| Class Name | Directory | Date Completed |
|---|---|---|
| Object Oriented R at a Glance | [/ObjectOrientedR] | {2016/12/23} |
| Data Visualization with ggplot2, Part 1 | [/DataVisGgplot2P1] | {2016/09/01} |
| Data Visualization with ggplot2, Part 2 | [/DataVisGgplot2P2] | {2017/01/16} |
| Data Visualization with ggplot2, Part 3 | [/DataVisGgplot2P3] | {2017/01/27} |
| Writing Functions in R | [/WritingFunctionsInR] | {2017/02/01} |
| Reporting with R Markdown | [/ReportingWithRMarkdown] | {2017/02/02} |
| Text Mining: Bag of Words | [/TextBagOfWords] | {2017/02/08} |
| Working With RStudio, Part 1 | [/WorkingWithRStudioP1] | {2017/02/12} |
| Working With RStudio, Part 2 | [/WorkingWithRStudioP2] | {2017/03/11} |
| Intro to Python for Data Science | [/IntroPythonDataScience] | {2017/03/18} |
| Intermediate to Python for Data Science | [/IntermediatePythonDataScience] | {2017/03/26} |
| Beginning Bayes in R | [/BeginningBayesR] | {2017/04/20} |
| Foundations of Inference | [/FoundationsInference] | {2017/04/27} |
| Intermediate R - Practice | [/IntermediateRPractice] | {2017/05/21} |
| Importing and Cleaning: Case Study | [/ImportCleaningCaseStudy] | {2017/06/03} |
| Importing Data in R, Part 1 | [/ImportDataRP1] | {2017/06/08} |
| Importing Data in R, Part 2 | [/ImportDataRP2] | {2017/06/09} |
| Joining Data in R with Dplyr | [/JoiningDataDplyr] | {2017/06/15} |
| Introduction to Spark in R | [/IntroToSparkR] | {2017/06/30} |
| Data Visualization in R | [/DataVisInR] | {2017/08/04} |
| Introduction to Data | [/IntroToData] | {2017/08/04} |
| Exploratory Data Analysis | [/ExploratoryDA] | {2017/08/07} |
| Correlation and Regression | [/CorrAndRegress] | {2017/08/09} |
| Machine Learning Toolbox | [/MLToolbox] | {2017/08/11} |
| Unsupervised Learning in R | [/UnsupervisedInR] | {2017/08/09} |
| Data Visualization in R with ggvis | [/DataVisGGVis] | {2017/08/23} |
| Data Visualization in R with Lattice | [/DataVisLattice] | {2017/08/25} |
| String Manipulation in R With Stringr | [/StringManipStringR] | {2017/09/01} |
| Introduction to R and Finance | [/introToRFinance] | {2017/09/16} |
| Intermediate R for Finance | [/IntermediateFinanceInR] | {2017/09/23} |
| Manipulating Time Series Data in R | [/ManipulatingTimeSeriesR] | {2017/09/29} |
| Importing and Managing Financial Data | [/ImportManageFinanceR] | {2017/10/06} |
| Working with Web Data in R | [/WebDataInR] | {2017/10/13} |
| Manipulating Time Series Data in Python | [/ManipulatingTimeSeriesPython] | ------------ |
| Data Analysis in R, the data.table Way | [/DataTableWay] | ------------- |
| Introduction to Time Series Analysis | [/TimeSeriesAnalysisR] | {2017/10/20} |
| ARIMA Modeling with R | [/ArimaInR] | {2017/10/27} |
| Manipulating Time Series: Case Study | [/ManipulatingTimeSeriesCaseStudy] | {2017/11/03} |
| Forcasting Using R | [/ForcasingUsingR] | {2017/11/10} |
| Introduction to Shell | [/IntroToShell] | {2017/11/16} |
| Visualizing Time Series in R | [/VisualizeTimeSeries] | {2017/11/23} |
| Introduction to Portfolio Analysis in R | [/IntroPortfolioAnalysisR] | {2017/12/14} |
| Sentiment Analysis in R | [/SentimentAnalysisR] | {2017/12/15} |
| NLP Fundamentals in Python | [/NLPInFundamentalsPython] | {2017/12/03} |
| Foundations of Probability in R | [/FoundationsProbabilityR] | {2017/12/23} |
| Building Web Applications With Shiny | [/WebAppsShiny] | {2017/12/29} |
| Network Analysis in R | [/NetworkAnalysisR] | {2018/1/04} |
| Geospatial Data in R | [/GeospatialDataR] | {2018/01/11} |
| Scalable Data Processing in R | [/ScalableDataProcessingR] | {2018/02/02} |
| Web Applications with Shiny: Case Study | [/WebAppsShinyCaseStudy] | {2018/02/09} |
| Introduction to the Tidyverse | [/IntroToTidyverse] | {2018/02/15} |
| Introduction to Databases in Python | [/IntroPythonDatabase] | {2018/02/23} |
| Intro To Stats: Corr. & Linear Reg. | [/IntroCorrLinearRegression] | {2018/03/02} |
| Building Chatbots in Python | [/ChatbotsInPython] | {2018/03/09} |
| Parallel Computing with Dask | [/ParallelComputingDask] | {2018/03/16} |
| Interactive Maps with leaflet in R | [/InteractiveMapsLeafletR] | {2018/07/13} |
| Network Science in R - A Tidy Approach | [/NetworkScienceInR] | {2018/07/19} |
| Experimental Design in R | [/ExperimentalDesignR] | {2018/08/01} |
| Structural Equation Modeling with Lavaan | [/StructuralModelingWithLavaan] | {2018/08/10} |
| Network Analysis in R: Case Studies d | [/NetowrkInRCaseStudy] | {2018/09/06} |
| Fundamentals of Bayesian Data Analysis | [/BayesianDataAnalysisInR] | {2018/09/14} |
| Deep Learning in Python | [/DeepLearningPython] | {2018/09/20} |
| Network Analysis in Python, Part 1 | [/NetworkingAnaysisP1] | {2018/10/11} |
| Network Analysis in Python, Part 2 | [/NetworkingAnaysisP2] | {2018/10/18} |
| Machine Learning in the Tidyverse | [/MLinTidyverse] | {2018/11/09} |
| Nonlinear Modeling in R with GAMs | [/NonlinearGamsR] | {2018/11/14} |
| Factor Analysis in R | [/FactorAnalysisR] | {2018/11/26} |
| Linear Algebra for Data Science in R | [/LinearAlgebraR] | {2018/11/29} |
| Foundations of Functional Programming | [/FoundationsFunctionalWithPurrr] | {2019/01/03} |
| Differential Expression Analysis in R | [/DifferentialExpressionsR] | {} |
| Hyperparameter Tuning in R | [/HyperparameterTuningR] | {2019/02/1} |
| Feature Engineering in PySpark | [/FeatureEngineeringPySpark] | {2019/03/11} |
| Python Data Science Toolbox, Part 1 | [/PythonDataScienceToolbox-P1] | {2019/03/16} |
| Pandas Foundations | [/PythonPandasFoundations] | {2019/03/29} |
| Writing Efficient Python Code | [/EfficientPython] | {2019/04/09} |
| Supply Chain Analytics in Python | [/SupplyChainPython] | {2019/5/1} |
| Interactive Data Visualization w/ Bokeh | [/InteractiveVisBokeh] | {} |
| Key | Meaning | |------------------- | | R | Review/Redo. | | O | Organize. | | F | Freeze. |