Components of a Big Data and AI Solution Introduction (BIG111)
Course Length: 3 days
Unlock business potential with our Data and AI Solution course, covering Hadoop, Spark, Kafka, NoSQL, machine learning, neural networks, and data visualization.

Register or Request Training
- Private class for your team
- Live expert instructor
- Online or on‑location
- Customizable agenda
- Proposal turnaround within 1–2 business days
Course Overview
Unlock the true potential of your business with our cutting-edge Components of a Data and AI Solution course! This hands-on introduction takes you on a transformative journey from raw data to invaluable insights, leveraging the power of data and AI. Gain a competitive edge by understanding what tools can do and how to extract real business value from their output. Our comprehensive training integrates an overarching view of the data-to-insights process with focused data science expertise, empowering you to store, manage, process, and analyze massive volumes of structured and unstructured data. Decision-makers will benefit significantly from exposure to available options and establishing a common vocabulary with technical practitioners. Maximize your potential with our Components of a Data and AI Solution training today!
Course Benefits
- Define the importance of data and its analysis in today's data-driven world
- Differentiate between different types of data
- Describe different types of data storage
- Assess the quality of data
- Outline the ETL and ELT processes
- Define Hadoop and HDFS
- Describe Spark
- Work with Kafka
- Define NoSQL
- Introduce the different types of Big Data data stores
- Gain experience using Big Data data stores, including Redis, MongoDB, Cassandra, and Neo4j
- Perform text searches with Lucene and Elasticsearch
- Discuss statistical analysis of data
- Explore machine learning, including recommendations, clustering, and classification
- Introduce key ideas behind neural networks
- Utilize deep neural networks for more complex problems
- Examine generational neural networks
- Visualize data to communicate results
- Examine plots used for different purposes
Delivery Methods
Delivered for your team at your site or online.
Course Outline
- Data and the Enterprise
- Define the importance of data and its analysis in today's data-driven world
- Differentiate between different types of data
- Storing and Querying Data
- Describe different types of data storage
- Assess the quality of data
- Outline the ETL and ELT processes
- HDFS, Spark, and Kafka
- Define Hadoop and HDFS
- Describe Spark
- Work with Kafka
- NoSQL Databases
- Define NoSQL
- Introduce the different types of Big Data data stores
- Key-value
- Document
- Column family
- Graph
- Gain experience using Big Data data stores, including
- Redis
- MongoDB
- Cassandra
- Neo4j
- Perform text searches with Lucene and Elasticsearch
- Analyzing and Interpreting Data
- Discuss statistical analysis of data
- Explore machine learning, including
- Recommendations
- Clustering
- Classification
- Neural Networks
- Introduce key ideas behind neural networks
- Utilize deep neural networks for more complex problems
- Examine generational neural networks
- Visualization
- Visualize data to communicate results
- Examine plots used for different purposes
Class Materials
Each student receives a comprehensive set of materials, including course notes and all class examples.
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