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Advanced Machine Learning, SQL and R Analytics

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  • Advanced Machine Learning, SQL and R Analytics
Advanced SQL
  • Complex Queries and Subqueries
  • Advanced JOIN Operations
  • Window Functions
  • Common Table Expressions (CTEs)
  • Recursive Queries
  • Indexing and Performance Tuning
  • Stored Procedures and Functions
  • Triggers and Events
  • Dynamic SQL
  • SQL Security Measures
  • Transaction Management and Concurrency Control
  • Handling Large Datasets
  • SQL with JSON and XML
  • Integrating SQL with Other Programming Languages
Time Series
  • Introduction to Time Series Analysis
  • Components of Time Series
  • Time Series Data Collection and Preparation
  • Moving Averages
  • Exponential Smoothing
  • ARIMA Models
  • Seasonal Adjustments
  • Trend Analysis
  • Cyclical and Irregular Components
  • Forecasting Techniques
  • Model Diagnostics and Validation
  • Spectral Analysis
  • Multivariate Time Series Analysis
Data Analysis using R Programming
  • Introduction to R
  • R Studio Interface
  • Data Structures in R (Vectors, Lists, Data Frames, Matrices)
  • Data Import and Export in R
  • Data Manipulation with dplyr
  • Data Cleaning Techniques
  • Exploratory Data Analysis in R
  • Statistical Analysis with R
  • Regression Analysis
  • Classification Techniques
  • Data Visualization with ggplot2
Advanced Machine Learning
  • Ensemble Methods
  • Neural Networks
  • Unsupervised Learning
  • Reinforcement Learning
  • Advanced Regression Techniques
  • Support Vector Machines
  • Natural Language Processing
  • Generative Models
  • Graphical Models
  • Advanced Optimization Techniques
  • Model Evaluation and Hyperparameter Tuning
  • Advanced Feature Engineering
  • Model Interpretability and Explainability
  • Deployment of Machine Learning Models

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