Technologies / Data & Analytics

Data Science in Big Data analysis

The training provides an advanced approach to Big Data analysis using Data Science methods. The program combines statistical theory with practical applications in a large-scale environment. Participants work on real data sets, learning to implement advanced analytical models. The class covers the full life cycle of a Data Science project, from data preparation to implementation of models in a production environment.

Issues

Machine learning algorithms for large data sets
Methods for preparing and cleaning data at the scale of Big Data
Platforms for processing distributed datasets
Dimensionality reduction and feature selection techniques
Predictive models and their implementation
Analysis of temporal and streaming data
Evaluation and comparison of analytical models
Methods for visualizing large data sets
Big Data system architectures
ETL process optimization in Data Science projects
Ethical aspects of data analysis and privacy
Strategies for implementing models in production

Benefits

Practical ability to design and implement advanced analytical models on large data sets.
Deep understanding of the statistical underpinnings of machine learning algorithms and their applications in Big Data.
Ability to optimize and scale analytical processes for increased efficiency.
Knowledge of tools and technologies to support the Data Science process in a Big Data environment.
Ability to visualize and present the results of the analysis to different audiences.
Ability to implement analytical models into production environments with good practices.
Expertise in monitoring and updating analytical models in real time.

Who is this training for?

Data Scientists

Data analysts

Machine Learning Specialists

Data engineers

Researchers involved in data analysis

Predictive modeling specialists

Data visualization experts

Business analysts interested in Data Science

Prerequisites

Basic knowledge of statistics and data analysis
Ability to program in Python or R
Experience working with relational databases and SQL
Basic knowledge of machine learning
Knowledge of data processing issues

Training program

Statistics in Big Data
Data preparation
Exploratory data analysis
Advanced modeling
Machine learning at the scale of Big Data

Ensemble models
Validation and evaluation of models
Implementation of solutions
Scaling models
Performance optimization

Process automation
Implementation and monitoring

Version management
Performance monitoring
Update models

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Frequently asked questions

What are the prerequisites for this training?

For Data Science in Big Data analysis we recommend: Basic knowledge of statistics and data analysis; Ability to program in Python or R; Experience working with relational databases and SQL.

What is the format and duration of this training?

The training lasts 5 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: Data Scientists; Data analysts; Machine Learning Specialists.