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 test the knowledge directly.

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