Learning Labs Pro

In Stock

$69.00

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

Purchase this course you will earn 69 Points worth of $6.90!
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We join Groupbuy AND always try to share knowledge with more people. Especially the quality is the same as salepage. You can buy directly at salepage, with full price. (link SALEPAGE are mounted directly on the post)

Learning Labs Pro

Learning Labs Pro

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!
Program Offers

Apply to your job, accelerate your career.

Get ed now!

Yearly Membership

Save $119 by upgrading to a yearly membership plan!
$349/year

6-month Payment Option

$199 every 6 months

Low Monthly Payments

Unlock access to all of the labs!
$39/month

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?

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

I highly recommend ing 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)

Get ed now!

Yearly Membership

Save $119 by upgrading to a yearly membership plan!
$349/year

6-month Payment Option

$199 every 6 months

Low Monthly Payments

Unlock access to all of the labs!
$39/month

Frequently Asked Questions

What will be the frequency of new material for this service?
The frequency is 2X screen-cast (1hr + code) every month. In addition, we have added EXCLUSIVE Shiny Apps to take the value way over the top!
What is the content roadmap & how do you pick topics?
Our topics are driven by our members – they pick the topics. For example, webscraping is a topic we consistently get requests for. This gets added to our list and we do webinars then on it. The roadmap is therefore flexible and driven by the community!
What is the advantage of Learning Labs PRO versus the BSU Courses?
Courses are foundational, project-driven, take weeks to complete, and you gain a ton of knowledge on how many different tools integrate to solve a problem. Learning Labs are tactical, tool or application focused, and provide short bursts on topics that are smaller in scope but are really important! This way both the Courses and Learning Labs COMPLIMENT each other. One teaches projects & foundations, the other teaches skills, tools & applications. WIN-WIN!
What if I can’t attend LIVE?
That’s actually why we ed Learning Labs PRO – So you can get the recordings and content even though you may be halfway around the world from us. Now you can get all of it, plus ask questions, plus get more topical training like webscraping, deep learning, domain-specific topics like sales, marketing, and more.
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 educating data scientists on how to apply powerful tools within their organization to yield ROI. Matt doesn’t rest until he gets results (literally, he doesn’t sleep so don’t be suprised if he responds to your email at 4AM)!

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 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

Get Learning Labs Pro download

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

Get immediately download 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 – 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)

Read more: https://archive.is/0CqwV


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