Big Data Analysis Training with AI Tools
Level
IntermediateDuration
24h / 3 daysDate
Individually arrangedPrice
Individually arrangedBig Data Analysis Training with AI Tools
Dive into the world of Big Data and explore advanced data analysis techniques powered by artificial intelligence. During this 3-day training, you will learn how to use tools such as Apache Spark, Python, and cloud platforms to process and analyze large datasets. With 80% of the course based on practical workshops, you will gain skills that will help you fully leverage the potential of Big Data, optimize analytical processes, and extract valuable insights to support your business decisions.
What You Will Learn
- Processing and analyzing large datasets with Apache Spark.
- Building AI models for predictive analysis and pattern detection in Big Data.
- Designing interactive dashboards and reports for large datasets.
- Implementing Big Data projects in a cloud environment integrated with AI.
Who is this training for?
Data analysts who want to work with large datasets and apply advanced analysis tools.-
IT specialists who want to expand their competencies in Big Data and AI.
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Technology project managers seeking knowledge about Big Data opportunities for business strategies.
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Professionals in industries such as e-commerce, finance, or manufacturing, where Big Data analysis supports company growth.
Training Program
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Day 1: Introduction to Big Data and Artificial Intelligence
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Big Data Basics
- Introduction to Big Data architecture – Hadoop, Apache Spark, distributed processing
- Challenges in analyzing large datasets: scalability, performance, data variety
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AI in Data Analysis
- Applying AI in Big Data – predictions, pattern recognition
- Overview of AI tools: TensorFlow, PyTorch, MLlib, AutoML
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Day 2: Data Processing with Apache Spark and AI
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Real-time Data Processing
- Workshop: building a data pipeline in Apache Spark (batch and stream processing)
- Performance optimization: data partitioning and distributed memory usage
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Integration with AI Tools
- Implementing AI models in Spark MLlib – classification and regression case study
- Workshop: training a predictive model on a large dataset
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Day 3: Visualization, Analysis, and Practical Implementation
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Big Data Visualization
- Creating dynamic reports with Power BI, Tableau, and Python (Seaborn, Plotly)
- Workshop: designing interactive dashboards for large dataset analysis
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Practical Applications of Big Data
- Case studies: demand forecasting, user behavior analysis, business process optimization
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Workshop: implementing a complete Big Data analysis project – from data processing to
interpreting results
