Portfolio Analytics Training Classes and Opportunities

As part of SC’s commitment to deepening the SC community’s skills, knowledge, and use of portfolio analytics techniques, a list of portfolio analytics learning opportunities has been created to support ongoing training needs. These courses feature learning opportunities that explore data cleaning, data analysis, data visualization, and data-driven decision making. This course listing will be updated as new training courses and opportunities are identified.

If you find a course suited to your needs and interests, please discuss with your supervisor and complete a training request in Learning Nucleus. If you choose a course that involves a subscription, you should identify that in the comments section and state the length of time you are requesting (monthly/yearly). Once that request has been completed and approved, HC will reach out to you to obtain your log-in information in order to complete the procurement action. Those employees who choose a year-long subscription will be responsible for canceling the membership before the year is completed or initiating a new approval through Learning Nucleus again.

If you have specific questions about courses, please contact Mary Beth West at westm@osti.gov.

Courses and Training

Data Cleaning

  • Getting and Cleaning Data
    • Source: Coursera - https://www.coursera.org/learn/data-cleaning
    • Lecturers: Johns Hopkins University
    • Overview: This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats.
      • It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks.
      • The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data.
    • Cost Options: $399 / year for Coursera Plus Subscription or $49 month-to-month.
  • Data Science: Wrangling
    • Source: edX – https://www.edx.org/course/data-science-wrangling
    • Lecturers: Harvard University
    • Overview: Learn to process and convert raw data into formats needed for analysis. In this course, part of our  Professional Certificate Program in Data Science,
      • This course covers several standard steps of the data wrangling process like importing data into R, tidying data, string processing, HTML parsing, working with dates and times, and text mining. Rarely are all these wrangling steps necessary in a single analysis, but a data scientist will likely face them all at some point.
    • Cost Options: Pay for course for certificate ($149).

Data Visualization

  • Visual Analytics Certificate
    • Source: Indiana University - https://visanalytics.cns.iu.edu/
    • Overview:
      • Online program, 6 weeks (30-hour, 3 CEU course)
        • Program Dates: Sept 20 – Oct 30, 2021
      • Modules
        • Data-Driven Decision making, Visual Analytics Framework, Workflow Design
        • “When”: Temporal Data Analysis and Visualization
        • “Where”: Geospatial Data Analysis and Visualization
        • “What”: Topical Data Analysis and Visualization
        • “With Whom”: Network Analysis and Visualization
        • Future Developments, Value Creation via Data-Driven Decision Making
      • Cost: $950
  • Data Science: Visualization
    • Source: edX - https://www.edx.org/course/data-science-visualization
    • Lecturers: HarvardX
    • Overview: This course covers the basics of data visualization and exploratory data analysis. We will use three motivating examples and ggplot2, a data visualization package for the statistical programming language R. We will start with simple datasets and then graduate to case studies about world health, economics, and infectious disease trends in the United States.
    • Cost Options: Pay for course for certificate ($149).
  • Analyzing and Visualizing Data with Power BI
    • Source: edX - https://www.edx.org/course/data-analysis-in-power-bi
    • Lecturers: Davidson College
    • Overview: This four-week course is a beginner's guide to working with data in Power BI and is perfect for professionals. You'll become confident in working with data, creating data visualizations, and preparing reports and dashboards.
    • Cost Options: Pay for course for certificate ($99).
  • Visualizing Text Analytics and Natural Language Processing with Python
    • Source: edX – https://www.edx.org/course/visualizing-text-analytics-and-natural-language-processing-with-python
    • Lecturers: UCX – University of Canterbury
    • Overview: This course is a practical and scientific introduction to text analytics. That means you’ll learn how it works and why it works at the same time. ou’ll learn how to create visualizations ranging from wordclouds, heatmaps, and line plots to distribution plots, choropleth maps, and facet grids. You’ll work through real case-studies using jupyter notebooks and to visualize the results of machine learning in Python using packages like pandas, matplotlib, and seaborn.
    • Cost Options: Pay for course for certificate ($249).
  • Data Analysis and Visualization Foundations Specialization
    • Source: Coursera - https://www.coursera.org/specializations/data-analysis-visualization-foundations
    • Lecturers: IBM
    • Overview: This course will teach skills required to successfully start data analysis tasks by becoming familiar with spreadsheets like Excel. Learners will examine different data sets, load them into the spreadsheet, and employ techniques like summarization, sorting, filtering, & creating pivot tables.
    • Cost Options: $399 / year for Coursera Plus Subscription or $39 month-to-month.
  • Microsoft Power BI - A Complete Introduction
    • Source: Udemy - https://www.udemy.com/course/powerbi-complete-introduction/
    • Overview: In this course you will learn why Power BI offers you a comprehensive set of Business Intelligence tools for your data analysis goals and how to use these tools to fulfill all of the above tasks - and more. Imagine to quickly structure your data, to easily add calculations to it and to create and publish nice-looking charts in just a few minutes. 
    • Cost: $94.99
  • Data Visualization: Communicating Data and Complex Ideas Visually (Online)
  • Data Visualization
    • Source: Management Concepts - https://www.managementconcepts.com/course/id/4606
    • Overview: Spreadsheets and large tables can be complex, difficult to decipher, and present barriers to extracting valuable information parsed from an organization’s data. Applying best practices for data visualization will allow you to solve problems, identify how to use visuals in presentations and reports, and make decisions. You will learn the basics of the visual perception of data as well as strengthen and practice these new techniques through a capstone exercise.
    • Cost: $909 (2-day course)
      • Delivery Method: Instructor-led live classroom
      • Alternative Delivery Methods: Instructor-led online (synchronous)

Data Analysis

  • Data Analytics Certificate
    • Source: Cornell University - https://info.ecornell.com/data-analytics
    • Overview:
      • Online program, 3 courses
        • The program consists of 3 three-week courses (with 1 week break between courses), all available 24/7 online, with 3-5 hours of study recommended per week.
      • Courses:
        • Understanding and Visualizing Data
        • Implementing Scientific Decision Making
        • Using Predictive Data Analysis
      • Cost: $3,600
  • Data Science Professional Certificate
    • Source: edX - https://www.edx.org/professional-certificate/harvardx-data-science
    • Lecturers: HarvardX
    • Overview: The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. The HarvardX Data Science program prepares you with the necessary knowledge base and useful skills to tackle real-world data analysis challenges. The program covers concepts such as probability, inference, regression, and machine learning and helps you develop an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document preparation with RStudio.
    • Cost: $792.80 (estimated completion 1 year, 5 months)
  • The Analytics Edge
    • Source: edX - https://www.edx.org/course/the-analytics-edge
    • Lecturers: MITx
    • Overview: We will teach you the following analytics methods: linear regression, logistic regression, trees, text analytics, clustering, visualization, and optimization. We will be using the statistical software R to build models and work with data. The contents of this course are essentially the same as those of the corresponding MIT class (The Analytics Edge). It is a challenging class, but it will enable you to apply analytics to real-world applications.
    • Cost Options: Pay for course for certificate ($199).
  • Introducing Text Analytics and Natural Language Processing with Python
    • Source: edX - https://www.edx.org/course/introducing-text-analytics-and-natural-language-processing-with-python
    • Lecturers: UCX – University of Canterbury
    • Overview: This first course introduces the core techniques of natural language processing (NLP). But we introduce these techniques from data science alongside the cognitive science that makes them possible. This course is a practical and scientific introduction to text analytics. That means you’ll learn how it works and why it works at the same time.  On the practical side, you’ll learn how to actually do an analysis in Python: creating pipelines for text classification and text similarity that use machine learning. These pipelines are automated workflows that go all the way from data collection to visualization. You’ll learn to use Python packages like pandas, scikit-learn, and tensorflow.
    • Cost: Pay for course for certificate ($249).
  • Data Science
    • Source: Coursera - https://www.coursera.org/specializations/jhu-data-science
    • Lecturers: Johns Hopkins University
    • Overview: This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.
    • Cost Options: $399 / year for Coursera Plus Subscription or $49 month-to-month.
  • Data Analysis and Visualization
    • Source: Coursera - https://www.coursera.org/learn/data-analyze-visualize
    • Lecturers: University at Buffalo, The State University of New York
    • Overview: By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries.
      • It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python).
      • Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time. The course also addresses do’s and don’ts of presenting data visually, visualization software (Tableau, Excel, Power BI), and creating a data story.
    • Cost Options: $399 / year for Coursera Plus Subscription or $49 month-to-month.
  • Text Mining and Analytics
    • Source: Coursera - https://www.coursera.org/learn/text-mining
    • Lecturers: University of Illinois
    • Overview: This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort. Detailed analysis of text data requires understanding of natural language text, which is known to be a difficult task for computers. However, a number of statistical approaches have been shown to work well for the "shallow" but robust analysis of text data for pattern finding and knowledge discovery. You will learn the basic concepts, principles, and major algorithms in text mining and their potential applications.
    • Cost Options: $399 / year for Coursera Plus Subscription or $49 month-to-month.
  • Applied Data Science with Python Specialization
    • Source: Coursera - https://www.coursera.org/specializations/data-science-python
    • Lecturers: University of Michigan
    • Overview: The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.
    • Cost Options: $399 / year for Coursera Plus Subscription or $49 month-to-month.
  • Applied Data Science with Python
    • Source: Coursera - https://www.coursera.org/specializations/data-science-python
    • Lecturers: University of Michigan
    • Overview: The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.
    • Cost Options: $399 / year for Coursera Plus Subscription or $49 month-to-month.
  • Applied Text Mining in Python
    • Source: Coursera - https://www.coursera.org/learn/python-text-mining
    • Lecturers: University of Michigan
    • Overview: This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).
    • Cost Options: $399 / year for Coursera Plus Subscription or $49 month-to-month.

Data-Driven Decision Making / Data Informed Decisions

  • Business Analytics for Data-Driven Decision Making
    • Source: edX - https://www.edx.org/course/business-analytics-for-data-driven-decision-making
    • Overview: In this course, part of both the Digital Leadership and Digital Product Management MicroMasters programs, you will learn the tools and techniques to become a data-driven or "evidence-based" manager.
      • Focus on PowerBI
      • Students will the process of reframing a business question as a data question, reasoning about what data might be of assistance and how to obtain it, integrating and cleaning the data, performing the analysis, deriving and communicating insights from the analysis, and building the managerial culture to operate in this way and create competitive advantages from enterprise data.
      • This course is unique in the sense that it aims squarely at the needs of a manager in an analytically focused enterprise by providing both a hands-on introduction to the concepts, methods and processes of business analytics as well as an introduction to the use of analytics as the basis for creating a competitive advantage.
    • Cost: $399 / year for Coursera Plus Subscription.
  • Business Analytics for Data-Driven Decision Making
    • Source: edX - https://www.edx.org/course/business-analytics-for-data-driven-decision-making
    • Lecturers: Boston University
    • Overview: You will learn the process of reframing a business question as a data question, reasoning about what data might be of assistance and how to obtain it, integrating and cleaning the data, performing the analysis, deriving and communicating insights from the analysis, and building the managerial culture to operate in this way and create competitive advantages from enterprise data.
      • Does use Power BI
    • Cost Options: Pay for course for certificate ($399).
  • Data-Driven Decision Making (DDDM) Specialization
    • Source: Coursera - https://www.coursera.org/specializations/data-driven-decision-making
    • Lecturers: University at Buffalo, The State University of New York
    • Overview: Created with the c-suite, directors and senior-level managers in mind, the three-course series explores how technology enables the collection and organization of unprecedented amounts of data, and how to dissect that data to gain powerful insights. Course topics include analyzing process maps for driving improvement, software for maximizing data analysis, statistical process control, creating metrics dashboards and translating data stories, and the connection between operations technology metrics and organizational performance.
      • Courses in Specialization:
        • Operational Context and Data
        • Data Analysis and Visualization
        • Applied Analytics for Decision Making
      • Cost Options: $399 / year for Coursera Plus Subscription or $49 month-to-month.
  • Applied Analytics and Data for Decision Making (one course within the DDDM Specialization)
    • Source: Coursera - https://www.coursera.org/learn/analytics-data-decisions
    • Lecturers: University at Buffalo, The State University of New York
    • Overview: By the end of this course, learners are prepared to identify and test the best solutions for improving performance and integrating concepts from operational excellence methodologies for optimum data-driven decision making.
      • The course begins with a focus on deciphering the root cause of problems through a variety of tools before determining and assessing best-fit solutions. Learners discover how to apply ISO, Lean and Six Sigma in the pursuit of aligning organizational operations data with performance standards.
    • Cost Options: $399 / year for Coursera Plus Subscription or $49 month-to-month.
  • Data Science & Business Analytics
    • Source: University of Texas at Austin - https://la.utexas.edu/greatlearning/uta-data-science-business-analytics-program.html
    • Overview:
      • 6-month online certificate program
      • Modules:
        • Python Foundations
        • Data Visualization with Tableau
        • Business Statistics
        • Supervised Learning Foundations
        • Supervised Learning Classification
        • Ensemble Techniques
        • Model Learning
        • Unsupervised Learning
        • Time Series Forecasting
        • Marketing and Retail Analytics
        • Web and Social Media Analytics
        • Supply Chain & Logistics Analysis
        • Finance and Risk Analysis
      • Cost: $3,500 USD
  • Data-Driven Decision Making
    • Source: Management Concepts - https://www.managementconcepts.com/course/id/4604
    • Overview: Sound business strategy requires robust data. However, raw data can only go so far without effective interpretation and analysis to inform decision-making. You will apply a data-driven process to decision-making while considering both the larger business context around risk and uncertainty and the organizational factors that influence stakeholder acceptance of data-driven conclusions. Relevant examples will help you learn to arrive at decisions individually, as a team, or as an organization—while maintaining a strategic lens that supports overarching goals.
    • Cost: $909 (2-day course)
      • Delivery Method: Instructor-led live classroom
      • Alternative Delivery Methods: Instructor-led online (synchronous)