Learning Labs Pro

 

Learning Labs Pro

Your resource for cutting edge technology in a focussed course format

Learning Labs They cover many topics of interest to data scientists. They are generally 1.5 hours & include live coding and demonstrations.

Why choose PRO?

It’s simple – You get a new 1-hour course in your inbox every 2-weeks on intermediate & advanced topics. This course is perfect for continuing data science education in all the critical topics that we don’t cover in our R-Track Course curriculum.

You can watch Learning Lab 28 – Shiny Real Estate API (Free Sample)

2x per month, you receive a lab with an Advanced Data Science Project in the mail!

Code + Video Instruction + Shiny app!
LL PRO Topics & Course List

Data science’s most important topics 2X per month
R in Production

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

Special: Time Series Forecasting using Modeltime

Lab 38 [Special]Modeltime Time Series Forecasting

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)

Get your instant download Learning Labs Pro

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 Customer Journey
Lab 25 [Part 2]: ChannelAttribution for Multi-Channel Marketing
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 Customer Churn
Lab 19 – Network Analysis – Cluster Influencers by Using Customer Credit Cards History
Lab 18: Anomaly detection for the Time Series
Lab 17: Anomaly Detection using H2O Machine Learning
Lab 16: R Optimization Toolchain – Part 2 – Stock Portfolio Analysis & Nonlinear Programming
Lab 15: The R’s Optimization Toolschain 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 Information
Lab 7: Five Strategies to Increase Business Forecasting by 50% or More
Lab 6: Communicating Machine Learning With the rmarkdown Package
Lab 5: Coding hands-on 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. Production: Building Production-Quality Apps With Shiny
Lab 1: How to Learn R Fast

 

Neu Learning Labs Are released 2X per Month!

All of it in one place so you can watch whenever suits you and rewatch at any time!

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

Register now to get access to this lab!
Program Offers

Apply to your job to accelerate your career.

Get ed now!

Yearly Membership

Upgrade to a yearly membership and save $119
$349/year

6-Month Payment Options

$199 for 6 Months

Monthly payments low

All labs are available for you!
$39/month

Learn Continuously. Accelerate your Career.

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

Learning Labs PRO labs are intermediate and advanced. They keep you learning even after you have completed the R-Track. Learn continuously. You can accelerate your career.

 

You don’t have any experience?

You can go from beginner to advanced in no time with our NEW 4-Course Course R-Track!

The R-Track Course Program is highly recommended. This course will help you build and deploy Shiny web apps and establish your data science knowledge. The Learning Labs This will allow you to expand your knowledge and give you opportunities to work on new projects.

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

Learn about Our 4-Course Track R-Track
Private Slack Community

Ask questions, give feedback, and share your knowledge with the community.

Summary of Everything

You get

1-Hour Courses on Advanced Topics

Full Code of Practice

Slack Channel Community

Resources (Slides. References. Links. And more).

Get ed now!

Yearly Membership

Upgrade to a yearly membership and save $119
$349/year

6-month payment option

$199 for 6 Months

Low Monthly Payments

All labs are available for you!
$39/month

Download it immediately Learning Labs Pro

Most Frequently Asked Questions

How often will new material be added to this service?
Every month, screencasts are 2X (one hour + code) To increase the value, we added EXCLUSIVE Shiny apps!
What is the content roadmap & how do you pick topics?
Our members choose the topics. Webscraping is one topic that we get a lot of requests for. This is added to our mailing list, and we then do webinars. Therefore, the roadmap can be modified and driven by our community.
What is the advantage? Learning Labs What is the difference between PRO and BSU courses?
The courses are project-driven, foundational and take weeks to complete. You will also learn a lot about the various tools that can be used to solve a particular problem. Learning Labs These are more tactical or tool-oriented and focus on a specific application. They also provide brief bursts of information on smaller but equally important topics. Both the Courses as well as the Lectures can be accessed in this way. Learning Labs Each other’s work should be complemented. One teaches projects & foundations, the other teaches skills, tools & applications. WIN-WIN!
What if my schedule is a little tight?
This is why we ed Learning Labs PRO – This allows you to access recordings and content no matter where you are located. You can now get everything, ask questions, and get additional training such as webscraping, deep-learning, and topics specific to your industry like sales, marketing, or any other topic.
Your Instructor

Matt Dancho
Matt Dancho

Founder of Business Science and general business & finance guru, He has worked with many clients from Fortune 500 to high-octane ups! Matt loves teaching data scientists about how to leverage powerful tools within an organization to generate ROI. Matt is relentless in his pursuit of results and doesn’t stop until he achieves them.

Course Curriculum

We are glad you came to Learning Labs PRO!

Learning Labs PRO! (0:52)

We are grateful that you joined LL PRO – Here’s the Dime Tour!

Join Our Slack Channel

MLOps series| MLOps Series

Lab 41: Forecasting at scale with MetaFlow + Modelltime + 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 Weather 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 with Scikit-Learn (HR Analytic) (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 and Shiny (66.52)

Lab 26: Machine Learning Customer Journey (96.38)

Lab 25: Marketing Multichannel 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)

SQL Databases

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 Customer Churn (79.03).

Network Analysis

Lab 19 – Clustering with Network Analysis using Customer Credit Card History (83:09).

Anomaly detection

Lab 18 – Time series anomaly detection – anomalize (87.15)

Lab 17 – Anomaly Detection using 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 of 4.6M rows (375 MB) Financial Data with data.table

Time Series

Lab 7: 5 Strategies for Improving Business Forecasting by 50% or More (89:02).

Production: Shiny & Plumber

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

Data collection

Download it immediately Learning Labs Pro

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 – Coded’s Beginning Labs

Lab 5: Hands on Coding with the NEW Parsnip package (75.54)

Lab 4: H2O AutoML – Erin LeDell Guest Appearance! (87:15)

No-Code / Free Labs (Before the transition to FULL CODE Labs)

[IMPORTANT] Labs 1-6 were made prior to LL PRO.

Lab 6: Communicating Machine Learning With the rmarkdown Package (71:38).

Lab 2: R. Production: Building Production Quality Apps with Shiny (55.32)

Lab 1: How to Learn R Fast (56:35)

Learn more https://archive.is/0CqwV