank Classifier.mp4

10:18

11. Classification Overview.mp4

10:31

12. Quick Tips Confusion Heatmap for Classification ML Class.mp4

01:11

13. Forecasting Time Series Data.mp4

17:24

14. Forecasting Prepare Sales Data.mp4

07:53

15. Forecasting Train Model and Predict Sales.mp4

15:41

16. Forecasting Train Model and Predict Temperatures.mp4

06:28

17. Forecasting Overview.mp4

05:28

18. Anomaly Detection Overview.mp4

08:11

19. Anomaly Detection Detect Outliers in Sales.mp4

11:05

20. Anomaly Detection Automation with Tasks and Alerts.mp4

05:07

21. Anomaly Detection Detect Outliers in Temperatures.mp4

06:52

22. Quick Tips Marking Outliers for Anomaly Detection.mp4

01:13

23. Quick Checkpoint About Forecasting and Anomaly Detection.mp4

00:38

24. Gradient Boosting Algorithm.mp4

05:57

25. Gradient Boosting Classifier & Regressor.mp4

04:48

26. Contribution Explorer Overview.mp4

12:43

27. Contribution Explorer What Led to a Change in Sales.mp4

12:25

28. Contribution Explorer What Makes a Customer Take to a Loan.mp4

06:51

29. Contribution Explorer How to Survive on Titanic.mp4

10:40

30.1 Why Snowflakes TOP_INSIGHTS is NOT a Time-Series Function!.html

30. Quick Checkpoint TOP_INSIGHTS is NOT a Time Series Function!.mp4

00:32

31. Access Rights Introduction to Roles.mp4

09:11

32. Access Rights Classification.mp4

15:29

33. Access Rights Forecasting and Anomaly Detection.mp4

07:23

34. Quick Checkpoint About Access Rights to ML Classes and Functions.mp4

00:49

35. Cost of ML Functions.mp4

07:36

36. Test Your Knowledge.html

6. LLM Functions and Extensions (in Cortex)

1. About this Section.mp4

03:07

2. Quick Tips SENTIMENT LLM Function.mp4

01:10

3. Introduction to LLM Functions Overview.mp4

08:40

4. Introduction to LLM Functions Quick Demo.mp4

09:33

5. Introduction to Data Science Important Milestones.mp4

04:57

6. Introduction to Data Science Deep Learning Review.mp4

04:43

7. Introduction to Data Science Generative AI Review.mp4

08:32

8.1 My TensorFlow Developer Certificate.html

8. Quick Checkpoint About Deep Learning in Snowflake.mp4

00:49

9. ChatGPT Integrations Local Applications.mp4

10:57

10. ChatGPT Integrations Snowflake Applications.mp4

11:11

11. ChatGPT Integrations Overview.mp4

03:44

12. COMPLETE LLM Functions.mp4

08:57

13. EXTRACT_ANSWER LLM Function.mp4

04:26

14. SENTIMENT LLM Function.mp4

05:34

15. SUMMARIZE LLM Functions.mp4

02:28

16. TRANSLATE LLM Function.mp4

03:28

17. Quick Checkpoint About the Specialized LLM Functions.mp4

00:38

18. Applications with Cortex LLM Functions.mp4

08:52

19. Access Rights to LLM Functions.mp4

02:33

20. Cost of LLM Functions.mp4

08:42

21. Quick Tips Mistral-Large Cost.mp4

01:07

22. Quick Checkpoint About Mistral Large.mp4

00:26

23. LLM Extensions in Snowsight.mp4

04:56

24. Universal Search Overview.mp4

08:16

25. Snowflake Copilot Quick Demo.mp4

08:57

26. Snowflake Copilot Overview.mp4

08:23

27. Snowflake Copilot SQL Query Generation with LangChain and ChatGPT.mp4

11:10

28. Quick Checkpoint Is Snowflake Copilot Reliable Enough.mp4

00:37

29. Document AI Overview.mp4

02:55

30. Document AI Private Data Access with LlamaIndex and ChatGPT.mp4

09:00

31.1 Top 10 Snowflake Integrations with ChatGPT.html

31. Quick Checkpoint About ChatGPT Integrations.mp4

00:30

32. Test Your Knowledge.html

7. Wrapping Up

1.1 GitHub Repository for this course.html

1. Setup Instructions GitHub Project and VSCode.mp4

14:50

2.1 Signup for a Free Snowflake Trial Account.html

2. Setup Instructions Free Snowflake Trial Account.mp4

11:59

3.1 OpenAI Developer Platform.html

3. Setup Instructions ChatGPTOpenAI Account.mp4

04:42

4. Congratulations, You Made It!.mp4

00:47

5. Bonus Lecture.html

Description

by World-Class Snowflake Expert

What You'll Learn?

Everything about Snowflake Cortex, the new AI & ML platform from Snowflake
How to implement end-to-end ML pipelines using both Snowpark and Snowpark ML
How to develop ML experiments with Snowflake using notebooks and code snippets
How to use the ML-powered classes and functions from Snowflake Cortex
How to call the new LLM functions from Snowflake Cortex
How to use Snowflake Copilot and other super-new LLM UI features in Snowsight
How to integrate Snowflake with ChatGPT using the OpenAI REST API
How to use Snowpark over in-memory Pandas DataFrames

Who is this for?

Data Scientists who want to learn about all AI & ML opportunities in Snowflake

Data Analysis looking how to use the new ML-based and LLM functions

Data and Software Engineers looking to expand into AI & ML on Snowflake

Project Managers looking for a 360 degree view of the new Snowflake Cortex platform

Data Architects willing to understand fast how Snowflake Cortex is built

Anyone else looking for a high-level (but detailed) picture of Snowflake Cortex

Anyone looking to understand the code and query pushdown model of Snowflake

Anyone looking how to save money on Snowflake using new built-in ML and LLM functions

Anyone looking for other Snowflake features yet to come in the AI & ML area

What You Need to Know?

Basic knowledge of Snowflake

Basic knowledge of programming in SQL

Basic knowledge of programming in Python

Basic knowledge of Data Science and Machine Learning

Basic knowledge of Deep Learning and Transformers

Basic knowledge of LLMs (like ChatGPT) and their use cases

Optional knowledge of Streamlit

Optional knowledge of Time Series

More details

Description
What is Snowflake Cortex
Snowflake got heavily involved into AI and ML only in the past two years. I know, because I've been around since the beginning. In Jan 2021 I was selected by them as a "Snowflake Data Superhero". And in my last two years alone I passed many DS and ML certification exams (see below).
In mid-2023 they came up with Snowpark ML. Then with some built-in ML-powered functions, about regression and classification. The new Model Registry from Snowpark ML - added in Jan 2024 - allows now end-to-end ML on the platform.
You'll see side-by-side data science experiments I will present to you "the old way", on Snowflake. Many of them with integrations with ChatGPT (about which I talked in detail in another course of mine). To compare them now with the new LLM functions, as Snowflake decided to host their own Large Language Models.
Most of these (and other features yet to come) are now presented under the Snowflake Cortex umbrella.
What you will learn
High-level picture of the new Snowflake Cortex AI & ML platform.
Detailed views on each of the Snowflake Cortex areas.
How ML experiments were done on Snowflake before Cortex.
How ML experiments can be implemented today with the Snowpark ML APIs, part of Snowflake Cortex.
End-to-end Machine Learning with Snowpark ML and its Model Registry.
How to use the new regression and classification ML-powered classes and functions, in Snowflake Cortex.
How to call the new LLM functions from Snowflake Cortex, and compare them with ChatGPT.
What to expect from Snowflake Copilot and other incoming Snowflake features in Cortex.
What was the roadmap and what are the future plans of Snowflake for Snowflake Cortex or in the AI & ML areas.
What this course is NOT about
I will not teach you data science and machine learning here from ground up. You are expected to have some basic knowledge about ML, DL, LLMs...
I will not teach you about many other areas in Snowflake. You are expected to have basic knowledge of Snowflake and data warehouses in general.
I will not teach programming in Python or SQL. It's a hands-on course and you are expected to have some basic knowledge in this area. However, I may come-up with some small Streamlit apps, but I'll keep everything simple and easy to understand.
This will not cover EVERYTHING you can do as data science in Snowflake. While you will see experiments "the old way" with scikit-learn, or integrations with ChatGPT, these are not part of Cortex! We have to limit mostly to Snowflake Cortex, as that's a huge platform.
While Snowpark Container Services are also very new and they also target mostly ML and DL experiments (especially the new containers with GPUs), there will not be enough time to go deeper in detail. And this is also a very specialized and more difficult platform to understand. I may come up later on with a more advanced course on SPCS, but for now this course does not require such an advanced level of preparation.
Who I am
The only world-class expert from Canada selected for the Snowflake Data Superhero program in 2021.
SnowPro Certification SME (Subject Matter Expert) - many SnowPro exam questions have been created by me.
Passed four SnowPro certification exams to date (with no retakes): Core, Architect, Data Engineer, Data Analyst.
Specialized in Snowflake for the past few years: I worked for Snowflake Partner companies. I served dozens of clients in this capacity or as an independent consultant. Today I share my knowledge with highly specialize courses on Snowflake.
A few of my latest Data Science and Machine Learning certifications
AWS Certified in Machine Learning
Microsoft Azure Data Scientist Associate
Microsoft Azure AI Engineer Associate
Microsoft Azure AI Fundamentals
TensorFlow Developer Certificate
Alteryx Machine Learning Fundamentals Certified
Dataiku ML Practitioner Certified
Dataiku MLOps Practitioner Certified
Neo4j Graph Data Science Certified
TigerGraph Graph Algorithms for Machine Learning
This course truly offers a complete coverage of the new Snowflake Cortex, and my intention is to update it frequently. Enroll today, and keep this course forever!
Who this course is for:
Data Scientists who want to learn about all AI & ML opportunities in Snowflake
Data Analysis looking how to use the new ML-based and LLM functions
Data and Software Engineers looking to expand into AI & ML on Snowflake
Project Managers looking for a 360 degree view of the new Snowflake Cortex platform
Data Architects willing to understand fast how Snowflake Cortex is built
Anyone else looking for a high-level (but detailed) picture of Snowflake Cortex
Anyone looking to understand the code and query pushdown model of Snowflake
Anyone looking how to save money on Snowflake using new built-in ML and LLM functions
Anyone looking for other Snowflake features yet to come in the AI & ML area

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Certified Solutions Architect in AWS/Azure/Google Cloud (20 total exams). Former Snowflake “Data Superhero” and SnowPro Certification SME. Certified in many NoSQL stores: Cassandra/Redis/Couchbase/Neo4j/TigerGraph...Decades of practical experience in software design and implementation. Former Microsoft employee. Architect of the Data Xtractor Suite - with a visual SQL editor, data visualization charts, data modeling... Former assistant professor at the "Polytechnica" University of Bucharest.I live in beautiful Vancouver/Canada.

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