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- Python Development: Creating Classes, Handling Errors, & Importing Modules
- Python Development: Defining, Configuring, & Invoking Functions
- Python Development: Working with If Statements, Loops, & Comprehensions
- Python Development: Getting Started with Programming in Python
- Data Science for Managers 2023 Bootcamp: Session 2 Replay
- AWS Solutions Architect Associate 2022: Data Storage Services
- AWS Solutions Architect Associate 2022: Managing S3 Buckets
- AWS Solutions Architect Associate 2022: Architecture & Tools
- AWS Solutions Architect Associate 2022: Security & Data Privacy
- Data Science for Managers Bootcamp: Session 3 Replay
- Applying Predictive Analytics
- Data Structures & Algorithms in Python: Sorting Algorithms
- Data Structures & Algorithms in Python: Implementing Sorting Algorithms
- Data Structures & Algorithms in Python: Implementing Data Structures
- Data Structures & Algorithms in Python: Fundamental Data Structures
- Python Classes & Inheritance: Working with Inheritance in Python
- Python Classes & Inheritance: Advanced Functionality Using Python Classes
- Advanced Python Topics: Migrating from Python 2 to Python 3
- Python Classes & Inheritance: Introduction
- Python Classes & Inheritance: Getting Started with Classes in Python
- Advanced Python Topics: Modules & Virtual Environments
- Advanced Python Topics: Exceptions & Command Line Arguments
- Advanced Python Topics: File Operations in Python
- AWS Certified Machine Learning: Data Engineering, Machine Learning, & AWS
- Introduction to Lambda
- Data Migration & EMR
- Functions in Python: Introduction
- Functions in Python: Gaining a Deeper Understanding of Python Functions
- Functions in Python: Working with Advanced Features of Python Functions
- Conditional Statements & Loops: While Loops in Python
- Conditional Statements & Loops: Advanced Operations Using for Loops in Python
- Conditional Statements & Loops: The Basics of for Loops in Python
- Complex Data Types in Python: Working with Dictionaries & Sets in Python
- Complex Data Types in Python: Working with Lists & Tuples in Python
- Complex Data Types in Python: Shallow & Deep Copies in Python
- Conditional Statements & Loops: If-else Control Structures in Python
- Machine & Deep Learning Algorithms: Imbalanced Datasets Using Pandas ML
- ML/DL in the Enterprise: Pipelines & Infrastructure
- Python for Data Science: Basic Data Visualization Using Seaborn
- Predictive Modeling: Implementing Predictive Models Using Visualizations
- ML/DL in the Enterprise: Machine Learning Modeling, Development, & Deployment
- Data Wrangling in Python Bootcamp: Session 4 Replay
- Enterprise Services: Enterprise Machine Learning with AWS
- Python - Using Pandas to Work with Series & DataFrames
- Python - Introduction to NumPy for Multi-dimensional Data
- Python - Advanced Operations with NumPy Arrays
- Python - Introduction to Pandas and DataFrames
- Python - Manipulating & Analyzing Data in Pandas DataFrames
- Data Wrangling in Python Bootcamp: Session 1 Replay
- Data Wrangling in Python Bootcamp: Session 2 Replay
- Predictive Modeling: Predictive Analytics & Exploratory Data Analysis
- Training Neural Networks: Implementing the Learning Process
- Bayesian Methods: Bayesian Concepts & Core Components
- Getting Started with Neural Networks: Biological & Artificial Neural Networks
- Getting Started with Neural Networks: Perceptrons & Neural Network Algorithms
- Building Neural Networks: Artificial Neural Networks Using Frameworks
- Building Neural Networks: Development Principles
- Linear Models & Gradient Descent: Gradient Descent and Regularization
- Math for Data Science & Machine Learning
- Linear Models & Gradient Descent: Managing Linear Models
- Model Management: Building Machine Learning Models & Pipelines
- Building ML Training Sets: Introduction
- Simplifying Regression and Classification with Estimators
- Building ML Training Sets: Preprocessing Datasets for Classification
- Building ML Training Sets: Preprocessing Datasets for Linear Regression
- Computational Theory: Language Principle & Finite Automata Theory
- Model Management: Building & Deploying Machine Learning Models in Production
- Linear Regression Models: Introduction to Logistic Regression
- Linear Regression Models: Introduction
- Linear Regression Models: Building Models with Scikit Learn & Keras
- Linear Regression Models: Multiple & Parsimonious
- Linear Algebra & Probability: Advanced Linear Algebra
- 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
- Partner Training - Solutions Architect Essentials
- Partner Training - Developer Essentials
- Partner Training - Developer Foundations
- Machine & Deep Learning Algorithms: Introduction
- Introducing Natural Language Processing
- Supervised Learning Models
- Data Science Fundamentals
- Exceptions
- Python: Getting Started
- Defensive Programmer: Defensive Techniques
- Getting Started with Python: Introduction
- Modules & Functions
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