What You’ll Discover in Learning Labs Pro
Learning Labs Pro
Your resource for cutting-edge technology in a focused course format
Learning Labs Data scientists are interested in a variety of topics. 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. It’s perfect for continuous data science education, covering all the important topics that are not covered in our core R Track Course curriculum.
Keep an eye out Learning Lab 28 – Shiny Real Estate API (Free Sample)
2X per month, you get a lab that contains an Advanced Data Science Project sent to your inbox!
Shiny App + Code!
LL PRO Topics & Course List
The top topics in data science 2X per Month
R in Production (MLOps).
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)
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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 (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 and Marketing Multi-Channel Attribution
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: Part 1 of R’s Optimization Toolchain for Business Decision Making
Lab 14: Customer Churn Survival Analysis
Lab 13 – Big Data – Wrangling of 4.6M rows (375MB) of Financial 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 They are published 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 to access this lab right away!
Programme Offers
Apply for your job to accelerate your career.
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Annual Membership
Upgrade to a Yearly Membership Plan and Save $119
$349/year
6-Month Payment Options
$199 every 6 month
Low Monthly Payments
All labs are available for you!
$39/month
Learn Continuously. You can accelerate your career.
Going PRO Compliments our University Courses by hitting diverse & critical topics.
Learning Labs PRO Labs are intermediate or advanced labs that will keep you learning well after you’ve finished the R-Track. Learn continuously. You can accelerate your career.
Do You Have Experience?
Our NEW 4-Course R-Track will take you from beginner to advanced FAST!
I recommend the R-Track Course Program. This course will help you build and deploy Shiny web apps and establish your data science knowledge. This is the 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
Find out more about our 4-Course R Track
Private Slack Community
Ask questions, share feedback and learn from 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!
Annual Membership
Upgrade to a Yearly Membership Plan and Save $119
$349/year
6-Month Payment Options
$199 every 6 month
Low Monthly Payments
All labs are available for you!
$39/month
Download it immediately Learning Labs Pro
Frequently Asked Question
How often will new material be added to this service?
Every month, screen-casts 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. We get many requests for webscraping, for example. We add it to our list, and then we host webinars on it. Therefore, the roadmap can be modified and driven by our community.
What’s the benefit of Learning Labs What is the difference between PRO and BSU courses?
These courses are project-driven and foundational. They take weeks to complete. You also gain a lot of knowledge about how different tools can be combined to solve a 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. The Courses and the Tutorials are both streamlined in this manner. Learning Labs They can complement each other. One teaches projects & foundations, the other teaches skills, tools & applications. WIN-WIN!
What happens if I am unable to attend LIVE?
This is why we ed Learning Labs PRO – You can access the recordings and content from anywhere in the world. 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 enjoys teaching data scientists how to use powerful tools within their organizations to increase ROI. Matt is relentless in his pursuit of results and doesn’t stop until he achieves them.
Course Curriculum
You are welcome to Learning Labs PRO!
Learning Labs PRO! (0:52)
We are grateful that you joined LL PRO – Here’s the Dime Tour!
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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 using Modeltime (85.29)
Python + R Series
Lab 37: NLP & PDF Text Extraction (spaCy) (100:37)
Lab 36: Tensorflow Multivariate Prediction (Energy and 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: ChannelAttribution and Marketing Multi-Channel Attribution (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: Using Customer Credit Cards History to Cluster with Network Analysis (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)
Finance Domain
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)
Continue reading:Â https://archive.is/0CqwV
IMPORTANT: This is it. “Learning Labs Pro” It is totally Downloadable And Available Check your account
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