Learning Labs Pro

Description

Learning Labs Pro
Original Price: $349
You Just Pay: $59.95 (One Time – 88% OFF)
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Sale Page:_https://archive.is/0CqwV
Product Delivery : You will receive a receipt with download link through email.
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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
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)