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Data Management, Visualization and Analytical Modeling

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  • Data Management, Visualization and Analytical Modeling
Database Management Systems
  • Introduction to Databases
  • Database Design Principles
  • SQL Syntax and Query Fundamentals
  • Data Definition Language (DDL)
  • Data Manipulation Language (DML)
  • Data Control Language (DCL)
  • Transaction Management
  • Indexing and Optimization Techniques
  • Normalization
  • Entity-Relationship (ER) Model
  • SQL Joins and Subqueries
  • Stored Procedures and Functions
  • Database Security
  • Backup and Recovery Techniques
Exploratory Data Analysis
  • Data Quality Assessment
  • Handling Missing Values
  • Data Filtering
  • Outlier Detection
  • Data Transformation
  • Feature Scaling and Normalization
  • Encoding Categorical Data
  • Data Integration
  • Date and Time Data Handling
  • Dealing with Duplicate Data
  • Using Regular Expressions for Data Cleaning
  • Data Validation Techniques
Data Visualization using Power BI
  • Introduction to Power BI
  • Power BI Desktop Interface
  • Data Importing and Transformation
  • Data Modeling
  • Creating Dashboards
  • DAX Basics
  • Visualization Techniques
  • Publishing and Sharing Reports
  • Power BI Service
  • Data Refresh and Scheduling
  • Integrating Power BI with Other Tools
  • Security Features in Power BI
  • Advanced DAX Functions
Machine Learning
  • Introduction to Machine Learning
  • Types of Machine Learning (Supervised, Unsupervised, Reinforcement)
  • Data Preprocessing
  • Feature Engineering
  • Regression Analysis
  • Classification Techniques
  • Decision Trees
  • Random Forests
  • Support Vector Machines
  • Neural Networks
  • Deep Learning
  • Clustering Algorithms
  • Dimensionality Reduction
  • Ensemble Methods
  • Model Evaluation and Validation
  • Hyperparameter Tuning
  • Machine Learning Pipelines

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