Business intelligence and data mining with Power BI Course Overview

Certainly! Here are the minimum required prerequisites for successfully undertaking the training in Business Intelligence and Data Mining with Power BI:

• Basic Understanding of Data: Familiarity with basic data concepts, such as types of data (numeric, categorical), data collection, and data storage.
• Foundational Knowledge in Statistics: Basic knowledge of statistical measures such as mean, median, mode, variance, and standard deviation.
• Basic Computer Skills: Comfort with using computers and navigating software applications.
• Familiarity with Microsoft Excel: Basic skills in Microsoft Excel, including the ability to create and manipulate spreadsheets.
• Interest in Data Analysis: A strong interest in data analysis, data visualization, and business intelligence.
• Problem-Solving Skills: Basic problem-solving and analytical thinking skills.

These prerequisites are designed to ensure that you have the foundational knowledge necessary to effectively engage with the course content and fully benefit from the training provided.

Target Audience for Business intelligence and data mining with Power BI

1. Introduction:

The Business Intelligence and Data Mining with Power BI course focuses on statistical data analysis, machine learning, and data visualization to equip professionals with advanced data-driven decision-making skills.

2. Job Roles and Audience:

• Data Analysts
• Business Intelligence Analysts
• Data Scientists
• Machine Learning Engineers
• IT Managers
• Database Administrators
• Data Engineers
• Market Researchers
• Financial Analysts
• Operations Managers
• Business Consultants
• Software Developers
• Project Managers
• Healthcare Analysts
• Academic Researchers
• Maritime Transport Analysts
• Marketing Professionals
• Compliance Officers
• Risk Analysts
• Government Data Officers

Learning Objectives - What you will Learn in this Business intelligence and data mining with Power BI?

Course Introduction

This 7-day course on Business Intelligence and Data Mining with Power BI offers comprehensive training in statistical data mining, data processing, and machine learning integrations. Participants will gain hands-on experience with Power BI and other data mining tools to effectively analyze and interpret large datasets.

Learning Objectives and Outcomes

• Understand the Fundamentals of Data Mining and Data Processing

  • Overview and significance of data mining in modern industries.
  • Differences between data mining and data processing techniques.

• Master Data Cleaning and Pre-Processing Techniques

  • Techniques for handling missing data, outliers, and noise using Power BI.
  • Data transformation and normalization processes.

• Perform Exploratory Data Analysis (EDA)

  • Application of descriptive statistics: mean, median, mode, variance, and standard deviation.
  • Data visualization techniques: histograms, box plots, scatter plots, and heatmaps.
  • Identifying patterns and relationships within data.

• Apply Various Data Mining Techniques

  • Classification methods: decision trees, random forests, support vector machines, and k-nearest neighbors.
  • Clustering techniques: k-means, hierarchical clustering, and DBSCAN.
  • Association rule mining: Apriori and FP-Growth algorithms.
  • Anomaly