Data Management Tools, Machine Learning and AI Training

In this data management tools, machine learning and AI training, you will gain the foundational knowledge to manage your organization’s data assets and gain value from that data – through data analytics and machine learning to modern AI techniques and learn how modern data management can supply efficient solutions to technical, business, and administrative challenges.

This data management tools, machine learning and AI course includes 6 hours of ILT (Instructor-Led Training) or VILT (Virtual Instructor-Led Training) presented by a real-world expert instructor.

Data Management Tools, Machine Learning and AI Training Benefits

• In this machine learning training, you will learn how to:

  • Deliver business value using ML, AI, and Data Analytics
  • Manage corporate data assets using Data Warehouses and Data Integration
  • Explore ML and AI evolution and trends such as ChatGPT
  • Define business strategies for Data Management, ML, and AI
  • Leverage continued support with after-course one-on-one instructor coaching and computing sandbox

• Prerequisites

  Before taking this course, attendees should have:

  • Working knowledge of Internet and data technologies
  • A background in programming and data analysis is not needed.

Data Management Tools, Machine Learning and AI Training Outline

Module 1: Introduction to Data Management, ML, and AI

• Evolution of Data Management and Databases
• What are Data Analytics, Machine Learning, and AI; and how do they relate to each other?
• Industry standards and processes for Data Management – CRISP
• Big Data – Volume, Velocity, and Variety
• Analyzing organizational data  - what value does it have and how to exploit that

Module 2: Data Management Tools and Platforms

Data Management Platforms

• Hadoop and Spark
• Evolution of Data Management

Data Lakes and Data Warehouses

• Integration of Data Management with Traditional Databases
• NoSQL
• Data Catalogs and Metadata
• Data Pipelines and Data Warehouses

Cloud Tools for Data Management

• Data Warehouses
• Data Analytics
• Serverless Computing

Module 3: Data Analytics – Understanding Your Data

Types of Data

• Categorial Data
• Quantitative Data
• Deriving Features from Data
• Choosing the right Cloud data platforms

Exploratory Data Analysis

• Introduction to Statistics
• Data Exploration
• Introduction to Probability and Applying it in Practice
• Data Distributions

Visualization

• Effective visualization – explaining your data
• Visualization tools and techniques
• Creating engaging presentations

Module 4: Machine Learning and AI

Fundamentals of Machine Learning

• Decision Trees
• Classification
• Clustering
• Regression

Deep Learning, Neural Networks, and Generative AI

• Neural Networks
• Generative AI

Module 5: Applying Data Management and ML/AI in your workplace

• Creating a strategy
• Data Management Best Practices
• Next steps