Site Map - skillsoft.digitalbadges.skillsoft.com
- User Authentication
- Prabhu Babu Swamy's Credentials
- Prabhu Babu Swamy's Wallet
- Track 5: Introductory Statistics
- Data Science Foundations
- Track 4: Data Cleaning with Python
- Track 3: Data Visualization with Python
- Track 2: Exploratory Data Analysis with Python
- Track 1: Python for Data Science
- Python Classes & Inheritance: Advanced Functionality Using Python Classes
- Python Classes & Inheritance: Working with Inheritance in Python
- Python Classes & Inheritance: Getting Started with Classes in Python
- Advanced Python Topics: Exceptions & Command Line Arguments
- Advanced Python Topics: File Operations in Python
- Final Exam: Python Novice
- Functions in Python: Working with Advanced Features of Python Functions
- Functions in Python: Gaining a Deeper Understanding of Python Functions
- Functions in Python: Introduction
- Conditional Statements & Loops: While Loops in Python
- Conditional Statements & Loops: The Basics of for Loops in Python
- Developing an AI/ML Data Strategy: The Data Analytics Maturity Model
- Fundamentals of AI & ML: Introduction to Artificial Intelligence
- Track 1: Fundamentals of AI and ML
- Fundamentals of AI & ML: Advanced Data Science Methods
- Fundamentals of AI & ML: Foundational Data Science Methods
- Conditional Statements & Loops: Advanced Operations Using for Loops in Python
- The Four Vs of Data
- Dash Python Framework: Leveraging Dash with User Input & Dash DataTable
- Dash Python Framework: Dash for Interactive Web Apps
- Python with Altair: Working with Specialized Graphs
- Python with Altair: Plotting Fundamental Graphs
- Python with Altair: An Introduction to Altair
- Captivate Everyone You Meet and Never Be Forgotten, Overlooked or Interrupted Again
- Python Statistical Plots: Time Series Data & Regression Analysis in Seaborn
- Python Statistical Plots: Visualizing & Analyzing Data Using Seaborn
- Track 1: Python for Developers
- Final Exam: Python for Developers
- Python Development: Creating Classes, Handling Errors, & Importing Modules
- Python Development: Leveraging Functions with Lambdas, Generators, Closures, & Decorators
- Python Development: Defining, Configuring, & Invoking Functions
- Python Development: Working with If Statements, Loops, & Comprehensions
- Python Development: Performing Operations with Complex Data Types
- Python Development: Getting Started with Programming in Python
- How to Get Out of Your Own Way and Achieve Success
- Getting Started with Java: The Fundamentals of Java Programming
- Track 4: Statistical Analysis and Modeling in R
- Data Analysis with R
- Conditional Statements & Loops: If-else Control Structures in Python
- Complex Data Types in Python: Shallow & Deep Copies in Python
- Complex Data Types in Python: Working with Dictionaries & Sets in Python
- Complex Data Types in Python: Working with Lists & Tuples in Python
- Getting Started with Python: Introduction
- Getting to the Root of a Problem
- VBA: Building User Interfaces with Forms in VBA & Excel
- VBA: Getting Started with VBA in Excel
- Final Exam: Statistical Analysis and Modeling in R
- Statistical Analysis and Modeling in R: Building Regularized Models & Ensemble Models
- Statistical Analysis and Modeling in R: Performing Clustering
- Statistical Analysis and Modeling in R: Performing Classification
- Statistical Analysis and Modeling in R: Statistical Analysis on Your Data
- Statistical Analysis and Modeling in R: Performing Regression Analysis
- Statistical Analysis and Modeling in R: Understanding & Interpreting Statistical Tests
- Statistical Analysis and Modeling in R: Working with Probability Distributions
- Track 3: Working with Datasets in R
- Final Exam: Working with Datasets in R
- Datasets in R: Selecting, Filtering, Ordering, & Grouping Data
- Datasets in R: Joining & Visualizing Data
- Datasets in R: Loading & Saving Data
- Datasets in R: Transforming Data
- Track 2: Applying and Using R Programming Structures
- Final Exam: Applying and Using R Programming Structures
- Using R Programming Structures: Functions & Environments
- Using R Programming Structures: Leveraging R with Control Flow & Looping
- Track 1: Getting Started with R Programming
- Final Exam: Getting Started with R Programming
- R Programming for Beginners: Understanding Data Frames, Factors, & Strings
- Using R Programming Structures: Object Systems
- R Programming for Beginners: Leveraging R with Matrices, Arrays, & Lists
- R Programming for Beginners: Exploring R Vectors
- R Programming for Beginners: Getting Started
- Communicating with Confidence
- The Art and Science of Communication
- Cleaning Data in R
- Inferential Statistics
- Common Approaches to Sampling Data
- R Classification & Clustering
- R for Data Science: Data Visualization
- Simple Descriptive Statistics
- R Regression Methods
- Data Exploration using R
- Python - Manipulating & Analyzing Data in Pandas DataFrames
- Abbreviating, Capitalizing, and Using Numbers
- Python - Introduction to Pandas and DataFrames
- K-Nearest Neighbor (k-NN) & Artificial Neural Networks
- Getting the Details Right: Spelling Basics
- Using the Parts of Speech
- Python - Advanced Operations with NumPy Arrays
- Data Architecture Getting Started
- Data Engineering Getting Started
- Python - Introduction to NumPy for Multi-dimensional Data
- Importing & Exporting Data using R
- Python - Using Pandas to Work with Series & DataFrames
- Advanced and Interactive Visualization in R Bootcamp: Session 1 Replay
- Graph & Charts
- Power BI: Getting Started with Data Analytics
- Planning an Effective Presentation
- R Data Structures
- Prabhu Babu Swamy's Transcript
- Prabhu Babu Swamy's Wallet
- About Accredible