Big Data Analysis Training with AI Tools
Level
IntermediateDuration
24h / 3 daysDate
Individually arrangedPrice
Individually arrangedBig Data Analysis Training with AI Tools
The Data Warehousing Training is an intensive two-day course focused on the practical application of leading data warehousing tools such as Amazon Redshift, Google BigQuery, and Snowflake. The training program is designed so that 80% of the time is dedicated to practical workshops, and 20% to theory. Participants will acquire the skills necessary to design, implement, and manage data warehouses in the cloud, working with real-world examples and use cases.rn
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
