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Item number: 137658030

Data Mining and Decision Making Training

Item number: 137658030

Data Mining and Decision Making Training

159,00 192,39 Incl. tax

Data Mining and Decision Making E-Learning Training Certified Teachers Exam Quizzes Assessments Test Exam Live Labs Tips Tricks Certificate.

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Data Mining and Decision Making E-Learning

Order this unique E-Learning course Data Mining and Decision Making online!
✔️ 1 year 24/7 access to rich interactive videos, speech, progress monitoring through reports and tests per chapter to immediately test your knowledge.
✔️ Discover how to convert data into valuable insights for better decisions within your organization.

Why choose this course?

In today's business world, it is becoming increasingly important to make data-driven decisions. With Data Mining and Decision Making you will learn how to discover valuable patterns in large amounts of data and use these insights for strategic decisions. This course provides you with the tools and techniques needed to improve decision-making processes, solve problems and even make predictions based on data.

What you will learn:

  • Basics of Data Mining: Understand the fundamentals of data mining and learn how to search data sets for important information and hidden patterns.
  • Data Analysis Techniques: Gain an in-depth understanding of different analysis methods, such as classification, clustering, and regression analysis.
  • Decision-making models: Learn how to translate insights from data mining into decisions that impact business operations and strategy.
  • Practical Applications: Discover how to use data for risk management, customer segmentation, and other strategic business decisions.
  • Tools and software: Get to know the software and tools used in data mining and decision-making so you can apply your skills effectively.

This course is ideal for professionals who want to harness the power of data to improve the quality of their decisions.

Who should participate?

This training is suitable for:

  • Data analysts who want to expand their knowledge into the field of data mining and making decisions based on data.
  • Leaders and managers who want to apply data-driven strategies to make better business decisions.
  • Business Intelligence professionals responsible for collecting, analyzing and interpreting data for decision making.
  • Decision makers in different sectors who want to learn how to use data for improved operational and strategic choices.
  • Students and aspiring professionals who want to strengthen their skills in data analysis and understand how to apply them in practice.

Course content

Data Mining and Decision Making: Modern Data Science Lifecycle

Course: 54 Minutes

  • Course Overview
  • Data Science vs. Data Analysis
  • Data Science Project Steps and Processes
  • Establishing Data Science Project Business Value
  • Data Preparation Processes
  • Using Descriptive Analysis to Drive Decision-making
  • Using Predictive Analytics to Drive Decision-making
  • Interpreting Predictive Models in a Business Context
  • Machine Learning: Model Validation
  • Machine Learning: Model Implementation
  • Case Study: Data-driven Decision-making
  • Course Summary

Data Mining and Decision Making: Data Preparation & Predictive Analytics

Course: 41 Minutes

  • Course Overview
  • Common Industrial and Commercial Data Sources
  • Data Collection Skills and Methods
  • Data Validation Best Practices
  • Data Cleaning Techniques
  • Data Exploration: Summary Statistics
  • Data Exploration: Summary Statistics II
  • Data Exploration: The Power of Visualization
  • Data Exploration: Advanced Visualization
  • Feature Engineering: Feature Generation
  • Feature Engineering: Feature Reduction
  • Course Summary

Data Mining and Decision Making: Data Mining for Answering Business Questions

Course: 1 Hour, 3 Minutes

  • Course Overview
  • Data Science, Data Analytics, and Machine Learning
  • Machine Learning Engineer vs. Data Science
  • Types of Machine Learning
  • How Do Machine Learning Algorithms Work?
  • Data Mining: Association Rules
  • Data Mining: Anomaly Detection
  • Data Mining: Customer Segmentation
  • Case Study: Walmart and Market Basket Analysis
  • Case Study: Customer Segmentation Analysis
  • Importance of Predictive Analysis in Business
  • Course Summary

Data Mining and Decision Making: Predictive Analytics for Business Strategies

Course: 57 Minutes

  • Course Overview
  • Data, Deep Learning, and Artificial Neural Networks
  • Artificial Neural Networks
  • Business Problems: Regression
  • Business Problems: Classification
  • Business Problems: Time Series
  • Business Problems: Actionable Recommender Systems
  • Recurrent and Convolutional Neural Networks
  • Natural Language Processing (NLP)
  • Computer Vision
  • World of Analytics: Integrated Futuristic Vision
  • Course Summary

Get started with Data Mining and Decision Making!

✔️ Learn at your own pace with interactive videos, exercises and hands-on scenarios.
✔️ Test your knowledge after each module with reports and tests to ensure that you have mastered everything.
✔️ Increase your decision-making skills by applying data analysis techniques in real-life business conditions.

Order your course now and discover how data can help you make better and smarter decisions!

Language English
Qualifications of the Instructor Certified
Course Format and Length Teaching videos with subtitles, interactive elements and assignments and tests
Lesson duration 3:32 Hours
Progress monitoring Yes
Access to Material 365 days
Technical Requirements Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge.
Support or Assistance Helpdesk and online knowledge base 24/7
Certification Certificate of participation in PDF format
Price and costs Course price at no extra cost
Cancellation policy and money-back guarantee We assess this on a case-by-case basis
Award Winning E-learning Yes
Tip! Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform.

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