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Data Management Tools, Machine Learning and AI Training

Data Management Tools, Machine Learning and AI Training

Course 4500

Duration: 1 day
Labs: Yes
Language: English
Level: Foundation

In this data management tools, machine learning and AI training, you will gain the foundational knowledge to manage your organisation’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 Delivery Methods

Attend online or bring this course to your facility

Data Management Tools, Machine Learning and AI Training Information

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
Analysing organisational 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

Visualisation

Effective visualisation – explaining your data
Visualisation 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

Get This Course 4 950 kr

1-day instructor-led course
Hands-on labs included
After-course computing sandbox included
After-course coaching available

Get the Advantage 37 295 kr

Take this course and gain unlimited access to more than 300 virtual instructor-led courses
Future-proof your career with more than 100 sought-after certifications in the market
Build real skills through hands-on learning in more than 180 virtual labs
Grow your skills and capabilities with more than one course at a time and save

Thank you for choosing subscriptions!

Include dates with afternoon start times

#4500

jun 11 15:00 - 22:30 CEST

Virtual
sep 18 15:00 - 22:30 CEST

Virtual
dec 9 15:00 - 22:30 CET

Virtual
mar 19 14:00 - 21:30 CET

Virtual

Bring this or any training to your organisation
Full-scale programme development
Delivered when, where, and how you want it
Blended learning models
Tailored content
Expert team coaching

Get the Advantage 37 295 kr

Take this course and gain unlimited access to more than 300 virtual instructor-led courses
Future-proof your career with more than 100 sought-after certifications in the market
Build real skills through hands-on learning in more than 180 virtual labs
Grow your skills and capabilities with more than one course at a time and save

Thank you for choosing subscriptions!

#4500

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Data Management Tools, Machine Learning and AI Training FAQs

The course has some demonstrations and workbooks with scripts for data analysis and management, but attendees do not have to do any programming (although there are some optional steps to do that for developers).

These are introduced and explained but not covered in depth.

The labs use remote desktops accessed through a browser and include short exercises and demos of data management, data analytics, and machine learning using online open-source/free workbooks and tools.

There are also classroom discussions and exercises that include “how to derive value from data” and “how to store and manage different types of data.”

No. The course uses local/workstation tools and connects to cloud resources that are not vendor-specific.

Data Management Tools, Machine Learning and AI Training

Data Management Tools, Machine Learning and AI Training Delivery Methods

Data Management Tools, Machine Learning and AI Training Information

Data Management Tools, Machine Learning and AI Training Outline

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

Module 2: Data Management Tools and Platforms

Module 3: Data Analytics – Understanding Your Data

Module 4: Machine Learning and AI

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

Upgrade your course experience with: Subscriptions

Get the Advantage 37 295 kr

Thank you for choosing subscriptions!

Upgrade your course experience with: Subscriptions

Get the Advantage 37 295 kr

Thank you for choosing subscriptions!

Data Management Tools, Machine Learning and AI Training FAQs

Does the course include any programming?

Does the course cover GenAI and Deep Learning?

What do the labs/exercises cover?

Does the course use Cloud computing providers/tools like AWS, Azure, and Google?

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