Site Map - skillsoft.digitalbadges.skillsoft.com
- User Authentication
- Arindam Bhattacharya's Credentials
- Arindam Bhattacharya's Wallet
- Track 1: Introduction to Large Language Models (LLMs)
- Introduction to Large Language Models (LLMs)
- Track 1: OpenAI API
- Open AI GPT API
- The Essential Role of the Agile Product Owner
- Developing and Supporting an Agile Mindset
- Predictive Analytics: Identifying Tumors with Deep Learning Models
- Predictive Analytics: Detecting Kidney Disease Using AI
- Predictive Analytics: Case Studies on Predictive Analytics for Healthcare
- Predictive Analytics: Performing Prediction Using Regression
- Predictive Analytics: Performing Classification Using Machine Learning
- Predictive Analytics: Applying Clustering to Soil Features & Conditions
- Predictive Analytics: Case Studies for AI in Agriculture
- Predictive Analytics: Customer Segmentation & Market Basket Analysis
- Predictive Analytics: Predicting Responses to Marketing Campaigns
- Predictive Analytics: Predicting Sales & Customer Lifetime Value
- Predictive Analytics: Identifying Machine Failures
- Predictive Analytics: Case Studies for Operations
- Predictive Analytics: Using SMOTE, Model Explanations, & Hyperparameter Tuning
- Predictive Analytics: Case Studies for Marketing & Retail
- Predictive Analytics: Identifying Network Attacks
- Predictive Analytics: Case Studies for Cybersecurity
- Linear Regression Models: Introduction to Logistic Regression
- Model Management: Building Machine Learning Models & Pipelines
- Simplifying Regression and Classification with Estimators
- Computational Theory: Language Principle & Finite Automata Theory
- Computational Theory: Using Turing, Transducers, & Complexity Classes
- Linear Regression Models: Multiple & Parsimonious
- Model Management: Building & Deploying Machine Learning Models in Production
- Linear Algebra & Probability: Advanced Linear Algebra
- Linear Regression Models: Introduction
- Linear Regression Models: Building Models with Scikit Learn & Keras
- Linear Algebra and Probability: Fundamentals of Linear Algebra
- NLP for ML with Python: NLP Using Python & NLTK
- NLP for ML with Python: Advanced NLP Using spaCy & Scikit-learn
- Computer Vision: AI & Computer Vision
- Computer Vision: Introduction
- Cognitive Models: Overview of Cognitive Models
- Python AI Development: Introduction
- Artificial Intelligence: Human-computer Interaction Methodologies
- Python AI Development: Practice
- Artificial Intelligence: Human-computer Interaction Overview
- Artificial Intelligence: Basic AI Theory
- Artificial Intelligence: Types of Artificial Intelligence
- Neural Network Mathematics: Understanding the Mathematics of a Neuron
- ML & Dimensionality Reduction: Performing Principal Component Analysis
- Neural Network Mathematics: Exploring the Math behind Gradient Descent
- Support Vector Machine (SVM) Math: Building & Applying SVM Models in Python
- Track 3: Math Behind ML Algorithms
- Recommender Systems: Under the Hood of Recommendation Systems
- Track 4: Advanced Math
- Essential Math for Data Science
- Final Exam: Advanced Math
- Final Exam: Math Behind ML Algorithms
- The Math Behind Decision Trees: An Exploration of Decision Trees
- Support Vector Machine (SVM) Math: A Conceptual Look at Support Vector Machines
- Distance-based Models: Overview of Distance-based Metrics & Algorithms
- Regression Math: Using Gradient Descent & Logistic Regression
- Distance-based Models: Implementing Distance-based Algorithms
- Regression Math: Getting Started with Linear Regression
- Statistical & Hypothesis Tests: Using Non-parametric Tests & ANOVA Analysis
- Track 2: Statistics and Probability
- Final Exam: Statistics and Probability
- Statistical & Hypothesis Tests: Performing Two-sample T-tests & Paired T-tests
- Statistical & Hypothesis Tests: Using the One-sample T-test
- Statistical & Hypothesis Tests: Getting Started with Hypothesis Testing
- Probability Distributions: Understanding Normal Distributions
- Probability Distributions: Uniform, Binomial, & Poisson Distributions
- Probability Distributions: Getting Started with Probability Distributions
- Probability Theory: Understanding Joint, Marginal, & Conditional Probability
- Core Statistical Concepts: Statistics & Sampling with Python
- Probability Theory: Creating Bayesian Models
- Probability Theory: Getting Started with Probability
- Setting up the Data Infrastructure in an Organization
- Data Nuts & Bolts: Fundamentals of Data
- Scalable Data Architectures: Getting Started
- Data Architecture Deep Dive - Microservices & Serverless Computing
- Data Engineering Getting Started
- Data Silos, Lakes, & Streams Introduction
- Data Lake Framework & Design Implementation
- Implementing Governance Strategies
- Data Lake Architectures & Data Management Principles
- Building Career Development Programs and Succession Planning
- Data Architecture Deep Dive - Design & Implementation
- Common Approaches to Sampling Data
- Data Architecture Getting Started
- Data Compliance Issues & Strategies
- Calculus: Understanding Integration
- Matrix Decomposition: Using Eigendecomposition & Singular Value Decomposition
- Matrix Decomposition: Getting Started with Matrix Decomposition
- Essential Maths: Exploring Linear Algebra
- Core Statistical Concepts: An Overview of Statistics & Sampling
- Track 1: Introduction to Math
- Math & Optimizations: Solving Optimization Problems Using Linear Programming
- Calculus: Getting Started with Derivatives
- Math & Optimizations: Solving Optimization Problems Using Integer Programming
- Calculus: Derivatives with Linear and Quadratic Functions & Partial Derivatives
- Application Developer to Blockchain Solutions Architect
- Blockchain Solutions Architect
- Math & Optimizations: Introducing Sets & Set Operations
- Final Exam: Blockchain Solutions Architect
- Cloud Blockchains: Building Apps on the Azure Blockchain Workbench
- Math & Optimizations: Introducing Graphs & Graph Operations
- Blockchain Engineer
- Blockchain & Hyperledger Fabric: An Overview of Blockchain Technology
- Cloud Blockchains: An Introduction to Blockchain on the Cloud
- Blockchain & Hyperledger Fabric: The Hyperledger Fabric
- Cloud Blockchains: Multi-Organization Networks on Amazon Managed Blockchain
- Blockchain & Hyperledger Fabric: An Overview of Hyperledger
- Cloud Blockchains: Single Organization Networks on Amazon Managed Blockchain
- Building Decentralized Applications for Ethereum: Building the Front End
- Building Decentralized Applications for Ethereum: Building the Back End
- Truffle Suite: Using Drizzle to Build Decentralized Apps
- Final Exam: Blockchain Engineer
- Building Decentralized Applications for Ethereum: An Introduction to dApps
- Building Decentralized Applications for Ethereum: Bespoke Ethereum Blockchain Tokens
- Blockchain Smart Contracts Programmer
- Smart Contracts & Hyperledger Fabric: Hyperledger Composer Playground
- Smart Contracts & Hyperledger Fabric: Web Apps for Hyperledger Composer Networks
- Truffle Suite: Introduction
- Truffle Suite: BlockBuilding Private Blockchain Networks with Ganache
- Truffle Suite: Automating Development with the Truffle Framework
- Final Exam: Blockchain Smart Contracts Programmer
- Smart Contracts & Hyperledger Fabric: Foundations of Hyperledger Fabric
- Smart Contracts & Hyperledger Fabric: Setting Up a Hyperledger Fabric Network
- Smart Contracts & Hyperledger Fabric: Working with Fabric Chaincode in Golang
- Smart Contracts & Hyperledger Fabric: Working with Fabric Chaincode in Node.js
- Smart Contracts & Hyperledger Fabric: Hyperledger Fabric Web App
- Ethereum Smart Contracts with Solidity: Build Decentralized Apps
- Ethereum Smart Contracts with Solidity: The Remix Solidity IDE
- Ethereum Smart Contracts with Solidity: Functions in Solidity
- Ethereum Smart Contracts with Solidity: Ether Transfer Operations in Solidity
- Ethereum Smart Contracts with Solidity: Data & Control Structures in Solidity
- Ethereum Smart Contracts with Solidity: Features of the Solidity Language
- Blockchain Application Developer
- Final Exam: Blockchain Application Developer
- Ethereum Smart Contracts with Solidity: An Overview of Ethereum and Solidity
- Working with Ethereum: Tools for Smart Contract Development
- Working with Ethereum: Smart Contract Development
- Working with Ethereum: Metamask & the Ethereum Wallet
- Working with Ethereum: Lifecycle of a Smart Contract
- Working with Ethereum: The Geth Client
- Blockchains & Ethereum: Introduction
- Blockchains & Ethereum: Performing Transactions in Ethereum
- Working with Ethereum: Storing Data
- Blockchains & Ethereum: Mining & Smart Contracts in Ethereum
- Talent Development and Transformation: Transforming Your Leadership: Session Replay
- Getting Started with Go: Basic Programming
- Getting Started with Python: Introduction
- Getting Started with Go: Introducing Go Programming Language
- Software Project Lead to Advanced Scrum Master
- Advanced Scrum Master
- Scaling an Organization's Scrum Process
- Advanced Scrum Metrics
- Scaling Scrum: Challenges
- Accessing the Business Value of Scrum
- Final Exam: Advanced Scrum Master
- Scaling Scrum: Choosing Scaled Agile Frameworks
- Advanced Lean, Agile, & Scrum Concepts
- Scrum Master
- Scrum Master: Sprint Goals & Planning
- SCRUM Quality, Planning, and Completion: The Definition of Done
- SCRUM Quality, Planning, and Completion: Effective User Stories
- Scrum Sprint: Retrospective
- SCRUM Quality, Planning, and Completion: Quality & Productivity
- Scrum Sprint: Review
- Final Exam: Scrum Master Responsibilities
- Scrum Team Velocity: Exploring Team Velocity
- SCRUM Meetings: On-target Daily Meetings
- Scrum Master: Scrum for the Team
- Software Product Owner
- Software Project Lead
- Applying Scrum Development Practices
- Scrum Practices: Managing the Scrum Project
- Final Exam: Software Product Owner
- Scrum: Creating Effective Product Backlogs
- Scrum: Product Backlog
- Scrum Concepts & the Product Owner
- Scrum: Product Development Framework
- Scrum Product: Defining the Why & How of the Product
- Final Exam: Software PM Lead
- Lean in Scrum: Lean Development Practices
- Transitioning to Scrum
- Product Development Practices
- Marketing and Competition
- Building and Leading Teams
- Product Management Journey
- Strategic and Critical Thinking
- Developing Your Critical Thinking and Cognitive Flexibility
- Expert Insights on Digital Marketing
- Transition to Scrum: Agile Foundation to Scrum
- Strategies for Managing Technical Teams
- Establishing Effective Virtual Teams
- Facing Virtual Team Challenges
- Building and Leading Successful Teams
- Measuring Outcomes and Using KPIs
- Assessing Your Organization's Risks
- Thinking Strategically as a Manager
- Responding Effectively to Risks
- Using Strategic Thinking to Consider the Big Picture
- Leading a Cross-functional Team
- Effective Team Communication
- Expert Insights on Critical Thinking
- Identifying Risks in Your Organization
- Design Thinking
- Innovation and Creativity
- Getting Started with Design Thinking
- Unleashing Personal and Team Creativity
- Expert Insights on Creative Thinking & Brainstorming
- Expert Insights on Social Media Marketing
- Design Thinking for Innovation: Stakeholder Engagement
- Design Thinking for Innovation: Brainstorming and Ideation
- Design Thinking for Innovation: Defining Opportunities
- Developing a Team of Creative Gurus
- Expert Insights on Design Thinking
- Design Thinking for Innovation: Prototyping and Testing
- Expert Insights on Innovation
- Verifying and Building on Creative Ideas
- Competitive Marketing Strategies: Analyzing Your Organization
- Traditional and Online Distribution and Ethics in the Marketing Mix
- Product, Pricing, and Promotion in the Marketing Mix
- The Basics of Marketing
- The People and Planning in Marketing
- Steps to Creativity Series
- Product Management Introduction
- Product Management: Designing and Running Experiments
- Product Management: Create a Go-to-Market Plan
- Product Management: Communication for Product Managers
- Product Management: Metrics for Product Managers
- Product Management: Understanding and Developing Customers
- Product Management: Building a Product Strategy
- Product Management: An Overview
- AWS Certified Machine Learning: AI/ML Services
- AWS Certified Machine Learning: Advanced SageMaker Functionality
- Product Management: Competitive and Market Analytics for Product Managers
- Product Management: Building a Product Roadmap and Agile Product Management
- AWS Certified Machine Learning: Problem Framing & Algorithm Selection
- AWS Certified Machine Learning: Machine Learning in SageMaker
- AWS Certified Machine Learning: ML Algorithms in SageMaker
- AWS Certified Machine Learning: AI Services & SageMaker Applications
- AWS Certified Machine Learning: Problem Formulation & Data Collection
- AWS Certified Machine Learning: Data Preparation & SageMaker Security
- AWS Certified Machine Learning: Model Training & Evaluation
- AWS Certified Machine Learning: Feature Engineering Techniques
- AWS Certified Machine Learning: Data Pipelines & Workflows
- AWS Certified Machine Learning: Data Analysis Fundamentals
- AWS Certified Machine Learning: Athena, QuickSight, & EMR
- AWS Certified Machine Learning: Feature Engineering Overview
- AWS Certified Machine Learning: Amazon S3 Simple Storage Service
- AWS Certified Machine Learning: Jupyter Notebook & Python
- AWS Certified Machine Learning: Data Engineering, Machine Learning, & AWS
- AWS Certified Machine Learning: Data Movement
- Defining a Project Scope and Team
- Advanced Agile: Software Project Management
- Pivot Series
- Gaining Insight through Organizational Awareness
- Developing Your Business Acumen
- Expert Insights on Career Planning
- Getting Your Career on the Right Track
- Developing a Plan to Further Your Career
- Using Performance Appraisals to Advance Your Career
- Developing a Growth Mindset
- Arindam Bhattacharya's Transcript
- Arindam Bhattacharya's Wallet
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