LL PRO Topics & Course List

The most important topics in data science 2X per month

Production with Targets

• Lab 57: Targets & Modeltime for Production Forecasting | Automated Forecast Audit Report
• Lab 56: Targets Machine Learning Pipelines | Shiny Customer Churn App (Marketing)

Tidy-Modeling Ecosystem

• Lab 52: Stacks Ensembles | Customer Churn Retention App
• Lab 51: Deep Learning with Torch & Tabnet | Shiny Loan Default Scorer App Bonus | Special Guest: Josh Starmer BAM
• Lab 50: Hierarchical Forecasting LightGBM | Shiny Hierarchical Forecaster App Bonus
  
• Lab 49: Feature Engineering & Customer Analytics | Special Guest: Max Kuhn | Shiny Customer Explorer Bonus
• Lab 48: NLP for Business | Text Recipes | Shiny AutoNLP Bonus

Special: Time Series Forecasting with Modeltime

• Lab 54: Modeltime Recursive Autoregressive Machine Learning | Energy Demand Forecasting
• Lab 53B: Modeltime H2O | Forecasting with H2O AutoML
• Lab 53A: Modeltime GluonTS | SaturnCloud NVIDIA GPU Bonus
• Lab 50: Hierarchical Forecasting LightGBM | Shiny Hierarchical Forecaster App Bonus
• Lab 47: Forecasting with Autoregressive Machine Learning (Recursive) | Scalable AR(ML) Bonus
• Lab 46: Forecasting at Scale with Modeltime | "Nostradamus" Auto-Forecasting Shiny App Bonus
• Lab 38: Time Series Forecasting | Intro to Modeltime

Building an R Package (R Developer Series)

• Lab 45 [Part 3]: Lab 45: Shiny Apps with Golem | golem | Shiny PowerPoint Golem App Bonus
• Lab 44 [Part 2]: R Package Development | usethis | Shiny PowerPoint Bonus
• Lab 43 [Part 1]: Tidy Eval + PowerPoint Automation | officer & rlang | Automate PowerPoint Bonus

R in Production (MLOps)

• Lab 42 [Part 4]: Automating Google Sheets with R API (Plumber, Docker, & AWS)
• 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

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!

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

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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.

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