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- Performance Engineering: Optimizing Database Performance
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- R for Data Science: Data Visualization
- Python for Data Science: Advanced Data Visualization Using Seaborn
- Machine Learning & Data Analytics
- Python - Advanced Operations with NumPy Arrays
- Python - Manipulating & Analyzing Data in Pandas DataFrames
- Python - Pandas Advanced Features
- R Data Structures
- Importing & Exporting Data using R
- Data Exploration using R
- R Regression Methods
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- Cleaning Data in R
- Statistics & Data Visualization
- Python - Introduction to NumPy for Multi-dimensional Data
- Deep Learning & Neural Network Implementation
- Implementing ML Algorithm Using scikit-learn
- AI Fundamentals
- Introduction
- Python for Data Science: Basic Data Visualization Using Seaborn
- Supervised, Unsupervised & Deep Learning
- Python - Introduction to Pandas and DataFrames
- Configuration, Advanced Help, & Queries
- Remote Management
- Output Formatting, Modules, & Customization
- Aliases, Providers, & Objects
- Cmdlet Structure & Help
- Syntax, Help, & Conditionals
- Introduction
- IT Infrastructure Automation: Python Automation Programming
- JSON Essentials
- SQL Concepts & Queries
- CompTIA Linux+: Introduction to Linux & the Command Line
- CompTIA A+ 220-1001: TCP & UDP ports
- DEVASC: Network & Network Communication Basics
- Need for Design Patterns & the Principles Guiding Design Patterns
- APIs
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- Cloud Computing Fundamentals: Introduction
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- Jenkins for DevOps: Jenkins Configuration for DevOps
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- Using Docker for DevOps: Introduction to Docker
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- Agile Software Development - Scrum
- Using Kanban in IT & Software Development
- Agile Test-Driven Development
- Software Data Analysis: Project Management Metrics
- SOLID & GRASP
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