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PROGRAMMING COURSES

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  • What is Business Analytics?
  • Importance of Business
  • Analytics in decision-making
  • Types of Business Analytics (descriptive, predictive, prescriptive)
    • Declaring variables
    • Data types in JavaScript
    • Operators in JavaScript
    • Types of data (structured, unstructured)
    • Data collection methods (surveys, interviews, web scraping, etc.)
    • Data cleaning and preprocessing
    • Data storage and retrieval (databases, data warehouses, data lakes)
    • Data visualization techniques (bar charts, histograms, scatter plots, etc.)
    • Summary statistics (mean, median, mode, standard deviation, etc.)
    • Correlation analysis
    • Segmentation analysis (cluster analysis, market basket analysis)
    • Customer churn analysis
    • Sales forecasting
    • Time series analysis
    • Regression analysis
    • Decision trees
    • Random forests
    • Support Vector Machines (SVM)
    • Neural Networks
    • Optimization techniques (linear programming, integer programming, mixed-integer programming)
    • Simulation and Monte Carlo analysis
    • Game theory
    • Design principles for effective data visualization
    • Tools for data visualization (Tableau, Power BI, etc.)
    • Communicating insights effectively
    • Introduction to Big Data
    • Hadoop and MapReduce
    • Apache Spark
    • NoSQL databases
    • Data warehousing and Business Intelligence OLAP and multidimensional databases Reporting tools (Crystal Reports, SSRS, etc.)
    • Privacy concerns Fairness and bias in algorithms Legal and regulatory issues
    • Current and emerging trends in Business Analytics Artificial Intelligence and Machine Learning Internet of Things (IoT)