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Components of a Big Data and AI Solution Introduction
Course 1250
3 DAY COURSE

Course Outline

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. Plus, decision-makers 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!

Components of a Big Data and AI Solution Introduction Benefits

  • In this course, you will:

    • Store, manage, and analyze structured and unstructured data.
    • Select the appropriate storage type for different datasets.
    • Process large datasets efficiently using distributed systems like HDFS and Spark to extract valuable insights.
    • Apply common machine learning techniques such as clustering, classification, and regression using SparkML and Python.
    • Harness the power of generative models like ChatGPT programmatically.
    • Benefit from continued support with post-course one-on-one instructor coaching.
    • Access a computing sandbox for hands-on practice and experimentation.

  • Prerequisites

    None.

Data and AI Solution Course Outline

Module 1: Data and the Enterprise

Define the importance of data and its analysis in today's data-driven world

Differentiate between different types of data

Module 2: Storing and Querying Data

Describe different types of data storage

Assess the quality of data

Outline the ETL and ELT processes

Module 3: HDFS, Spark, and Kafka

Define Hadoop and HDFS

Describe Spark

Work with Kafka

Module 4: 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

Module 5: Analyzing and Interpreting Data

Discuss statistical analysis of Data

Explore machine learning including

Recommendations

Clustering

Classification

Module 6: Neural Networks

Introduce key ideas behind neural networks

Utilize deep neural networks for more complex problems

Examine generational neural networks

Module 7: Visualization

Visualize data to communicate results

Examine plots used for different purposes

Course Dates
Attendance Method
Note about the Certification Exam

When you register for the course, you will be prompted to choose Y/N to take the exam. Please select yes, as all HHS CISO employees are required to attempt the exam if one is offered for the course. Please be advised, if your course if funded by DIR, the Certification Organization has agreed to provide DIR the pass/fail status of your exam. DIR will only share this information in an aggregated report to state leadership that reflects total exam pass or fails. No individual names of any students will be included in any reports.

DIR requires that you submit the request for your exam voucher within one month of the last day of your course. DIR requires that you take your exam within six months of the last day of your course.

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