Advanced Data Analysis Techniques

Course Info

Date: Dec-29-2025

Length: 1 Week

City: Kuala Lumpur

Fees: 3,990

Type: In Classroom

Available Dates

  • Mar-31-2025

    Kuala Lumpur

  • June-30-2025

    Kuala Lumpur

  • Sep-29-2025

    Kuala Lumpur

  • Dec-29-2025

    Kuala Lumpur

Dates in Other Venues

  • Dec-30-2024

    Singapore

  • Dec-30-2024

    Barcelona

  • Jan-20-2025

    Dubai

  • Feb-17-2025

    London

  • Mar-31-2025

    Istanbul

  • Mar-31-2025

    Singapore

  • Mar-31-2025

    Paris

  • Mar-31-2025

    Barcelona

  • Mar-31-2025

    Amsterdam

  • Mar-31-2025

    Dubai

  • Apr-21-2025

    London

  • May-19-2025

    Dubai

  • June-30-2025

    Amsterdam

  • June-30-2025

    Paris

  • June-30-2025

    Istanbul

  • June-30-2025

    Barcelona

  • June-30-2025

    London

  • June-30-2025

    Singapore

  • July-21-2025

    Dubai

  • Aug-18-2025

    London

  • Sep-29-2025

    Amsterdam

  • Sep-29-2025

    Dubai

  • Sep-29-2025

    Barcelona

  • Sep-29-2025

    Paris

  • Sep-29-2025

    Singapore

  • Sep-29-2025

    Istanbul

  • Oct-20-2025

    London

  • Nov-17-2025

    Dubai

  • Dec-29-2025

    Barcelona

  • Dec-29-2025

    Paris

  • Dec-29-2025

    Singapore

  • Dec-29-2025

    Istanbul

  • Dec-29-2025

    London

  • Dec-29-2025

    Amsterdam

Course Details

Course Outline

5 days course

Exploratory Data Analysis

  • Introduction to exploratory data analysis (EDA)
  • Techniques for data visualization and exploration
  • Measures of central tendency, dispersion, and correlation
  • Outlier detection and treatment
  • Hand-on examples

Machine Learning for Data Analysis

  • Introduction to machine learning (ML) algorithms
  • Supervised learning: regression, classification, decision trees, random forests
  • Unsupervised learning: clustering, dimensionality reduction
  • Cross-validation and hyperparameter tuning
  • Hand-on examples

Time Series Analysis

 

  • Introduction to time series data
  • Time series decomposition and trend analysis
  • Seasonality and periodicity analysis
  • Autoregressive Integrated Moving Average (ARIMA) models
  • Hand-on examples

Bayesian Data Analysis

  • Introduction to Bayesian statistics
  • Bayes' theorem and probability distributions
  • Bayesian modeling and inference
  • Markov Chain Monte Carlo (MCMC) methods
  • Hand-on examples

 

Big Data Analytics

 

  • Introduction to big data and distributed computing
  • MapReduce and Hadoop ecosystem
  • Apache Spark and Spark SQL
  • Machine learning on big data: Spark MLlib
  • Hand-on examples

Course Video