Big Data And Analytics Training | High-Dimensional Data Analysis Masterclass in Athens

High-Dimensional Data Analysis Masterclass Course Outline

Module 1: Introduction to High-Dimensional Data Analysis

• Defining High-Dimensional Data
• Why High-Dimensional Data Analysis Matters?
• Challenges and Complexities in High-Dimensional Data
• Real-World Applications and Examples
• Ethical Considerations in Data Analysis

Module 2: Data Preprocessing and Dimension Reduction

• Data Cleaning and Quality Assurance
• Feature Selection Vs Feature Extraction
• Principal Component Analysis
• t-Distributed Stochastic Neighbour Embedding (t-SNE)
• Handling Missing Data in High Dimensions

Module 3: Exploratory Data Analysis (EDA)

• Visualising High-Dimensional Data
• Scatterplot Matrices and Heatmaps
• Clustering Techniques
• Dimensionality Reduction for EDA
• Identifying Outliers and Anomalies

Module 4: Machine Learning for High-Dimensional Data

• Supervised Vs Unsupervised Learning
• Classification and Regression in High Dimensions
• Ensemble Learning Approaches
• Regularisation Techniques
• Handling Imbalanced Data

Module 5: Feature Engineering and Selection Strategies

• Domain Knowledge and Feature Engineering
• Recursive Feature Elimination
• Feature Importance Analysis
• Dealing with High Correlations
• Feature Engineering for Specific Domains

Module 6: Advanced Dimension Reduction Techniques

• Non-Negative Matrix Factorization
• Independent Component Analysis
• Manifold Learning
• Autoencoders and Neural Network-based Dimensionality Reduction
• Application-Specific Approaches

Module 7: Multivariate Analysis in High Dimensions

• Multivariate Regression and Analysis of Variance (ANOVA)
• Canonical Correlation Analysis (CCA)
• Partial Least Squares (PLS)
• MANOVA and Multivariate Classification
• Multivariate Time Series Analysis

Module 8: Big Data and High-Dimensional Data Analysis

• Challenges of Big Data in High Dimensions
• Distributed Computing Frameworks
• Scalable Algorithms for High-Dimensional Data
• Real-Time Analysis of Streaming High-Dimensional Data

Who should attend this High-Dimensional Data Analysis Masterclass?

The High-Dimensional Data Analysis Masterclass is tailored for professionals and researchers who work with complex datasets and seek advanced techniques to extract meaningful insights. This course is valuable for a diverse range of individuals, including:

• Data Scientists
• Machine Learning Engineers
• Statisticians
• Researchers
• Business Analysts
• Bioinformaticians
• Quantitative Analysts

Prerequisites of the High-Dimensional Data Analysis Masterclass

There are no formal prerequisites for the High-Dimensional Data Analysis Masterclass Course. Participants should ideally have a fundamental understanding of data analysis concepts and some experience working with datasets.

High-Dimensional Data Analysis Masterclass Course Overview

High-Dimensional indicates that the number of dimensions are staggeringly high so that calculations become very complex, and with high dimensional data, the count of features can beat the number of views. High-dimensional statistics concentrate on data sets in which the quantity of components is similar to or larger than the number of observations. Data Analysis systematically applies statistical and logical methods to illustrate, describe, condense, and evaluate data. It can help organisations to evaluate their ad campaigns, better know their customers, personalise content, create content strategies, and improve products.

Every business is using data analytics to increase its performance and improve the bottom line. Therefore, there is high demand for professionals who have in-depth knowledge and skills using Data Analysis. Choosing this course can help you take a wonderful career move, and professionals working in this field can easily demand an impressive salary.

Our 1-day High-Dimensional Data Analysis Masterclass Training course aims to provide delegates with a comprehensive knowledge of data analysis. During this course, delegates will learn about oracle and adaptive compound decision rules for FDR control, classical approaches, statistical methods in eQTL studies, regularised cox regression, combining for adaptation and many more. They will also learn about various regularised methods for the accelerated failure time model and theoretic approach to large-scale multiple testing. Our highly professional trainer with years of experience in teaching such courses will conduct this training course and will help you get a complete understanding of this course.

Course Objectives

• To understand the concept and challenges of high-dimensional data
• To apply pre-processing and dimension reduction techniques
• To conduct exploratory and multivariate data analysis
• To implement machine learning strategies for complex datasets
• To utilize advanced feature selection and engineering methods
• To integrate big data tools for high-dimensional analysis
• To develop skills for real-time data analysis applications

After attending this training, delegates will be empowered to apply high-dimensional data analysis techniques confidently and effectively. They will be able to identify, clean, and transform high-dimensional data into a more manageable form, use exploratory data analysis to uncover hidden patterns, and apply various machine learning models to predict and classify complex datasets.

What’s Included in this High-Dimensional Data Analysis Masterclass?

• World-Class Training Sessions from Experienced Instructors
• High-Dimensional Data Analysis Certificate
• Digital Delegate Pack