Learning Labs Pro – Matt Dancho

Salepage link: At HERE. Archive: https://archive.is/0CqwV

Learning Labs Pro

1-Hour Data Science Courses Released 2X Per Month

Your Resource for Cutting-Edge Technology in a Focused Course Format

Learning Labs cover a wide variety of topics that matter to data scientists. They are generally 1.5 hours & include live coding and demonstrations.

Why go PRO?

It’s simple – You get a new 1-hour course in your inbox every 2-weeks on intermediate & advanced topics. Perfect for continuous data science education on all of the critical topics we don’t touch in our core R-Track Course curriculum.

Watch Learning Lab 28 – Shiny Real Estate API (Free Sample)

You get a lab containing an Advanced Data Science Project in your inbox 2X per Month!

Code + Video Instruction + Shiny App!

LL PRO Topics & Course List

The most important topics in data science 2X per month

R in Production (MLOps)

• Lab 41 [Part 3]: Scalable Forecasting with Metaflow + Modeltime + AWS
• Lab 40 [Part 2]: Docker for Data Science
• Lab 39 [Part 1]: Building a Bankruptcy Prediction API with H2O & MLFlow

Special: Time Series Forecasting with Modeltime

• Lab 38 [Special]: Time Series Forecasting with Modeltime

Python & R Series, 5-Part Series

• Lab 37 [Part 5]: NLP & PDF Text Extraction (spaCy)
• Lab 36 [Part 4]: TensorFlow Multivariate Forecasting & Enhanced TF Tutorial (Time Series, Energy)
• Lab 35 [Part 3]: TensorFlow Univariate Forecasting & Gold Forecasting App (Time Series, Finance)
• Lab 34 [Part 2]: Advanced Customer Segmentation & Market Basket Analyzer App (E-Commerce, Scikit-Learn)
• Lab 33 [Part 1]: Employee Segmentation with Python & R (HR Analytics, Scikit-Learn)

Shiny API, 5-Part Series

• Lab 32 [Part 5]: Text Mining Tweets with Twitter & Tidytext
• Lab 31 [Part 4]: Forecasting Google Analytics with Facebook Prophet & Shiny
• Lab 30 [Part 3]: Shiny Financial Analysis with Tidyquant API (Finance)
• Lab 29 [Part 2]: Shiny Crude Oil Forecast (Multivariate ARIMA) with Quandl API & Fable
• Lab 28 [Part 1]: Shiny Real Estate App with Zillow API

Marketing Analytics, 4-Part Series

• Lab 27 [Part 4]: Google Trends Automation with Shiny
• Lab 26 [Part 3]: Machine Learning for Customer Journey
• Lab 25 [Part 2]: Marketing Multi-Channel Attribution with ChannelAttribution
• Lab 24 [Part 1]: A/B Testing for Website Optimization with Infer & Google Optimize

SQL for Data Scientists, 3-Part Series

• Lab 23 [Part 3]: Google Analytics & BigQuery (SQL) – Conversion Funnel Analysis
• Lab 22 [Part 2]: SQL for Time Series – Mortgage Loan Delinquency
• Lab 21 [Part 1]: SQL for Data Science – Home Loan Applications & Default

Plus 20 More Labs:

• Lab 20: Explaining Machine Learning for Customer Churn
• Lab 19: Network Analysis – Using Customer Credit Card History to Cluster Influencers
• Lab 18: Anomaly Detection for Time Series
• Lab 17: Anomaly Detection with H2O Machine Learning
• Lab 16: R Optimization Toolchain – Part 2 – Stock Portfolio Analysis & Nonlinear Programming
• Lab 15: R’s Optimization Toolchain For Business Decision Making Part 1
• Lab 14: Customer Churn Survival Analysis
• Lab 13: Big Data – Wrangling 4.6M Rows (375 MB) of Financial Data with data.table
• Lab 12: How I Built This – R Package Anomalize using Tidy Eval & Rlang
• Lab 11: Market Basket Analysis & Recommendation Systems w/ recommenderlab
• Lab 10: Building API’s with Plumber & Postman
• Lab 9: Finance with R – Performance Analysis & Portfolio Optimization with tidyquant
• Lab 8: Web Scraping – Build A Strategic Database With Product Data
• Lab 7: 5 Strategies to Improve Business Forecasting by 50% (or more)
• Lab 6: Communicating Machine Learning with the rmarkdown package
• Lab 5: Hands-On Coding with the NEW parsnip package
• Lab 4: H2O AutoML – Erin LeDell Guest Appearance!
• Lab 3: Marketing Analytics Case Study – Excel to R
• Lab 2: R In Production: Building Production-Quality Apps with Shiny
• Lab 1: How to Learn R Fast!

New Learning Labs are released 2X per month!

All in one convenient location so you can watch on your schedule (and rewatch any time!)

Lab 34 – Advanced Customer Segmentation w/ Scikit-Learn & Shiny

Sign up to unlock this lab immediately!

Learn Continuously. Accelerate Your Career.

Going PRO Compliments our University Courses by hitting diverse & critical topics.

Learning Labs PRO are intermediate and advanced labs that keep you learning long after you’ve completed the R-Track. Learn continuously. Accelerate you Career.

No Experience?

Start with our NEW 4-Course R-Track to go from beginner to advanced FAST!

I highly recommend starting with the R-Track Course Program. This will set your data science foundations and teach you how to build and deploy Shiny web applications. The Learning Labs will then extend your knowledge by giving you new projects that expand your skills.

Gain Foundations & Advanced Techniques so you can take FULL ADVANTAGE of Learning Labs PRO

Learn About Our 4-Course R-Track

Private Slack Community

Ask questions, provide feedback, and learn with the community!

Summary of Everything

You get

1-Hour Courses on Advanced Topics

Full Working Code

Slack Channel Community

Resources (Slides, References, Links, and more)

Course Curriculum

Welcome to Learning Labs PRO!

• Learning Labs PRO! (0:52)
• Thank You For Joining LL PRO – Here’s The Dime Tour!
• Join Our Slack Channel

R in Production | MLOps Series

• Lab 42: Automating Google Sheets with R API (Plumber, Docker, & AWS) (86:12)
• Lab 41: Forecasting at Scale with MetaFlow + Modeltime + AWS (97:21)
• Lab 40: Docker for Data Science (91:37)
• Lab 39: H2O & MLFlow for Bankruptcy Prediction API (88:47)

SPECIAL: Forecasting with Modeltime!

• Lab 38: Time Series Forecasting with Modeltime (85:29)

Python + R Series

• Lab 37: NLP & PDF Text Extraction (spaCy) (100:37)
• Lab 36: Tensorflow Multivariate Forecasting (Energy, LSTM) (108:17)
• Lab 35: TensorFlow for Finance & Gold Price Forecaster App (Time Series, LSTM) (119:27)
• Lab 34: Advanced Customer Segmentation & Market Basket App (E-Commerce) (107:21)
• Lab 33: Employee Segmentation w/ Scikit-Learn (HR Analytics) (88:08)

Shiny API Series

• Lab 32: Text Mining Tweets with Twitter & Tidytext (91:07)
• Lab 31: Forecasting Google Analytics with Facebook Prophet & Shiny (79:26)
• Lab 30: Shiny Finance with Tidyquant (Excel in R) (88:54)
• Lab 29: Shiny Crude Oil Forecast (Multivariate ARIMA) App with Fable & Quandl API (83:13)
• Lab 28: Shiny Real Estate App with Zillow API (72:50)

Marketing Analytics Series

• Lab 27: Google Trends Automation with Shiny (66:52)
• Lab 26: Machine Learning for Customer Journey (96:38)
• Lab 25: Marketing Multi-Channel Attribution with ChannelAttribution (96:08)
• Lab 24: A/B Testing for Website Optimization with Infer & Google Optimize (90:59)
• Lab 14: Customer Churn Survival Analysis w/ correlationfunnel, parsnip, & H2O (88:30)
• Lab 11: Market Basket Analysis & Recommendation Systems w/ recommenderlab (78:35)
• Lab 3: Marketing Analytics Case Study – Excel to R (77:54)

Databases – SQL

• Lab 23 – Google Analytics & BigQuery (SQL) – Conversion Funnel Analysis (85:04)
• Lab 22 – SQL for Time Series – Stocks & Fannie Mae Mortgage Delinquency Analysis (90:16)
• Lab 21 – SQL for Data Science – Home Loans with SQL, R, & dplyr (92:06)

Explainable Machine Learning

• Lab 20 – Explaining Machine Learning for Customer Churn (79:03)

Network Analysis

• Lab 19 – Using Customer Credit Card History to Cluster with Network Analysis (83:09)

Anomaly Detection

• Lab 18 – Time Series Anomaly Detection – anomalize (87:15)
• Lab 17 – Anomaly Detection with H2O Machine Learning (90:34)

Optimization & Simulation

• Lab 16: R Optimization Toolchain – Part 2 – Stock Portfolio & Nonlinear Programming with ROI (88:09)
• Lab 15: R Optimization Toolchain – Part 1 – Product Mix & Linear Programming with ompr (80:35)

Big Data

• Lab 13: Wrangling 4.6M Rows (375 MB) of Financial Data with data.table (78:36)

Time Series

• Lab 7: 5 Strategies to Improve Business Forecasting by 50% (or more) (89:02)

Production: Shiny & Plumber

• Lab 10: Building API’s with Plumber & Postman (80:18)

Data Collection

• Lab 8: Web Scraping – Build A Strategic Database With Product Data (70:07)

Domain: Finance

• Lab 9: Finance with R – Performance Analysis & Portfolio Optimization with tidyquant (77:35)

Advanced Functional Programming

• Lab 12: How I Built This – R Package Anomalize using Tidy Eval & Rlang (74:50)

Machine Learning – Beginning of Coded Labs

• Lab 5: Hands-On Coding with the NEW parsnip package (75:54)
• Lab 4: H2O AutoML – Erin LeDell Guest Appearance! (87:15)

Free / No-Code Labs (Before we transitioned to FULL CODE Labs)

• [IMPORTANT] Labs 1-6 were made before LL PRO existed.
• Lab 6: Communicating Machine Learning with the rmarkdown package (71:38)
• Lab 2: R In Production: Building Production-Quality Apps with Shiny (55:32)
• Lab 1: How to Learn R Fast! (56:35)