Site Map - skillsoft.digitalbadges-eu.skillsoft.com
- User Authentication
- Ursula George's Credentials
- Ursula George's Wallet
- Navigating AI Ethical Challenges and Risks
- Scrum Master: Advanced Facilitation & Coaching Practices
- Creating Data APIs Using Node.js
- Machine & Deep Learning Algorithms: Introduction
- Data Science Statistics: Using Python to Compute & Visualize Statistics
- Tableau Desktop: Real Time Dashboards
- Data Science Statistics: Applied Inferential Statistics
- Storytelling with Data: Tableau & Power BI
- Machine & Deep Learning Algorithms: Regression & Clustering
- Data Insights, Anomalies, & Verification: Handling Anomalies
- Streaming Data Architectures: Processing Streaming Data with Spark
- Data Recommendation Engines
- Machine & Deep Learning Algorithms: Imbalanced Datasets Using Pandas ML
- Machine & Deep Learning Algorithms: Data Preparation in Pandas ML
- Final Exam: Data Scientist
- Data Research Techniques
- Advanced Visualizations & Dashboards: Visualization Using R
- Data Insights, Anomalies, & Verification: Machine Learning & Visualization Tools
- Data Research Exploration Techniques
- Data Research Statistical Approaches
- Statistical & Hypothesis Tests: Using Non-parametric Tests & ANOVA Analysis
- Final Exam: Statistics and Probability
- Track 2: Statistics and Probability
- Data Scientist
- Streaming Data Architectures: An Introduction to Streaming Data in Spark
- Storytelling with Data: Introduction
- R for Data Science: Data Visualization
- Advanced Visualizations & Dashboards: Visualization Using Python
- Raw Data to Insights: Data Ingestion & Statistical Analysis
- Data Science Tools
- The Four Vs of Data
- Clustering, Errors, & Validation
- Data Driven Organizations
- Raw Data to Insights: Data Management & Decision Making
- Probability Distributions: Understanding Normal Distributions
- Statistical & Hypothesis Tests: Getting Started with Hypothesis Testing
- Data Communication & Visualization
- Probability Distributions: Uniform, Binomial, & Poisson Distributions
- Statistical & Hypothesis Tests: Using the One-sample T-test
- Statistical & Hypothesis Tests: Performing Two-sample T-tests & Paired T-tests
- Data Transformation
- Data Filtering
- Data Integration
- Estimates & Measures
- Core Statistical Concepts: Statistics & Sampling with Python
- Probability Distributions: Getting Started with Probability Distributions
- Probability Theory: Getting Started with Probability
- Probability Theory: Understanding Joint, Marginal, & Conditional Probability
- Probability Theory: Creating Bayesian Models
- Data Gathering
- Data Architecture Deep Dive - Design & Implementation
- Data Lake Architectures & Data Management Principles
- Final Exam: Data Wrangler
- Data Architecture Deep Dive - Microservices & Serverless Computing
- Data Wrangler
- Data Analysis Using the Spark DataFrame API
- Data Analysis using Spark SQL
- Data Lake Framework & Design Implementation
- Hadoop MapReduce Applications With Combiners
- Advanced Operations Using Hadoop MapReduce
- MongoDB Querying
- MongoDB Aggregation
- Optimizing Query Executions with Hive
- Using Hive to Optimize Query Executions with Partitioning
- Loading & Querying Data with Hive
- Getting Started with Hive
- Viewing & Querying Complex Data with Hive
- Bucketing & Window Functions with Hive
- Filtering Data Using Hadoop MapReduce
- Core Statistical Concepts: An Overview of Statistics & Sampling
- Technology Landscape & Tools for Data Management
- Cleaning Data in R
- Machine Learning & Deep Learning Tools in the Cloud
- Python - Using Pandas to Work with Series & DataFrames
- Data Wrangling with Trifacta
- Python - Pandas Advanced Features
- Python - Using Pandas for Visualizations and Time-Series Data
- Python for Data Science: Advanced Data Visualization Using Seaborn
- Python - Manipulating & Analyzing Data in Pandas DataFrames
- Python for Data Science: Basic Data Visualization Using Seaborn
- Python - Advanced Operations with NumPy Arrays
- Python - Introduction to Pandas and DataFrames
- Python - Introduction to NumPy for Multi-dimensional Data
- Final Exam: Business Analyst to Data Analyst
- Analyzing Data Using Python: Filtering Data in Pandas
- Analyzing Data Using Python: Cleaning & Analyzing Data in Pandas
- Analyzing Data Using Python: Importing, Exporting, & Analyzing Data With Pandas
- Analyzing Data Using Python: Data Analytics Using Pandas
- Using BigML: Unsupervised Learning
- Using BigML: Getting Hands-on with BigML
- Using BigML: An Introduction to Machine Learning & BigML
- Using BigML: Building Supervised Learning Models
- VBA: Getting Started with VBA in Excel
- VBA: Building User Interfaces with Forms in VBA & Excel
- VBA: Leveraging VBA to Work with Charts, Stocks, & MS Access
- Final Exam: Business Analyst
- Complete Guide to Excel 365: Pivot, PowerPivot, & Financial Modeling
- Complete Guide to Excel 365: What-If Analysis, Solver, & Analysis ToolPak
- Complete Guide to Excel 365: Validating, Cleaning, & Performing Lookups on Data
- Complete Guide to Excel 365: Using Formatting, Styles, & Themes
- Complete Guide to Excel 365: Linking, Printing, & Protecting Workbooks
- Complete Guide to Excel 365: Working With Charts & Sparklines
- Complete Guide to Excel 365: Getting Started
- Generative AI and Its Impact to Everyday Business
- Organizational IT Trends, Analytics, and Application Development
- Spark for High-speed Big Data Analytics
- Techniques for Big Data Analytics
- Big Data Concepts: Getting to Know Big Data
- Big Data Concepts: Big Data Essentials
- Six Sigma and Lean: Foundations and Principles
- Best Practices for Digital Transformation
- Creating a Coaching at Scale Program
- Prioritizing and Delivering Value (2021 Update)
- Agile Project Management Bootcamp: Session 1 Replay
- Communicating and Engaging Teams and Stakeholders (2021 Update)
- Ursula George's Transcript
- Ursula George's Wallet
- About Accredible